case study on tuberculosis

Remote Access
Save figures into PowerPoint
Download tables as PDFs

Infectious Diseases: A Case Study Approach

34: Tuberculosis

David Cluck

Download Chapter PDF

Disclaimer: These citations have been automatically generated based on the information we have and it may not be 100% accurate. Please consult the latest official manual style if you have any questions regarding the format accuracy.

Download citation file:

Search Book

Jump to a Section

Patient presentation.

Full Chapter
Supplementary Content

Chief Complaint

“I have a cough that won’t go away.”

History of Present Illness

A 63-year-old male presents to the emergency department with complaints of cough/shortness of breath which he attributes to a “nagging cold.” He states he fears this may be something worse after experiencing hemoptysis for the past 3 days. He also admits to waking up in the middle of the night “drenched in sweat” for the past few weeks. When asked, the patient denies ever having a positive PPD and was last screened “several years ago.” His chart indicates he was in the emergency department last week with similar symptoms and was diagnosed with community-acquired pneumonia and discharged with azithromycin.

Past Medical History

Hypertension, dyslipidemia, COPD, atrial fibrillation, generalized anxiety disorder

Surgical History

Appendectomy at age 18

Family History

Father passed away from a myocardial infarction 4 years ago; mother had type 2 DM and passed away from a ruptured abdominal aortic aneurysm

Social History

Retired geologist recently moved from India to live with his son who is currently in medical school in upstate New York. Smoked ½ ppd × 40 years and drinks 6 to 8 beers per day, recently admits to drinking ½ pint of vodka “every few days” since the passing of his wife 6 months ago.

Sulfa (hives); penicillin (nausea/vomiting); shellfish (itching)

Home Medications

Albuterol metered-dose-inhaler 2 puffs q4h PRN shortness of breath

Aspirin 81 mg PO daily

Atorvastatin 40 mg PO daily

Budesonide/formoterol 160 mcg/4.5 mcg 2 inhalations BID

Clonazepam 0.5 mg PO three times daily PRN anxiety

Lisinopril 20 mg PO daily

Metoprolol succinate 100 mg PO daily

Tiotropium 2 inhalations once daily

Venlafaxine 150 mg PO daily

Warfarin 7.5 mg PO daily

Physical Examination

Vital signs.

Temp 100.8°F, P 96, RR 24 breaths per minute, BP 150/84 mm Hg, pO 2 92%, Ht 5′10″, Wt 56.4 kg

Slightly disheveled male in mild-to-moderate distress

Normocephalic, atraumatic, PERRLA, EOMI, pale/dry mucous membranes and conjunctiva, poor dentition

Bronchial breath sounds in RUL

Cardiovascular

NSR, no m/r/g

Soft, non-distended, non-tender, (+) bowel sounds

Genitourinary

Get free access through your institution, pop-up div successfully displayed.

This div only appears when the trigger link is hovered over. Otherwise it is hidden from view.

Please Wait

Case report
Open access
Published: 19 November 2022

A case report of persistent drug-sensitive pulmonary tuberculosis after treatment completion

Sergo A. Vashakidze 1 , 2 ,
Abivarma Chandrakumaran 3 ,
Merab Japaridze 1 ,
Giorgi Gogishvili 1 ,
Jeffrey M. Collins 4 ,
Manana Rekhviashvili 1 &
Russell R. Kempker 4

BMC Infectious Diseases volume 22 , Article number: 864 ( 2022 ) Cite this article

6739 Accesses

1 Citations

2 Altmetric

Metrics details

Mycobacterium tuberculosis (Mtb) has been found to persist within cavities in patients who have completed their anti-tuberculosis therapy. The clinical implications of Mtb persistence after therapy include recurrence of disease and destructive changes within the lungs. Data on residual changes in patients who completed anti-tuberculosis therapy are scarce. This case highlights the radiological and pathological changes that persist after anti-tuberculosis therapy completion and the importance of achieving sterilization of cavities in order to prevent these changes.

Case presentation

This is a case report of a 33 year old female with drug-sensitive pulmonary tuberculosis who despite successfully completing standard 6-month treatment had persistent changes in her lungs on radiological imaging. The patient underwent multiple adjunctive surgeries to resect cavitary lesions, which were culture positive for Mtb. After surgical treatment, the patient’s chest radiographies improved, symptoms subsided, and she was given a definition of cure.

Conclusions

Medical therapy alone, in the presence of severe cavitary lung lesions may not be able to achieve sterilizing cure in all cases. Cavities can not only cause reactivation but also drive inflammatory changes and subsequent lung damage leading to airflow obstruction, bronchiectasis, and fibrosis. Surgical removal of these foci of bacilli can be an effective adjunctive treatment necessary for a sterilizing cure and improved long term lung health.

Peer Review reports

Mycobacterium tuberculosis treatment has been evolving over the years, especially with the introduction of newer drugs and shorter regimens [ 1 , 2 ]. Apart from the cavitary nature of tuberculous disease, patients who have been treated with current regimens often are given the designation of cure without achieving proper sterilization. Patients who complete the tuberculous regimen are given the definition of cure after they achieve sputum negativity but many of these patients harbor bacilli within cavities that continue to exert their effects on the respiratory system [ 3 ]. The residual changes that occur in patients who have completed medical therapy have been poorly attended to in the literature. Patients that underwent surgical and medical sterilization have been reported to have better pulmonary health in the long term, especially after the removal of cavities [ 4 ].

Here, we report a patient who underwent a complete regimen of medical therapy for pulmonary tuberculosis and later had to have surgical resection of her cavities, which grew tuberculous bacilli even after achieving sputum negativity.

A 33-year-old female from the country of Georgia presented to a tuberculosis dispensary on July 10, 2020, with a temperature of 38° C and symptoms of malaise, productive cough, and night sweats. The patient had no known medical problems. She reported smoking ~ 10 cigarettes daily and denied alcohol or illicit drug use. She had 3 children and her husband was a prisoner being treated for pulmonary tuberculosis. Upon physical examination there were decreased breath sounds in the upper lobes of the lungs with dullness to percussion. The patient had a body mass index (BMI) of 16.3 kg/m 2 . A complete blood count revealed a moderate leukocytosis of 10.2 × 10 9 /L and an erythrocyte sedimentation rate (ESR) of 42 mm/h. Biochemical blood parameters were normal. Sputum testing found a negative acid-fast bacilli (AFB) microscopy, positive Xpert MTB/RIF test (no RIF resistance), and positive culture for Mycobacterium tuberculosis (Mtb). Additionally, drug susceptibility testing (DST) revealed sensitivity to rifampin, isoniazid, and ethambutol. Chest radiography revealed multiple small foci in the upper lobes of both lungs and a cavity in the right lung (Fig. 1 A). The patient was initiated on daily outpatient treatment with three pills of a fixed dosed combination pill containing isoniazid 75 mg, rifampin 150 mg, ethambutol 275 mg and pyrazinamide 400 mg. Treatment was given through directly observed therapy (DOT). She converted her sputum cultures to negative at 2 months and continued rifampin and isoniazid to finish 6 months of treatment. An end of treatment chest x-ray revealed fibrosis and honeycombing in the right upper lung, and fibrosis and dense focal shadows in the 1st and 2nd intercostal spaces of the left lung (Fig. 1 B). The complete treatment timeline is summarized in Fig. 2 .

A (left): Baseline chest X-ray showing a cavity in the right lung and multiple foci in the upper lobes of both lungs. B (right): End of initial treatment chest X-ray, showing fibrosis, local honeycombing and dense focal shadows in both lungs

Patient treatment timeline ( HRZE isoniazid, rifampin, pyrazinamide, ethambutol; HR isoniazid & rifampin; DOTS directly observed therapy, short-course; CT computed tomography; AFB acid fast bacilli)

A follow up chest computed tomography (CT) scan demonstrated a cavity in the right upper lobe measuring 12 × 10 mm in size with a thick and heterogeneous wall and nodules and bronchiectasis in the left lung (Fig. 3 A–D). Based on CT findings and in accordance with National tuberculosis guidelines, the patient was offered surgical resection of the affected portion of the lung. It should be noted that the patient reported no symptoms, complaints, or functional disability before the surgery. Preoperative workup including pulmonary function testing, an echocardiogram, bronchoscopy, and blood chemistries were normal. The patient consented to surgery and underwent a surgical resection of the S1 and S2 segments of the right lung 2 weeks later. Intraoperatively, moderate adhesions were visualized in the S1 and S2 area with a palpable dense formation ~ 3.0 cm in diameter, in addition to a dense nodule. Gross pathology of the resected lesion showed a thick-walled fibrous cavity filled with caseous necrosis (Fig. 4 A) corresponding to the right preoperative CT lesion seen on Fig. 3 A, C.

CT scan (January 11, 2021) showing, A a cavity in the upper lobe of the right lung with heterogeneous thick walls. B S1 and S2 segments of the left lung shows a 23 × 18 mm oval shaped calcified inclusions; C , D areas with calcified, compacted nodules 13 × 20 mm in size with additional traction bronchiectasis

A Gross pathological image of a resected cavity with caseous material from first surgery (S1 & S2 segment of right lung). B The gross pathology from the second surgery showed the presence of a blocked cavity measuring up to 2 cm in diameter filled with caseous material in the S1, S2 and C Tuberculoma in S6 segment

Microbiological analysis on the resected tissue revealed acid-fast bacilli on microscopy, and positive Xpert MTB/RIF and culture results. Mtb grew from the caseous center, inner and outer walls of the cavity and a resected foci located ~ 3 cm from the cavity. DST revealed sensitivity to isoniazid, rifampin, and ethambutol.

Pathological examination of the resected lesion showed findings consistent with fibrocavernous tuberculosis. No postoperative complications were experienced, and the patient reinitiated first-line therapy via DOT on the 2nd postoperative day and was discharged on postoperative day 11.

A follow up CT scan performed after 3 months showed postoperative changes in the right upper lobe, and an unchanged left lung (Fig. 5 A–C). Based on the persistent conglomerate of tuberculomas and multiple small tuberculous foci, growth of Mtb from the previous surgical specimen, and the patient’s social situation (mother of three young children) a second surgery to optimize the chance of cure was recommended. The patient reported no symptoms, complaints, or functional disability before the surgery. Preoperative sputum testing found negative AFB smear microscopy and culture. The patient underwent the second operation on May 18, 2021, in which the S1, S2 and part of the S6 segment of the left lung were resected. Intraoperatively, moderate adhesions seen along with a dense palpable ~ 3 cm mass in the S1 and S2 region and a dense focus in S6.

A – C Follow-up CT scan after first adjunctive surgery showing postoperative changes of the right lung and radiological changes in the left lung, that were unchanged compared to the initial CT. D Final CT scan showing normal postoperative changes with no cavities as previously seen

Microbiological examinations performed on resected tissue revealed positive AFB smear microscopy and Xpert MTB/RIF results and a negative AFB culture. The pathological examination of the surgical samples indicated a variety of destructive changes in addition to ongoing inflammation. The gross specimen of S1 and S2 segments of the left lung showed fibrocavernous tuberculosis shown in Fig. 4 B, which corresponds to the left lung lesion seen on the first preoperative CT in Figs. 3 B and 5 A in the second preoperative CT; the gross specimen of the S6 segment showed progressive tuberculoma seen in Fig. 4 C, which corresponds to the left lung lesion seen on the first preoperative CT in Figs. 3 D and 5 C in the second preoperative CT.

There were no postoperative complications, and tuberculosis (TB) treatment was reinitiated. The patient successfully completed treatment with normalization of clinical and laboratory parameters and a clinical outcome of cure in September 2021, ~ 14 months after beginning treatment. The patient had reported near complete resolution of her symptoms, having a much better ability to perform her daily activities. The patient appreciated the effects surgery had on her recovery and was happy to have gone through that treatment route. A post treatment CT scan demonstrated postoperative changes in the upper segments of both lungs (Fig. 5 D). Results from post treatment lung function testing were all within normal range.

Discussion and conclusions

We present this case to highlight the heterogeneous nature of pulmonary tuberculosis and need for an individualized treatment approach, especially for patients with cavitary disease. Over the last decade, novel diagnostics, drugs, and treatment regimens have revolutionized TB management including a recent landmark clinical trial demonstrating an effective 4-month regimen for drug-susceptible TB [ 1 ]. The move towards shorter regimens is critical to improve treatment completion rates and help meet TB elimination goals. However, during a transition to shorter treatment durations it is imperative that clinicians remain aware of complex and severe pulmonary TB cases that may require longer durations of treatment and adjunctive therapies such as surgery. Supporting evidence comes from a recent landmark study finding persistent inflammation on imaging associated with finding Mtb mRNA in sputum after successful treatment and a meta-analysis demonstrating a hard-to-treat TB phenotype not cured with the standard 6 months of treatment [ 2 , 5 ]. However, regarding recommendations for prolonging treatment beyond 6 months for drug-susceptible pulmonary tuberculosis, ATS/CDC/IDSA recommends (expert opinion) extended treatment for persons with cavitary disease and a positive 2 month culture (our patient would not have met this criteria); World Health Organization (WHO) does not recommend extended treatment for any persons with drug-susceptible TB [ 6 , 7 ]. Accumulating evidence demonstrates surgical resection may be an effective adjunctive treatment in cases with cavitary disease [ 8 , 9 , 10 , 11 , 12 ]. Ultimately, a precision medicine approach towards TB will be able to identify patients who would benefit from short course therapy and those who would benefit from longer therapy and adjunctive treatment including surgery [ 13 ].

Mtb has a unique ability and propensity to induce cavities in humans with various studies showing cavitary lesions in ~ 30 to 85% of patients with pulmonary tuberculosis [ 14 ]. Lung cavities are more common in certain groups including patients with diabetes mellitus and undernutrition such as our patient who had a baseline BMI of 16.3 kg/m 2 [ 15 , 16 ]. Their presence indicates more advanced and severe pulmonary disease as evidenced by their association with worse clinical outcomes. Cavitary disease has been associated with higher rates of treatment failure, disease relapse, acquired drug resistance, and long term-term pulmonary morbidity [ 2 , 17 , 18 , 19 ]. The impact of cavitary disease may be more pronounced in drug-resistant disease as shown in an observational study from our group which found a five times higher rate of acquired drug resistance and eight times higher rate of treatment failure among patients multidrug- or extensively drug-resistant cavitary disease compared to those without [ 20 ].

Mtb cavities are characterized by a fibrotic surface with variable vascularization, a lymphocytic cuff at the periphery followed by a cellular layer consisting of primarily macrophages and a necrotic center with foamy apoptotic macrophages and high concentrations of bacteria. Historically, each portion of the TB cavity has been conceptualized as concentric layers of a spherical structure due to its appearance on histologic cross-sections. However, recent studies using more detailed imaging techniques have shown most TB cavities exhibit complex structures with diverse, branching morphologies [ 21 ]. A dysregulated host immune response to Mtb is thought to contribute to the development of lung cavities, which may explain why cavitary lesions are seen less frequently among immunosuppressed patients including people living with Human Immunodeficiency Virus (HIV) [ 14 ]. The center of the TB cavity (caseum) is characterized by accumulation of pro-inflammatory lipid signaling molecules (eicosanoids) and reactive oxygen species, which result in ongoing tissue destruction, but do little to control Mtb replication [ 22 ]. Conversely, the cellular rim and lymphocytic cuff are characterized by a lower abundance of pro-inflammatory lipids and increases in immunosuppressive signals including elevated expression of TGF-beta and indoleamine-2,3-dioxygenase-1 [ 22 ]. The anti-inflammatory milieu within these TB cavity microenvironments impairs effector T cell responses, further limiting control of bacterial replication [ 23 , 24 , 25 ].

The combination of impaired cell-mediated immune responses with accumulation of inflammatory mediators at the rim of the caseum leads to ongoing tissue destruction with the potential for long-term pulmonary sequelae. Many with cavitary tuberculosis suffer chronic obstructive pulmonary disease after successful treatment and the risk may be greater in those with multidrug-resistant disease [ 3 , 4 ]. This has led to research into adjunctive treatment with immune modulator therapies with a goal of mitigating the over-exuberant inflammatory response at the interior edge of the cavity to limit tissue damage. In a recent randomized clinical trial, patients with radiographically severe pulmonary tuberculosis treated with adjunctive everolimus or CC-11050 (phosphodiesterase inhibitor with anti-inflammatory properties) achieved better long-term pulmonary outcomes versus those who received placebo [ 26 ]. Such results suggest the inflammatory response can be modified with appropriate host-directed therapies to improve pulmonary outcomes, particularly in those with cavitary tuberculosis.

Tuberculosis cavities not only hinder an effective immune response, but also prevent anti-tuberculosis drugs from achieving sterilizing concentrations throughout the lesion and especially in necrotic regions. The necrotic center of cavitary lesions is associated with extremely high rates of bacilli (up to 10 9 per milliliter), many of which enter a dormant state with reduced metabolic activity. Bacilli in this dormant state may be less responsive to the host immune response and exhibit phenotypic resistance to some anti-tuberculosis drugs thereby preventing sterilization and increasing chances of relapse [ 14 , 27 , 28 ]. The fact that the specimens from our patient’s second surgery were Xpert and AFB positive, but culture negative may indicate the presence of either dead bacilli or metabolically altered(dormant) bacilli that may be alive, but not culturable by standard techniques. Further, genomic sequencing studies have also found distinct strains of Mtb within different areas of the cavity that have varying drug-susceptibilities demonstrating cavities as a potential incubator for drug resistance [ 27 , 29 ].

Emerging literature has started to elucidate the varying abilities of drugs to penetrate into cavitary lesions and the importance of adequate target site concentrations. One notable study found that decreasing tissue concentrations within resected cavitary TB lesions were associated with increasing drug phenotypic MIC values [ 30 ]. Innovative studies using MALDI mass spectrometry imaging have further demonstrated varied spatiotemporal penetration of anti-TB drugs in human TB cavities [ 31 ]. This study found rifampin accumulated within caseum, moxifloxacin preferentially at the cellular rim, and pyrazinamide throughout the lesion, demonstrating the need to consider drug penetration when designing drug regimens in patients with cavitary TB. Computational modeling studies have further demonstrated the importance of complete lesion drug coverage to ensure relapse-free cure [ 32 ]. Furthermore, clinical trials are now incorporating these principles into study design by (1) using radiological characteristics to determine treatment length and (2) incorporating tissue penetration into drug selection and regimen design [ 33 , 34 ]. Beyond tissue penetration, varying drug levels and rapid INH acetylation status can also lead to suboptimal pharmacokinetics and poor clinical outcomes [ 35 , 36 ]. As highlighted in a recent expert document, clinical standards to optimize and individualize dosing need to be developed to improve outcomes [ 37 ].

Available literature points to a benefit of adjunctive surgical resection particularly among patients with drug resistant tuberculosis. A meta-analysis of 24 comparative studies found surgical intervention was associated with favorable treatment outcomes among patients with drug-resistant TB (odds ratio 2.24, 95% CI 1.68–2.97) [ 38 ]. Additionally, an individual patient data meta-analysis found that partial lung resection (adjusted OR 3.9, 95% CI 1.5–5.9) but not pneumectomy was associated with treatment success [ 39 ]. In two observational studies, we have also found that adjunctive surgical resection was associated with high and improved outcomes compared to patients with cavitary disease not undergoing surgery and was associated with less reentry into TB care. It should be noted that all studies of surgical resection for pulmonary TB were observational studies, which may be subject to selection bias, and no clinical trials (very difficult to implement in practice) were conducted to provide more conclusive evidence. Based on available evidence, the WHO has provided guidance to consider surgery among certain hard to treat cases of both drug-susceptible and resistant cavitary disease [ 40 ]. Criteria for surgical intervention included (1) failure of medical therapy (persistent sputum culture positive for M. tuberculosis ), (2) a high likelihood of treatment failure or disease relapse, (3) complications from the disease, (4) localized cavitary lesion, and (5) sufficient pulmonary function to tolerate surgery. For our patient, the severity of disease, lack of improvement of radiological imaging despite appropriate treatment, and high risk of relapse were the main indicators for surgery. Contraindications for surgery included a forced expiratory volume (FEV1) < 1000 mL, severe malnutrition, or patients at high risk for perioperative cardiovascular complications. With strict adherence to indications and contraindications for surgery, an acceptable level of postoperative complications are noted (5–17%) [ 4 , 38 ]. Our results also demonstrate the safety of adjunctive surgery, as our post-operative complication rate (8%) was low with the majority being minor complications [ 41 ].

As our case highlights, patients with persistent cavitary disease at the end of treatment require close clinical follow up and a tailored, individualized plan to determine the best approach for disease elimination and cure. In certain cases, including those with persistent cavitary disease and end of treatment, and where available, surgical resection is an effective adjunctive treatment option that can reduce disease burden and aid anti-tuberculosis agents in providing a sterilizing cure. As we enter an era of welcomed new shorter treatment options for tuberculosis it is imperative for clinicians to be able to identify and recognize complicated TB cases that require prolonged treatment and potentially adjunctive surgery.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

Acid fast bacilli

American Thoracic Society

Body mass index

Center for Disease Control

Computed tomography

Directly observed therapy

Drug sensitive tuberculosis

Erythrocyte sedimentation rate

Human Immunodeficiency Virus

Infectious Diseases Society of America

Mycobacterium tuberculosis

Tuberculosis

World Health Organization

Dorman S, Nahid P, Kurbatova E, Phillips P, Bryant K, Dooley K, et al. Four-month rifapentine regimens with or without moxifloxacin for tuberculosis. N Engl J Med. 2021;384(18):1705–18.

Article PubMed PubMed Central CAS Google Scholar

Imperial M, Nahid P, Phillips P, Davies G, Fielding K, Hanna D, et al. A patient-level pooled analysis of treatment-shortening regimens for drug-susceptible pulmonary tuberculosis. Nat Med. 2018;24(11):1708–15.

Vashakidze S, Kempker J, Jakobia N, Gogishvili S, Nikolaishvili K, Goginashvili L, et al. Pulmonary function and respiratory health after successful treatment of drug-resistant tuberculosis. Int J Infect Dis. 2019;82:66–72.

Article PubMed PubMed Central Google Scholar

Harris RC, Khan MS, Martin LJ, et al. The effect of surgery on the outcome of treatment for multidrug-resistant tuberculosis: a systematic review and meta-analysis. BMC Infect Dis. 2016;16:262.

Malherbe S, Shenai S, Ronacher K, Loxton A, Dolganov G, Kriel M, et al. Persisting positron emission tomography lesion activity and Mycobacterium tuberculosis mRNA after tuberculosis cure. Nat Med. 2016;22(10):1094–100.

Nahid P, Dorman S, Alipanah N, Barry P, Brozek J, Cattamanchi A, et al. Official American Thoracic Society/Centers for Disease Control and Prevention/Infectious Diseases Society of America clinical practice guidelines: treatment of drug-susceptible tuberculosis. Clin Infect Dis. 2016;63(7):e147–95.

World Health Organization. The WHO consolidated guidelines on tuberculosis, module 4: treatment—drug-susceptible tuberculosis treatment. Geneva: WHO; 2022.

Google Scholar

Kang M, Kim H, Choi Y, Kim K, Shim Y, Koh W, et al. Surgical treatment for multidrug-resistant and extensive drug-resistant tuberculosis. Ann Thorac Surg. 2010;89(5):1597–602.

Article PubMed Google Scholar

Pomerantz B, Cleveland J, Olson H, Pomerantz M. Pulmonary resection for multi-drug resistant tuberculosis. J Thorac Cardiovasc Surg. 2001;121(3):448–53.

Article PubMed CAS Google Scholar

Somocurcio J, Sotomayor A, Shin S, Portilla S, Valcarcel M, Guerra D, et al. Surgery for patients with drug-resistant tuberculosis: report of 121 cases receiving community-based treatment in Lima, Peru. Thorax. 2007;62(5):416–21.

Dravniece G, Cain K, Holtz T, Riekstina V, Leimane V, Zaleskis R. Adjunctive resectional lung surgery for extensively drug-resistant tuberculosis. Eur Respir J. 2009;34(1):180–3.

Wang H, Lin H, Jiang G. Pulmonary resection in the treatment of multidrug-resistant tuberculosis: a retrospective study of 56 cases. Ann Thorac Surg. 2008;86(5):1640–5.

Lange C, Aarnoutse R, Chesov D, van Crevel R, Gillespie S, Grobbel H, et al. Perspective for precision medicine for tuberculosis. Front Immunol. 2020. https://doi.org/10.3389/fimmu.2020.566608 .

Urbanowski M, Ordonez A, Ruiz-Bedoya C, Jain S, Bishai W. Cavitary tuberculosis: the gateway of disease transmission. Lancet Infect Dis. 2020;20(6):e117–28.

Zafar M, Chen L, Xiaofeng Y, Gao F. Impact of diabetes mellitus on radiological presentation of pulmonary tuberculosis in otherwise non-immunocompromised patients: a systematic review. Curr Med Imaging Rev. 2019;15(6):543–54.

Sinha P, Bhargava A, Carwile M, Cintron C, Cegielski J, Lönnroth K, et al. Undernutrition can no longer be an afterthought for global efforts to eliminate TB. Int J Tuberc Lung Dis. 2022;26(6):477–80.

Cegielski J, Dalton T, Yagui M, Wattanaamornkiet W, Volchenkov G, Via L, et al. Extensive drug resistance acquired during treatment of multidrug-resistant tuberculosis. Clin Infect Dis. 2014;59(8):1049–63.

Gao J, Ma Y, Du J, Zhu G, Tan S, Fu Y, et al. Later emergence of acquired drug resistance and its effect on treatment outcome in patients treated with Standard Short-Course Chemotherapy for tuberculosis. BMC Pulm Med. 2016. https://doi.org/10.1186/s12890-016-0187-3 .

Shin S, Keshavjee S, Gelmanova I, Atwood S, Franke M, Mishustin S, et al. Development of extensively drug-resistant tuberculosis during multidrug-resistant tuberculosis treatment. Am J Respir Crit Care Med. 2010;182(3):426–32.

Kempker R, Kipiani M, Mirtskhulava V, Tukvadze N, Magee M, Blumberg H. Acquired drug resistance in Mycobacterium tuberculosis and poor outcomes among patients with multidrug-resistant tuberculosis. Emerg Infect Dis. 2015;21(6):992–1001.

Wells G, Glasgow J, Nargan K, Lumamba K, Madansein R, Maharaj K, et al. Micro-computed tomography analysis of the human tuberculous lung reveals remarkable heterogeneity in three-dimensional granuloma morphology. Am J Respir Crit Care Med. 2021;204(5):583–95.

Marakalala M, Raju R, Sharma K, Zhang Y, Eugenin E, Prideaux B, et al. Inflammatory signaling in human tuberculosis granulomas is spatially organized. Nat Med. 2016;22(5):531–8.

McCaffrey E, Donato M, Keren L, Chen Z, Delmastro A, Fitzpatrick M, et al. The immunoregulatory landscape of human tuberculosis granulomas. Nat Immunol. 2022;23(2):318–29.

Gern B, Adams K, Plumlee C, Stoltzfus C, Shehata L, Moguche A, et al. TGFβ restricts expansion, survival, and function of T cells within the tuberculous granuloma. Cell Host Microbe. 2021;29(4):594-606.e6.

Gautam U, Foreman T, Bucsan A, Veatch A, Alvarez X, Adekambi T, et al. In vivo inhibition of tryptophan catabolism reorganizes the tuberculoma and augments immune-mediated control of Mycobacterium tuberculosis. Proc Natl Acad Sci USA. 2017. https://doi.org/10.1073/pnas.1711373114 .

Wallis R, Ginindza S, Beattie T, Arjun N, Likoti M, Edward V, et al. Adjunctive host-directed therapies for pulmonary tuberculosis: a prospective, open-label, phase 2, randomised controlled trial. Lancet Respir Med. 2021;9(8):897–908.

Kaplan G, Post F, Moreira A, Wainwright H, Kreiswirth B, Tanverdi M, et al. Mycobacterium tuberculosis growth at the cavity surface: a microenvironment with failed immunity. Infect Immun. 2003;71(12):7099–108.

Fattorini L, Piccaro G, Mustazzolu A, Giannoni F. Targeting dormant bacilli to fight tuberculosis. Mediterr J Hematol Infect Dis. 2013;5(1):e2013072.

Moreno-Molina M, Shubladze N, Khurtsilava I, Avaliani Z, Bablishvili N, Torres-Puente M, et al. Genomic analyses of Mycobacterium tuberculosis from human lung resections reveal a high frequency of polyclonal infections. Nat Commun. 2021;12(1):2716.

Dheda K, Lenders L, Magombedze G, Srivastava S, Raj P, Arning E, et al. Drug-penetration gradients associated with acquired drug resistance in patients with tuberculosis. Am J Respir Crit Care Med. 2018;198(9):1208–19.

Prideaux B, Via L, Zimmerman M, Eum S, Sarathy J, O’Brien P, et al. The association between sterilizing activity and drug distribution into tuberculosis lesions. Nat Med. 2015;21(10):1223–7.

Strydom N, Gupta S, Fox W, Via L, Bang H, Lee M, et al. Tuberculosis drugs’ distribution and emergence of resistance in patient’s lung lesions: a mechanistic model and tool for regimen and dose optimization. PLoS Med. 2019;16(4): e1002773.

Chen R, Via L, Dodd L, Walzl G, Malherbe S, Loxton A, et al. Using biomarkers to predict TB treatment duration (predict TB): a prospective, randomized, noninferiority, treatment shortening clinical trial. Gates Open Res. 2017;1:9.

Bartelink I, Zhang N, Keizer R, Strydom N, Converse P, Dooley K, et al. New paradigm for translational modeling to predict long-term tuberculosis treatment response. Clin Transl Sci. 2017;10(5):366–79.

Pasipanodya J, Srivastava S, Gumbo T. Meta-analysis of clinical studies supports the pharmacokinetic variability hypothesis for acquired drug resistance and failure of antituberculosis therapy. Clin Infect Dis. 2012;55(2):169–77.

Colangeli R, Jedrey H, Kim S, Connell R, Ma S, Chippada Venkata U, et al. Bacterial factors that predict relapse after tuberculosis therapy. N Engl J Med. 2018;379(9):823–33.

Alffenaar J, Stocker S, Forsman L, Garcia-Prats A, Heysell S, Aarnoutse R, et al. Clinical standards for the dosing and management of TB drugs. Int J Tuberc Lung Dis. 2022;26(6):483–99.

Marrone M, Venkataramanan V, Goodman M, Hill A, Jereb J, Mase S. Surgical interventions for drug-resistant tuberculosis: a systematic review and meta-analysis [review article]. Int J Tuberc Lung Dis. 2013;17(1):6–16.

Fox G, Mitnick C, Benedetti A, Chan E, Becerra M, Chiang C, et al. Surgery as an adjunctive treatment for multidrug-resistant tuberculosis: an individual patient data metaanalysis. Clin Infect Dis. 2016;62(7):887–95.

Word Health Organization Europe. The role of surgery in the treatment of pulmonary TB and multidrug and extensively drug-resistant TB. Copenhagen: WHO Regional Office for Europe; 2014.

Vashakidze SA, Gogishvili SG, Nikolaishvili KG, et al. Adjunctive surgery versus medical treatment among patients with cavitary multidrug-resistant tuberculosis. Eur J Cardiothorac Surg. 2021;60(6):1279–85. https://doi.org/10.1093/ejcts/ezab337 .

Download references

Acknowledgements

The authors thank the physicians, nurses, and staff at the NCTLD in Tbilisi, Georgia, who provided care for the patient described in this report. Additionally, the authors are thankful for the patient with pulmonary tuberculosis who was willing to have their course of illness presented and help contribute meaningful data that may help future patients with the same illness.

This study did not receive any specific funding.

Author information

Authors and affiliations.

Thoracic Surgery Department, National Center for Tuberculosis and Lung Diseases, 50 Maruashvili, 0101, Tbilisi, Georgia

Sergo A. Vashakidze, Merab Japaridze, Giorgi Gogishvili & Manana Rekhviashvili

The University of Georgia, Tbilisi, Georgia

Sergo A. Vashakidze

Tbilisi State Medical University, Tbilisi, Georgia

Abivarma Chandrakumaran

Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA

Jeffrey M. Collins & Russell R. Kempker

You can also search for this author in PubMed Google Scholar

Contributions

SAV: Conceptualization; Data collection and interpretation; Scientific Writing including initial draft preparation and manuscript revision and editing. AC: Data interpretation; Table and Figure preparation; Literature review; Scientific Writing including initial draft preparation and manuscript revision and editing. MJ: Data collection; Scientific Writing including manuscript review and editing. GG: Data collection; Scientific Writing including manuscript review and editing. JMC: Data interpretation; Scientific Writing including manuscript review and editing. MR: Data interpretation; Scientific Writing including manuscript review and editing. RRK: Conceptualization; Literature review; Scientific Writing including manuscript review and editing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sergo A. Vashakidze .

Ethics declarations

Ethics approval and consent to participate.

The authors confirm that written informed consent has been obtained from the patient involved in the case report. Ethics approval is not needed for case reports according to our institutional (National Center for Tuberculosis and Lung Disease) review board.

Consent for publication

The authors confirm that written consent has been obtained from the patient for publication of images.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Vashakidze, S.A., Chandrakumaran, A., Japaridze, M. et al. A case report of persistent drug-sensitive pulmonary tuberculosis after treatment completion. BMC Infect Dis 22 , 864 (2022). https://doi.org/10.1186/s12879-022-07836-y

Download citation

Received : 08 August 2022

Accepted : 02 November 2022

Published : 19 November 2022

DOI : https://doi.org/10.1186/s12879-022-07836-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Thoracic surgery

BMC Infectious Diseases

ISSN: 1471-2334

General enquiries: [email protected]

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
My Bibliography
Collections
Citation manager

Save citation to file

Email citation, add to collections.

Create a new collection
Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

Search in PubMed
Search in NLM Catalog
Add to Search

A case study of a patient with multidrug-resistant tuberculosis

Affiliation.

1 Community nurse working in South West England.
PMID: 30048191
DOI: 10.12968/bjon.2018.27.14.806

In this case study, a nurse presents her reflections on the challenges of supporting a patient through his treatment journey for multidrug-resistant tuberculosis. The patient has significant comorbidities and social issues, such as diabetes and homelessness. There was also a language barrier. All these aspects made the management of his treatment challenging. The medication side effects and his lifestyle were also a barrier to full engagement. The same multidisciplinary team was involved with the patient and, despite the obstacles, he seemed willing to engage with treatment and the team.

Keywords: Comorbidities; Language barrier; Multidisciplinary team; Multidrug-resistant tuberculosis; Pulmonary TB; Under-served population.

PubMed Disclaimer

Related information

Linkout - more resources, full text sources, other literature sources.

scite Smart Citations
Genetic Alliance

Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

CASE STUDY ON PULMONARY TUBERCULOSIS

January 2017
This person is not on ResearchGate, or hasn't claimed this research yet.

Tamil Nadu Dr. M.G.R. Medical University

Vel's Group of Institutions

Discover the world's research

25+ million members
160+ million publication pages
2.3+ billion citations

J T Crawford
T M Shinnick
JL Kamerbeek

EMERG INFECT DIS
Gaby E. Pfyffer

Dick van Soolingen
Mamadou Daffé
Michael R. McNeil
Patrick J. Brennan
D Soolingen
T Hoogenboezem
Pwm Hermans
K S Teppema
Recruit researchers
Join for free
Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Fact sheets
Facts in pictures
Publications
Questions and answers
Tools and toolkits
Endometriosis
Excessive heat
Mental disorders
Polycystic ovary syndrome
All countries
Eastern Mediterranean
South-East Asia
Western Pacific
Data by country
Country presence
Country strengthening
Country cooperation strategies
News releases
Feature stories
Press conferences
Commentaries
Photo library
Afghanistan
Cholera
Coronavirus disease (COVID-19)
Greater Horn of Africa
Israel and occupied Palestinian territory
Disease Outbreak News
Situation reports
Weekly Epidemiological Record
Surveillance
Health emergency appeal
International Health Regulations
Independent Oversight and Advisory Committee
Classifications
Data collections
Global Health Estimates
Mortality Database
Sustainable Development Goals
Health Inequality Monitor
Global Progress
World Health Statistics
Partnerships
Committees and advisory groups
Collaborating centres
Technical teams
Organizational structure
Initiatives
General Programme of Work
WHO Academy
Investment in WHO
WHO Foundation
External audit
Financial statements
Internal audit and investigations
Programme Budget
Results reports
Governing bodies
World Health Assembly
Executive Board
Member States Portal

Section navigation

Featured topics
Case-based TB surveillance
Country success stories
COVID-19, TB and India
TB and diabetes
TB guidelines

Digital, case-based, real-time surveillance for TB: status of progress

Tuberculosis (TB) surveillance is the continuous and systematic collection, analysis and reporting of data related to TB infection and TB disease in the population. To support countries to implement national surveillance systems for TB in a consistent and comparable way worldwide, the World Health Organization (WHO) has, since the mid-1990s, provided guidance with standardized definitions, forms, registers and reports ( 1 ). There were major updates to this guidance in 2006 ( 2 ) and 2013 ( 3 ).

A new edition of guidance on TB surveillance is in development and will be published in 2022. It will have an expanded scope that covers the full pathway of screening, diagnosis, treatment and care for people with TB infection and TB disease. It also aims to facilitate implementation of digital, case-based, real-time surveillance systems for TB, including the strengthening of systems that already exist and the transition to such systems elsewhere, especially in countries that are using a mixture of paper-based and digital systems or that rely primarily on paper-based systems.

Digital and case-based real-time surveillance systems for TB have several advantages over more traditional paper-based reporting of aggregated data. These include enabling the use of automated data quality checks, timely access to data and the availability of individual-level data for people with TB infection or disease, from the level of health facilities up to national level. These systems also greatly facilitate data analysis (including by age, sex and location) to inform adaptation and targeting of response efforts, both geographically and for specific population groups.

As of August 2021, data on the type of TB surveillance system in place at national level were available for 210 countries and territories ( Fig. 1 ). Of these, 130 reported having in place a digital, case-based surveillance system that covered all people diagnosed and reported with TB (both those with drug-susceptible TB and those with drug-resistant TB [DR-TB]). A further 14 countries, mainly in the WHO regions of Africa, the Americas and South-East Asia, had a case-based surveillance system only for people with DR-TB. Twenty countries reported that they were in the process of transitioning from a paper to digital system. About half of the countries in the WHO African Region still have paper-based systems for the recording and reporting of data.

The WHO Global TB Programme has been working with other WHO departments, the University of Oslo and the Global Fund to Fight AIDS, Tuberculosis and Malaria (Global Fund) to develop and support country implementation of digital packages for the collection, analysis, visualization and use of data from routine health facility information systems ( 4 ). This has built on WHO guidance about case-based digital TB surveillance ( 5 ), guidance on the routine analysis and use of TB data ( 6 ) and the WHO TB surveillance checklist of standards and benchmarks ( 7 ). The packages are based on WHO data standards and have been developed using DHIS2 software (because many countries have already chosen DHIS2 for use within their health information systems) but can be adapted for use with other software. Each package contains a machine-readable DHIS2 configuration, an analysis guide with a core set of indicators and dashboards, and an accompanying exercise book.

A TB-specific package for the digital management, analysis and use of key surveillance data in aggregated format has been available since early 2019 ( 8 ), 1 for use by countries that are not yet ready to transition to case-based digital surveillance. The TB package for case-based data, which enables the digital management of data for both drug-susceptible TB and DR-TB in a single system, has been available since late 2020 for download as a digital data configuration package in both English and French ( 8 ). Both TB packages are based on the latest WHO recording and reporting framework, and both allow extensive data analysis at different levels of the health system (e.g. health facility and subnational administrative area). The standard dashboards include graphs, tables and maps for core surveillance indicators (e.g. notifications, coverage of testing for drug resistance and HIV, and treatment outcomes) and data quality indicators (e.g. completeness and internal consistency).

The status of implementation and use of the WHO digital package for aggregated TB data is shown in Fig. 2 . Historical subnational TB data from 60 countries have been stored and can be analysed and visualized in this package. At national level, the digital package for aggregated data has already been implemented for ongoing collection, analysis, visualization (using standard dashboards) and reporting of data in 18 countries; an additional 12 countries are in the process of doing the same. In a further 22 countries, the package has been used to upload historical data for analysis during a national TB epidemiological review. As of August 2021, piloting of the TB digital package for case-based data was underway in four countries.

The longer term goal is that all countries are able to rely on a unified case-based digital environment for TB surveillance, along the complete pathway of prevention and care for people at risk of TB infection and TB disease; an illustration is shown in Fig. 3 . This will be supported by WHO standards for metadata, indicators and analytics (via a software-agnostic digital accelerator kit for TB, for countries that would like to develop the environment in the software of their choice), as well as a fully developed environment in DHIS2 (for countries that are looking for an off-the-shelf solution).

The success of case-based digital surveillance for TB in most countries is not just about the availability of technical products (e.g. digital packages, data standards and guidance). Other prerequisites include the necessary infrastructure, a competent core national health information and surveillance team, sufficient staffing and funding, and political commitment to TB data. WHO is currently developing standardized terms of reference for national assessments of readiness to adopt and implement case-based digital TB surveillance, in collaboration with stakeholders including national and local governments, technical agencies, funding agencies and civil society.

Fig. 1 Countries with national, case-based digital surveillance systems for TB, 2020

Fig. 2 Global status of implementation and use of the WHO TB DHIS2 packages for health facility and case-based data, 2017–2020

Fig. 3 An illustration of a unified, digital environment for TB surveillance, along the pathway of care

WHO Tuberculosis Programme: framework for effective TB control. Geneva: World Health Organization; 1994 ( https://apps.who.int/iris/handle/10665/58717 ).
Revised TB recording and reporting forms and registers - version 2006 (WHO/HTM/TB/2006.373). Geneva: World Health Organization; 2006 ( https://www.who.int/tb/err/rr_final_forms_en.pdf ).
Definitions and reporting framework for tuberculosis - 2013 revision (updated December 2014 and January 2020). Geneva: World Health Organization; 2013 ( https://apps.who.int/iris/handle/10665/79199 ).
WHO toolkit for routine health information systems data [website]. Geneva: World Health Organization; 2021. ( https://www.who.int/data/data-collection-tools/health-service-data/toolkit-for-routine-health-information-system-data/modules ).
Electronic recording and reporting for tuberculosis care and control. Geneva: World Health Organization; 2012 ( https://apps.who.int/iris/handle/10665/44840 ).
Understanding and using tuberculosis data (WHO/HTM/TB/2014.09). Geneva: World Health Organization Global Task Force on TB Impact Measurement; 2014 ( https://apps.who.int/iris/handle/10665/129942 ).
Standards and benchmarks for tuberculosis surveillance and vital registration systems: checklist and user guide (WHO/HTM/TB/2014.02). Geneva: World Health Organization; 2014 ( https://apps.who.int/iris/handle/10665/112673 ).
Metadata package downloads [website]. Geneva: World Health Organization; 2021 ( https://dhis2.org/metadata-package-downloads/ ).

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
Open access
Published: 09 August 2024

A study on factors influencing delayed sputum conversion in newly diagnosed pulmonary tuberculosis based on bacteriology and genomics

Mengdi Pang 1 , 2 na1 ,
Xiaowei Dai 2 na1 ,
Nenhan Wang 2 ,
Junli Yi 2 ,
Shanhua Sun 2 ,
Honghao Miao 1 , 2 ,
Jie Zhang 2 ,
Hongtai Zhang 2 ,
Beichuan Ding 2 ,
Xinyu Yang 2 &
Chuanyou Li 1 , 2

Scientific Reports volume 14 , Article number: 18550 ( 2024 ) Cite this article

67 Accesses

Metrics details

Epidemiology
Infectious diseases
Risk factors

Conversion of sputum from positive to negative is one of the indicators to evaluate the efficacy of anti-tuberculosis treatment (ATT). We investigate the factors associated with delayed sputum conversion after 2 or 5 months of ATT from the perspectives of bacteriology and genomics. A retrospective study of sputum conversion in sputum positive 1782 pulmonary tuberculosis (PTB) was conducted from 2021 to 2022 in Beijing, China. We also designed a case-matched study including 24 pairs of delayed-sputum-conversion patients (DSCPs) and timely-sputum-conversion patients (TSCPs), and collect clinical isolates from DSCPs before and after ATT and initial isolates of TSCPs who successfully achieved sputum conversion to negative after 2 months of ATT. A total of 75 strains were conducted drug sensitivity testing (DST) of 13 anti-TB drugs and whole-genome sequencing (WGS) to analyze the risk factors of delayed conversion and the dynamics changes of drug resistance and genomics of Mycobacterium tuberculosis (MTB) during ATT. We found TSCPs have better treatment outcomes and whose initial isolates show lower levels of drug resistance. Clinical isolates of DSCPs showed dynamically changing of resistance phenotypes and intra-host heterogeneity. Single nucleotide polymorphism (SNP) profiles showed large differences between groups. The study provided insight into the bacteriological and genomic variation of delayed sputum conversion. It would be helpful for early indication of sputum conversion and guidance on ATT.

Targeted next-generation sequencing of sputum for diagnosis of drug-resistant TB: results of a national survey in Democratic Republic of the Congo

Sputum culture reversion in longer treatments with bedaquiline, delamanid, and repurposed drugs for drug-resistant tuberculosis

Prevalence and factors associated with multidrug-resistant tuberculosis in South India

Introduction.

Tuberculosis (TB) is the second leading cause of mortality by a single infectious agent, with 1.3 million deaths globally in 2022, almost twice as many deaths as HIV/AIDS 1 . Complex types and heteroresistance of drug-resistant TB increased difficulty in diagnosis and treatment, further complicating the progress towards ending TB, and personalized diagnosis and treatment of TB has become the key to controlling the disease 2 , 3 .

Sputum positive PTB have high sputum transmissibility 3 . Sputum conversion of PTB after 2 months of ATT is a reliable measure of the bactericidal activity of drugs, and has been identified as an important predictor of cure rate 4 . Delayed sputum conversion patients (DSCPs) were characterized by the persistence of sputum-positive PTB status upon completion of the intensive treatment phase, contributing to higher treatment cost and additional burden to healthcare services 5 , 6 , 7 , 8 . TB as a “social disease”, the solution to this dilemma depends on social, economic and environmental interventions, which also influence the occurrence of sputum conversion and sputum conversion rate (SCR) 9 , 10 . Besides, previous studies have proposed the main risk factors including baseline bacterial load, neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, but these conclusions may not be consistent due to differences in sample sizes and geographic regions 10 , 11 , 12 , 13 , 14 .

However, it remains uncertain whether the drug-resistance and genomic diversity of initial isolates impact sputum conversion. For DSCPs, the dynamics changes of molecular and phenotypic drug-resistance is also a matter of concern. Additionally, the genome of pathogenic bacteria's role in disease progression and treatment is increasingly distinct 3 , 15 , 16 , 17 , 18 , while the relationship between delayed sputum conversion and increased bacterial genomic heterogeneity intra-host requires further investigation. This study provided new perspective on the factors influencing the delayed sputum conversion of PTB and observed the dynamics of drug resistance and MTB genome changes of DSCPs during ATT.

Study design and ethics statement

A retrospective cohort study was carried out on data of 1782 PTB managed in Beijing, China from January 2021 to December 2022 to analyze the sputum conversions and epidemiological influences.

We selected PTB who were older than 18 years of age without any other immune diseases, and had preserved serial clinical isolates to constitute the delayed sputum conversion group (Case group). Due to the stringent conditions for strain preservation, only 24 DSCPs were ultimately included in the study. We conducted a case-matched study containing a Control group (24 TSCPs and their 24 clinical isolates) matched to a Case group (24 DSCPs and a total of 51 clinical isolates before and after ATT) based on age, gender, and comorbidities of cohort entry to explore the factors for delayed sputum conversion based on the genotype and phonotype drug-resistance of initial clinical isolates from PTB as well as the genetic diversity between TSCPs and DSCPs (Figs. 1 , S1).

Flowchart of Study Population. Abbreviations: PTB: pulmonary tuberculosis; ATT, anti-tuberculosis treatment; NTM, non-tuberculous mycobacteria; MTB, Mycobacterium tuberculosis.

The 24 pre-treatment isolates of 24 DSCPs in Case group constitute Case_Baseline group (Case_B) and 27 post-treatment isolates constitute Case_Treated group (Case_T) including 18 strains isolated at the 2nd month of ATT and 9 strains isolated after 5 months of ATT. The Case_6 and Case_23 patients had two and three clinical isolates from different periods after ATT, respectively. This comparison was used to explore and elucidate the dynamics of DSCPs' drug resistance profiles, genomes, and dominant flora during ATT.

This study was approved by Beijing Center for Disease Prevention and Control (No.2023.16).

Bacteria subculture, species identification and DST

All clinical isolates were stored in 7H9 medium supplemented with 25% glycerin at − 80 °C refrigerator. Resuscitated clinical isolates were inoculated in LJ solid medium for subsequent DNA extraction and DST. DNA extraction of isolates was followed by strain identification using Mycobacterium nucleic acid detection kit (PCR-fluorescent probe method, CapitalBio technology, China). Microplate DST was used to get the MIC (Minimum Inhibitory Concentration) of MTB in this study, customized microtiter plates containing 13 anti-TB drugs (RIF, INH, PZA, EMB, LFX, MFX, BDQ, LZD, CFZ, DLM, DCS, KAN, CPM) sensitization tests (BASO, Zhuhai, China) was shown in the Fig. S2, experimental operation was carried out in full accordance with the instructions.

WGS and analysis

Extraction and purification of genomic DNA were carried out following Bacterial DNA Extraction Kit (Gene-Optimal, 60,300 K-50 T) protocols. All WGS procedures were performed by Shanghai Gene-Optimal Science & Technology Co. Ltd. (Shanghai, China). Libraries were constructed on the Illumina platform using an FS DNA Lib Prep Kit V6 (RK20259), and we used an Illumina NovaSeq 6000 sequencer, PE 150 software for base-calling, Fastp (0.20.0) for quality control and removal of low-quality data in Raw Data, Cutadapt (v1.15) for trim adapter sequences at the tail of sequencing reads. Clean data was aligned to reference genome (H37Rv, NC000962.3) using BWA (v0.7.17) to evaluate the sequencing depth and coverage. kraken2 for species annotation and abundance detection, compared with the species database of NCBI ( https://www.ncbi.nlm.nih.gov/) 19 , 20 . Variant sites were identified through alignment with the reference genome H37Rv using Freebayes 1.3.2 and SnpEff 4.3t. Snippy, 4.4.3 for mutation matrix; snp-dists 0.7.0 for matrix of SNP distances, and clustered strains were identified (≤ 12 SNPs) 21 , 22 . Drug-Phenotypes were predicted based on mutation and resistance relationships in the Resistance Locus Database ( https://github.com/jodyphelan/tbdb ). The phylogenetic tree was constructed with SAM-TB 23 , visualized and modified using iTOL ( https://itol.embl.de/ ).

Statistical analysis

The basic information of patients was downloaded from the Beijing Municipal Tuberculosis Report system. Data were analyzed using SPSS 20.0 software. For continuous variables that were normally distributed, the mean ± standard deviation (SD) was used. Counting data was described in terms of rate or composition ratio (%). χ2 test was used to analyze the single factor correlation between groups. p < 0.05 was considered statistically significant.

Statistics on sputum conversion at the end of ATT of 1782 PTB

1782 cases initially diagnosed with positive sputum and available for subsequent pathogen detection reports were recruited from the registered TB in Beijing. Sputum conversion at the end of a two-month intensive period of antituberculosis treatment is an important indicator for efficacy evaluation. PTB are required to undergo sputum test at the end of the 2nd, 5th and 6th month of ATT, but not all patients comply with this requirement. Based on the sputum reports, we can categorize the patients into the following groups. we can categorize patients into several groups: timely or delayed sputum conversion, reversion to positive after initial conversion, and persistent non-conversion. 1706 patients (95.7%) successfully achieved sputum conversion after complete ATT. 932 patients underwent sputum test at the end of the 2nd month of ATT, 89.6% of them achieved sputum conversion, but 9 patients subsequently relapsed with positive sputum. The cumulative population of PTB who achieved sputum conversion to negative at the end of the 5 and 6 months of ATT and maintained are 1545(86.7%), 1706(95.7%), respectively. Additionally, 76 (4.3%) patients fail to sputum conversion to negative at the end of ATT, including 10 patients who achieved sputum conversion during treatment but eventually relapsed and 65 patients (3.6%) who never reported negative sputum results (Fig. 2 ).

Sputum test results at different time points during the ATT of 1782 PTB. Patients with positive sputum tests for the last time marked with red frames. Abbreviation: ATT: anti-tuberculosis treatment; M, month; CTN: conversion to negative.

Basic description of the study population

A total of 932 patients underwent sputum testing at the end of the 2nd month of anti-tuberculosis treatment. As shown in Table 1 , the population age structure, gender and household registration address were no statistically significant difference between sputum conversion patients at the end of 2nd month of ATT and patients remain sputum test positive, but those patients who achieve sputum conversion at the 2nd month of ATT have better prognosis and shorter treatment time notably.

As for the case-matched design cohort, 24 patients were recruited in our Case group, only 4 pairs of study subjects were female, the median age of the whole group was 45 years (range: 24–80 years). Among the 24 pairs cases enrolled, diabetes mellitus (n = 10, 41.7%) was the most frequent comorbidity in patients with PTB. In addition, we examined the type of household registration as an epidemiological risk factor that could potentially impact delayed conversion. However, we didn’t find significant difference in our small sample. The number of cured patients was notably higher in Control group compared to the Case group ( P < 0.05, Table 2 ). The phylogenetic tree of the enrolled isolates is in Fig. S3, which includes strain lineage and drug resistance information.

Delayed sputum conversion patients present more extensive and complex drug resistance

We conducted 13 anti-TB-drugs DST on all 75 clinical isolates. Compared to the Control group, the Case_B group emerged higher frequency of drug-resistance (Fig. 3 A) and high-level of resistance 24 , as shown in Table S1, specifically, INH (2 in Control, 5 in Case), LFX (0 in Control, 1 in Case), and KAN (1 in Control, 0 in Case). There were significant differences in the frequency of resistance to both first-line and total tested 13-drugs between the two groups ( P = 0.048, 0.045, Table 3 ). The overall resistance to multiple drugs is related to achieving sputum conversion at the end of 2 months of ATT, rather than a single drug. When we observed the overall changes in drug resistance before and after ATT from a longitudinal perspective of DSCPs, we found that the resistance rates to drugs RIF, EMB and DCS also increased significantly. Besides, comparing WGS resistance mutation detection and MIC, the missed detection rate of WGS was relatively low (7/107, 6.5%, Table S1), indicating WGS is profound for application in drug-resistance detection due to its shorter turnaround time, high detection rate, and ability to provide additional strain information.

Drug resistance of Control and Case_Baseline Case_Treated groups. ( A ) Drug susceptibility test results of clinical isolates from the control group and the experimental baseline group; ( B ) Drug susceptibility test results of clinical isolates before and after 2 months of ATT (n = 18); ( C ) Drug susceptibility test results of clinical isolates before and after ≥ 5 months of ATT(n = 9). Anti-tuberculosis drugs with pink backgrounds are first-line drugs. Gray: drug-sensitive; Orange: MIC-only reported resistance; Green: MIC and WGS both reported resistance; Blue: only WGS reported resistance. Strains labeled with red are those reported as NTM by WGS.

Changes of drug resistance among delayed sputum conversion patients after ATT

We further analyzed the overall changes in drug resistance before and after ATT from a longitudinal perspective of DSCPs, the frequencies of strains acquired phenotypic drug resistance within first-line drugs and total drugs were significantly increased ( P < 0.001, Table 3 , Fig. 3 B, C ). Notably, there was a significant increase in the frequency of resistance to RIF and DCS ( P RIF = 0.042; P DCS = 0.024). Additionally, the incidence of high-level INH resistance and KAN resistance also increased (INH: 5 in Case_B, 11 in Case_T; KAN: 0 in Case_B, 1 in Case_T). The number of multidrug-resistant bacteria in the Case group increased after treatment.

The statistics of drug-resistance changes in DSCPs before and after ATT are shown in Table 4 . 44.4% of patients acquired drug-resistance within two months of treatment, larger compared to after five months of treatment, revealing the initial two months of ATT play a crucial role in ensuring proper drug administration to prevent the emergence of new drug-resistance. Among all patients, 55.6% of isolates showed no change in drug-resistance, while 33.3% developed phenotypic drug-resistance cluster in first-line drugs RIF and INH, with frequencies more than 25%. These results underscore the importance of regular DST for TB throughout the treatment process, facilitating medication adjustments during the course of treatment to prevent the development of worse drug-resistance. Interestingly, re-sensitization occurred in several strains: CPM (Case_7), INH (Case_6), DLM (Case_7, 10). The mechanisms of acquired resistance and re-sensitization require further study.

Genomic changes in series clinical isolates from delayed sputum conversion patients

We further analyzed the differences in SNPs of serial isolates from delayed-sputum-conversion PTB to confirm whether intra-host evolution or multiple/mixed infections occurred during treatment. The SNP differential matrix plot (Fig. 4 A) revealed that 16/24 patients (71%) remain in a cluster after ATT (SNP < 12), while case 11 exhibited no change in bacterial species but occurred a high SNPs count of 557, indicating possible multiple infections. Surprisingly, 7 patients (29%) dominant organism changed to nontuberculous mycobacteria (NTM) on the second sputum test (Fig. S4, Table S2).

Differential SNPs and Their Frequencies within Groups among Control, Case_Baseline, and Case_Treated Strains. ( A ) The digital matrix chart of the differential single-nucleotide polymorphisms (SNPs) of 24 pairs. NTM marked in red. ( B ) The frequency of the differential SNPs of MTB within the Control, Case_Baseline, and Case_Treated groups; ( C ) Statistics of frequency and gene distribution of differential SNPs in groups. Below is the genomic map of H37Rv for reference.

Excluding 7 NTM strains and nonsense mutation, we further analyzed the differential SNPs characteristics and their frequencies within three cohorts: Control, Case_B and Case_T (n = 20) groups. The SNPs blank regions exhibited distinct distribution patterns across the three groups. Specifically, 11% of the SNPs were uniquely present in either the Control or Case_B (existing in only one group), while the Case_B and Case_T exhibited more similar in SNPs distribution, with 94% showing no differences (Fig. 4 B).

We aimed to identify high-frequency SNPs specific to each group. As shown in Fig. 4 C, 55–68% of the differential SNPs between groups have a low frequency within-group (0/24, or 1/24). The differential SNPs with high frequency in the Control and Case_B are relatively high, indicating that there may be SNPs-set distinguish two groups; conversely, the genetic changes of Case_T are more complex and diverse. Obtaining a specific and efficient SNPs-set that can distinguish different groups require further investigation with larger sample size and comprehensive research.

The conversion of sputum in PTB during the intensive treatment period is an effective indicator for evaluating treatment outcomes, affected by various factors. This study shows that PTB who achieved sputum conversion at the end of 2nd month of ATT have better treatment outcome, which is identical to the previous reports 5 , 6 , 7 , 25 . Differing from existing research perspectives about factors affecting sputum conversion 12 , 13 , 25 , 26 , we provide an innovative and comprehensive information on bacteriology and genomics of clinical isolates from DSCPs.

Phenotypic DST of 13 anti-tuberculosis drugs demonstrates that DSCPs more extensive and complex drug resistance undergo dynamic changes during the ATT, which may increase the difficulty of treatment. Compared to general TB patients, people who developed RR/MDR-TB have poorer anti-tuberculosis treatment outcomes, higher treatment costs, and longer duration of the infectious period 1 . During our exploration of drug resistance changes in the treatment process, the difference between phenotypic drug resistance and molecular drug resistance may also be a factor affecting the judgment. For example, Case6_T was reported INH-resistant by MIC without INH-related drug-resistant mutation that stresses the importance of paying attention to specific MIC values such as “low concentration resistance”, “high concentration resistance”, “critical concentration resistance” 24 , et. It is necessary to expand regional studies on genotype and phenotype drug-resistant consistency of MTB, and update the catalogs of drug-resistant mutation based on WGS 2 , 27 , 28 .

There are two cases were DLM re-sensitization in our cohort. DLM is included in Group C, which is recommended for use in longer multidrug-resistant (MDR)-TB regimens 29 , more attention has been paid to the exploration of DLM resistance mutation sites and mechanism 30 , 31 . Besides, changes in the resistance phenotype of DSCPs may be caused by mixed/multiple infections, where the dominant strain in the patient changes along with the course of treatment, resulting in drug-resistant changes. Complex infections possibly lead to multidrug resistance 32 . Strict implementation of sputum bacteriological and drug-resistant monitoring during ATT are crucial for effectively valuing treatment progress. It aids in enhancing our understanding of the local prevalence, evolution, and transmission of pulmonary tuberculosis.

In addition, a certain percentage of PTB whose dominant strain turned to NTM in our study, drawing our attention to mix infection and personalized treatment. While minor NTM known can cause human disease, the incidence of NTM infections appears risen significantly in recent decades due to factors like population aging, immunosuppression, and the use of broad-spectrum antibiotics 33 . Whether our findings suggest that patients on ATT are more susceptible to other pathogens remains uncertain.

The whole-genome analysis of isolates reveals variations in SNPs site distribution regions and frequencies between Control and Case groups, showing differences in genetic backgrounds of the two groups, suggesting the possible presence of group-specific SNPs-set. The effect of pathogenic microbial (such as MTB) genome SNPs is profound in microbial genetics and infectious diseases 34 . The association of SNPs with drug-resistance implying that SNPs can affect an individual's susceptibility, treatment response and disease prognosis 35 . The SNPs-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. For technical and sample size limitations, we did not explore the impact of small insertions and deletions or large chromosomal changes (such as repeat regions in the genome) and SNPs-set analysis following this study 36 .

MTB is characterized by low mutation rate, and NGS-related studies have also shown that the MTB genome is highly stable during transmission between individuals, with an evolutionary mutation rate of approximately 0.5 SNPs/genome/year 37 . However, MTB evolution within patients exhibited considerable genetic diversity 38 , more SNPs observed in series isolates MTB populations from individual patients, these SNPs occurred concurrently with drug-resistance, leading to mutations referred as "hitchhiker SNPs" 37 . With the treatment duration increases, the variation level decreases, suggesting that the selective pressure from drug exposure has led to a purifying effect 21 , 37 , 38 . Intra-patient microevolution of MDR-MTBC strains under longitudinal treatment is more complex than previously anticipated 39 . Rapid expansion and collapse of different clones led to a difference of 11 SNPs between two strains separated by only three months 37 . The number of SNPs between initial and treated isolates in this study was concentrated in the range of 0–6, with only Case_11 experiencing an explosive change with a high SNPs count of 557, which may involve the rapid expansion of different clones and possibly the occurrence of multiple infections.

This study illustrates that PTB achieved sputum conversion at the end of 2 months of ATT had better treatment outcome through the cohort of 1782 PTB. We also provide valuable insights into the understanding risk factors and dynamics in therapy of delayed sputum conversion PTB from the perspective of drug resistance, genomic diversity, intra-host evolution. Delayed sputum conversion patients present more extensive and complex drug resistance and show dynamic changes resistance (re-sensitization, acquired phenotypic drug resistance) during the treatment process, which may be caused by intra-host heterogeneity and faster microevolution.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Global tuberculosis report 2023. Geneva: World Health Organization; 2023. Licence: CC BY-NC-SA 3.0 IGO.

Danchuk S, et al. (2024) Mycobacterium tuberculosisChallenging the gold standard: the limitations of molecular assays for detection of heteroresistance. Thorax.

Gill, C. et al. New developments in tuberculosis diagnosis and treatment. Breathe (Sheff.) 18 (1), 210149 (2022).

Article PubMed Google Scholar

Mitchison, D. et al. Assessment of new sterilizing drugs for treating pulmonary tuberculosis by culture at 2 months. Am. Rev. Respirat. Disease 147 (4), 1062–1063 (1993).

Article CAS Google Scholar

Mlotshwa, M. et al. Risk factors for tuberculosis smear non-conversion in Eden district, Western Cape, South Africa, 2007–2013: a retrospective cohort study. BMC Infect. Dis. 16 , 365 (2016).

Article PubMed PubMed Central Google Scholar

Wang, J. et al. Factors influencing time to smear conversion in patients with smear-positive pulmonary tuberculosis. Respirology (Carlton, Vic) 14 (7), 1012–1019 (2009).

Gopi, P. et al. Association of conversion & cure with initial smear grading among new smear positive pulmonary tuberculosis patients treated with Category I regimen. Indian J. Med. Res. 123 (6), 807–814 (2006).

CAS PubMed Google Scholar

Ramarokoto, H. et al. Bacteriological follow-up of tuberculosis treatment: A comparative study of smear microscopy and culture results at the second month of treatment. Int. J. Tuberculos. Lung Disease 6 (10), 909–912 (2002).

CAS Google Scholar

Lönnroth, K. et al. Drivers of tuberculosis epidemics: The role of risk factors and social determinants. Soc. Sci. Med. 68 (12), 2240–2246 (2009).

Költringer, F. et al. The social determinants of national tuberculosis incidence rates in 116 countries: A longitudinal ecological study between 2005–2015. BMC Public Health 23 (1), 337 (2023).

Saffari, M. et al. Smear grading and the Mantoux skin test can be used to predict sputum smear conversion in patients suffering from tuberculosis. GMS Hygiene Infect. Control 12 , 12 (2017).

Google Scholar

Wardani, D. et al. Risk factors for delayed sputum conversion: A qualitative case study from the person-in-charge of TB program’s perspectives. J Public Health Research 12 (4), 22799036231208356 (2023).

Article Google Scholar

Nguyen, M. et al. Factors associated with sputum culture-negative vs culture-positive diagnosis of pulmonary tuberculosis. JAMA Network Open 2 (2), e187617 (2019).

D’Souza, K. et al. Factors associated with month 2 smear non-conversion among Category 1 tuberculosis patients in Karachi, Pakistan. J. Infect. Public Health 11 (2), 283–285 (2018).

Article MathSciNet PubMed Google Scholar

Barrick, J. et al. Genome-wide mutational diversity in an evolving population of Escherichia coli. Cold Spring Harb. Symposia Quant. Biol. 74 , 119–129 (2009).

Article CAS PubMed Google Scholar

Zagordi, O. et al. Error correction of next-generation sequencing data and reliable estimation of HIV quasispecies. Nucl. Acids Res. 38 (21), 7400–7409 (2010).

Article CAS PubMed PubMed Central Google Scholar

Folkvardsen, D. et al. Rifampin heteroresistance in Mycobacterium tuberculosis cultures as detected by phenotypic and genotypic drug susceptibility test methods. J. Clin. Microbiol. 51 (12), 4220–4222 (2013).

Hofmann-Thiel, S. et al. Mechanisms of heteroresistance to isoniazid and rifampin of Mycobacterium tuberculosis in Tashkent, Uzbekistan. Eur. Respirat. J. 33 (2), 368–374 (2009).

Walker, T. et al. Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. Lancet Infect. Diseases 15 (10), 1193–1202 (2015).

Phelan, J. et al. Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs. Genome Med. 11 (1), 41 (2019).

Walker, T. et al. Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: A retrospective observational study. Lancet Infect. Diseases 13 (2), 137–146 (2013).

Article MathSciNet CAS Google Scholar

Francesc, C. et al. A robust SNP barcode for typing Mycobacterium tuberculosis complex strains. Nat. Commun. 5 , 1 (2014).

Tingting, Y. et al. SAM-TB: A whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission. Brief Bioinform. 23 (2), 1 (2022).

et al. World Health Organization. (2022). Optimized broth microdilution plate methodology for drug susceptibility testing of Mycobacterium tuberculosis complex. World Health Organization. https://iris.who.int/handle/10665/353066 .

Khor, L. et al. Prevalence and associated factors of delayed sputum smear conversion in patients treated for smear positive pulmonary tuberculosis: A retrospective follow up study in Sabah. Malaysia. PloS one 18 (3), e0282733 (2023).

Gstöttenmayer, F. et al. Correction Notice to: Development and characterization of microsatellite markers for the tsetse species Glossina brevipalpis and preliminary population genetics analyses. Parasite 30 , 34. https://doi.org/10.1051/parasite/2023038 (2023).

de Neeling, A. et al. Mycobacterium tuberculosisCharacteristic SNPs defining the major multidrug-resistant clusters identified by EuSeqMyTB to support routine surveillance, EU/EEA, 2017 to 2019. Eur. Commun. Disease Bull. 29 (12), 1 (2024).

García-Marín, A. et al. Role of the first WHO mutation catalogue in the diagnosis of antibiotic resistance in Mycobacterium tuberculosis in the Valencia Region, Spain: A retrospective genomic analysis. Lancet Microbe. 5 (1), e43–e51 (2024).

Yuanyuan, L. et al. Spontaneous Mutational Patterns and Novel Mutations for Delamanid Resistance in Mycobacterium tuberculosis. Antimicrob Agents Chemother 66 (12), 1 (2022).

Skripconoka, V. et al. Delamanid improves outcomes and reduces mortality in multidrug-resistant tuberculosis. Eur. Respirat. J. 41 (6), 1393–1400 (2013).

Gler, M. et al. Delamanid for multidrug-resistant pulmonary tuberculosis. New Engl. J. Med. 366 (23), 2151–2160 (2012).

Nathavitharana, R. R. et al. Polyclonal pulmonary tuberculosis infections and risk for multidrug resistance, Lima, Peru. Emerg Infect Dis. 23 , 1 (2017).

Johansen, M. et al. Non-tuberculous mycobacteria and the rise of Mycobacterium abscessus. Nat. Rev. Microbiol. 18 (7), 392–407 (2020).

Singh, D. et al. Immune-related gene polymorphisms in pulmonary diseases. Toxicology. 383 , 24–39 (2017).

Vargas, R. et al. Mycobacterium tuberculosisIn-host population dynamics of complex during active disease. eLife. 10 , 1 (2021).

Xiao, H. et al. Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture. Cardiovasc. Diabetol. 21 (1), 276 (2022).

Eldholm, V. et al. Evolution of extensively drug-resistant Mycobacterium tuberculosis from a susceptible ancestor in a single patient. Genome Biol. 15 (11), 490 (2014).

Sun, G. et al. Dynamic population changes in Mycobacterium tuberculosis during acquisition and fixation of drug resistance in patients. J. Infect. Diseases. 206 (11), 1724–1733 (2012).

Merker, M. et al. Whole genome sequencing reveals complex evolution patterns of multidrug-resistant Mycobacterium tuberculosis Beijing strains in patients. PloS One 8 (12), e82551 (2013).

Article ADS PubMed PubMed Central Google Scholar

Download references

This study was supported by the Capital’s Funds for Health Improvement and Research [Grant No. 2022-1G-3012 to CL]; the Scientific Research Training program of Beijing Center for Disease Control and Prevention [Grant No. 2023-KYJH-05 to XY].

Author information

These authors contributed equally: Mengdi Pang and Xiaowei Dai.

Authors and Affiliations

School of Public Health, Capital Medical University, Beijing, China

Mengdi Pang, Honghao Miao & Chuanyou Li

Beijing Center for Disease Prevention and Control, Beijing, 100035, China

Mengdi Pang, Xiaowei Dai, Nenhan Wang, Junli Yi, Shanhua Sun, Honghao Miao, Jie Zhang, Hongtai Zhang, Jie Li, Beichuan Ding, Xinyu Yang & Chuanyou Li

You can also search for this author in PubMed Google Scholar

Contributions

C.L., X.Y., M.P., X.D., B.D.: made substantial contributions to the conception or design of the work; C.L., X.Y., B.D.: project administration; M.P., X.Y.: wrote the manuscript; M.P., X.Y., J.Y., X.D., C.L., N.W., H.M., J.Z.: experiments and data analysis; S.S., X.Y., M.P.: collected clinical data; C.L., X.Y., X.D., J.L., H.Z., B.D.: acquired funding for the study. All authors contributed to the article and approved the submitted version. All authors approved the manuscript and author contributions statement.

Corresponding authors

Correspondence to Xinyu Yang or Chuanyou Li .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary information 1., supplementary information 2., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Pang, M., Dai, X., Wang, N. et al. A study on factors influencing delayed sputum conversion in newly diagnosed pulmonary tuberculosis based on bacteriology and genomics. Sci Rep 14 , 18550 (2024). https://doi.org/10.1038/s41598-024-69636-5

Download citation

Received : 29 May 2024

Accepted : 07 August 2024

Published : 09 August 2024

DOI : https://doi.org/10.1038/s41598-024-69636-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Mycobacterium tuberculosis
Delayed sputum conversion
Anti-tuberculosis treatment
Whole genome sequencing
Drug-resistance

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

Explore articles by subject
Guide to authors
Editorial policies

Systematic Review
Open access
Published: 07 August 2024

Prevalence, incidence, and case fatality of tuberculous meningitis in adults living with HIV: a systematic review and meta-analysis

Xue Chen 1 , 2 na1 ,
Jiaqi Wei 1 na1 ,
Mei Zhang 1 na1 ,
Meixin Ren 1 ,
Miaotian Cai 3 ,
Yulin Zhang 3 , 4 &
Tong Zhang 1

BMC Public Health volume 24 , Article number: 2145 ( 2024 ) Cite this article

201 Accesses

Metrics details

Tuberculous meningitis (TBM) emerges as a grave complication of tuberculosis in people living with HIV (PLWH). The diagnosis and treatment of TBM pose significant challenges, leading to elevated mortality rates. To comprehensively grasp the epidemiological landscape of TBM in PLWH, a systematic review and meta-analysis were meticulously undertaken.

We performed a comprehensive search in PubMed, Embase, and Web of Science from database inception to September 19th, 2023, with no limitations on the publication type. The search terms were HIV/AIDS terms (AIDS OR HIV OR PLWH) and TBM-related terms (tuberculous meningitis OR TBM). Studies included in this meta-analysis evaluated the incidence of TBM among PLWH, or we were able to calculate the incidence of TBM among PLWH from the research.

The analysis revealed that the prevalence of TBM among PLWH was 13.6% (95% CI: 6.6–25.9%), with an incidence rate of 1.5 cases per 1000 persons per year. The case fatality rate was found to be 38.1% (95% CI: 24.3–54.1%). No significant publication bias was observed. Meta-regression analysis identified the proportion of females and finance situation as factors influencing the outcomes.

Conclusions

Our study highlights TBM as a prevalent opportunistic infection that targets the central nervous system in PLWH. The elevated case fatality rate is especially prominent among PLWH in impoverished regions, underscores the pressing necessity for enhanced management strategies for PLWH suffering from TBM.

Trial registration

PROSPERO; No: CRD42022338586.

Peer Review reports

Tuberculous meningitis (TBM) is a common neurological disorder in young children and people living with HIV (PLWH), and it accounts for approximately 1% of all cases of tuberculous (TB) [ 1 , 2 ]. Moreover, TBM is a fatal form of TB that kills or severely disables up to 50% of infected individuals [ 3 , 4 , 5 ]. In many regions around the world, especially in countries with TB epidemics, TB is the predominant cause of bacterial meningitis due to the protective effects of vaccination against other forms of meningitis. Moreover, the challenge of diagnosis and treatment delay is compounded by the lack of specific clinical features and the insensitivity of laboratory tests, ultimately contributing to its elevated mortality rate [ 6 ]. Critical risk factors for TBM, including age, anti-TB regimens, disease duration, and HIV infection, may contribute to the incidence and outcomes of TBM [ 7 , 8 ].

PLWHs have an increased risk of developing all forms of TB [ 9 ], coinfection with TB influences the pathogenesis of HIV and increases HIV‑1 replication in PLWH [ 10 ]. In adults, HIV-1 coinfection is the most significant risk factor for TBM. Additionally, TBM has become a severe HIV-associated CNS opportunistic infection and has increased the relative risk of death from two- to three-fold in PLWH, even with the introduction of antiretroviral therapy (ART) [ 11 ]. In the context of HIV infection, the pathological, clinical, and laboratory findings in patients with TBM are influenced in various ways, and the outcomes of TBM may be poor [ 12 ]. Although previous studies have shown that TBM is linked to a significant risk of neurological complications and death [ 13 , 14 , 15 ], and Purmohamad et al. found a high incidence of TBM-HIV coinfection [ 16 ], there is currently a lack of systematic analysis of the incidence, prevalence, and mortality rates of TBM infection in adult PLWH.

In this study, we performed a systematic review and meta-analysis to understand the global prevalence, incidence and case fatality of PLWH with TBM. Additionally, we aimed to analyse the potential risks of death associated with TBM in PLWH, providing new insights into strategies for diagnosing and treating the disease.

This study is registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration No: CRD42022338586). Furthermore, this study was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [ 17 ]. The PRISMA checklist is provided in Supplement Table 1 .

Search strategy

We performed a comprehensive search in PubMed, Embase, and Web of Science from database inception to September 19th, 2023, with no limitations on the publication type. To avoid bias due to language barriers, we only searched the articles written in English. The search terms were HIV/AIDS terms (AIDS OR HIV OR PLWH) and TBM-related terms (tuberculous meningitis OR TBM). We further screened the reference lists of the selected articles to identify missing studies. A detailed description of the search strategies is provided in Supplement Table 2 .

Selection criteria

Studies included in this meta-analysis evaluated the incidence of TBM among PLWH, or provided data that allow for the calculation of the incidence of TBM among PLWH from the presented research. We excluded the following types of studies: (1) not related to HIV/AIDS; (2) research protocols or feedback reports; (3) case reports; (4) review articles; (5) children-oriented; (6) comparative study; (7) the prevalence or the incidence of TBM among PLWH could not be extracted; (8) participants less than 20. Researchers (XC and JW) removed duplicate studies using EndNote X9 software, selected preliminary search results through title and abstract, and then further determined the remaining articles by assessing full-text. Disagreements between reviewers about eligibility were resolved by discussion with TZ and YZ.

Data extraction

Two researchers (XC and JW) independently extracted and cross-checked relevant data using an Excel spreadsheet. The main information was the prevalence, incidence, and case fatality of TBM among PLWH. Additionally, we extracted other information from these articles, including authorship, year of publication, type of study, study location, sample size, mean age of participants, sex distribution, and current CD4 + T cell count from the total PLWH population and the TBM population.

Statistical analysis

Comprehensive Meta-Analysis (CMA) Version 3.0 (Biostat, Englewood, New Jersey) was adopted for quantitative analysis. Firstly, we calculated the combined event rate (ER) using the prevalence and death of TBM, and the total number of samples included. Next, the number of cases in the cohort articles was divided by the number of months of surveillance and then multiplied by 12 to calculate the number of cases per year [ 18 ]. Person-years were represented by the total number of HIV cases in each country during the study year, obtained from the UNAIDS website ( https://www.unaids.org/en/regionscountries/countries ). The rate was the number of cases per year multiplied by person per year. In addition, we conducted a random effects meta-analysis using the ER to estimate the prevalence and the case fatality of TBM among PLWH and used the rate to estimate the incidence of TBM among PLWH. Additionally, the Egger ranks correlation test was adopted to assess publication bias across studies. The I 2 and Q-tests were used to evaluate the proportion and statistical significance of heterogeneity. The threshold for statistical significance was 2-tailed p < 0.05.

Quality assessment

Two researchers (XC and JW) used the Agency of Healthcare Research and Quality (AHRQ) methodology checklist ( http://www.ncbi.nlm.nih.Gov/books/NBK35156/ ) for cross-sectional studies and independently assessed the individual studies. The checklist contained 11 items: (1) information source, (2) study criteria, (3) study period, (4) sampling, (5) interview method, (6) instrument validation, (7) exclusion criteria, (8) the measurement of confounding effects, (9) the process of dealing with missing values, (10) response rate, and (11) the use of follow-up assessment. According to this standard, studies were divided into three levels: high-quality (over 8 points), moderate-quality (4–7 points), and low-quality (0–3 points).

Meta regression

The primary outcome of our study was the prevalence and incidence of TBM among PLWH, and the secondary outcome was the case fatality of TBM among PLWH. The predefined continuous moderators were age, gender (the proportion of women), the current median/mean CD4 + T cell counts among PLWH and TBM, finance situation (Per capita gross domestic product (GDP) was obtained from the world bank website: https://data.worldbank.org.cn ), and study quality. The categorical moderators were the study period, and the study design. Restricted ML meta-regression was used to evaluate associations. The results with p < 0.05 were considered as significance-level factors.

Search results

After removing all duplicates from the 1824 records, 1821 studies were screened. Of these, 1779 records were excluded based on the title and abstract, and 42 full-text articles were assessed for eligibility. Overall, 17 eligible studies were included in the meta-analysis. A flowchart of the study selection is shown in Fig. 1 , and the details of the excluded articles are shown in Supplementary Table 3 .

The flowchart of study selection

Study characteristics

Among the 17 studies included, 9 were retrospective, and 7 were prospective. The remaining studies were a combination of retrospective and prospective designs. In addition, 12 were cross-sectional studies, and five were cohort studies. Studies included data from Africa, Europe, Asia, and South America, comprising 6561 participants. Thirteen studies reported a mean age of 35 (range, 28–39) years; the mean female proportion was 36% (range, 14–68%). The current CD4 + T cell counts was 13–158 cells/µl in PLWH and 14–142 cells/µl in TBM. Six studies were considered moderate-quality studies, whereas the remaining were high-quality (Supplementary Table 4 ). Additional characteristics of the included studies and their corresponding participants are presented in Table 1 .

Meta-analysis of prevalence, incidence and case fatality of TBM

Twelve studies reported the prevalence of TBM among PLWH. The combined ER of TBM was 13.6% (95% confidence interval [CI]: 6.6–25.9%). Significant heterogeneity was detected (Q: 520.4; I 2 : 97.9%; p < 0.001). Publication bias of the included studies had no statistical significance (intercept: -0.1, 95% CI: -114.4 to 14.3; p = 0.9) (Fig. 2 ).

Five studies reported the incidence of TBM among PLWH. The combined rate of TBM was 1.5 per 1000 per year (95% CI: 0.6–2.5 per 1000 per year). Significant heterogeneity was detected (Q: 43.9; I 2 : 90.9%; p < 0.001). Publication bias of the included studies had no statistical significance (intercept: 5.6, 95% CI: -2.5 to 13.7; p = 0.1) (Fig. 3 ).

Case fatality

Twelve studies reported on the case fatality of patients with TBM. The combined ER was 38.1% (95% CI: 24.3–54.1%), and a significant heterogeneity was detected (Q: 69.1; I 2 : 84.1%; p < 0.001). No significant publication bias was found (intercept: -1.5, 95% CI: -5.8 to 2.8; p = 0.4). The detailed results of the meta-analysis are presented in Fig. 4 .

Meta-regression

We conducted meta-regressions on all factors extracted from the studies to analyse the prevalence and case fatality among patients with TBM. While no significant results were found for prevalence, two factors produced substantial changes in outcomes: female proportion (coefficient: 0.05; p < 0.01) and finance situation (coefficient: -1.16; p = 0.02). The detailed results for the meta-regression are available in Supplementary Table 5 .

This comprehensive systematic review and meta-analysis was conducted to elucidate the prevalence incidence of TBM in PLWH and the corresponding case fatality in this population. We found that the prevalence, incidence and case fatality were approximately 13.6%, 1.5 per 1000 per year, and 38.1%, respectively, indicating that the prevalence and incidence of TBM were relatively low, while TBM-associated case fatality was high in PLWH. Moreover, the results of the meta-regression analysis suggested that the proportion of females and the finance situation may have substantial impacts on the outcomes.

PLWH are approximately 14 times more likely to develop TB, and face more than double the mortality rate during TB treatment compared to the general population [ 19 ]. PLWH are at heightened risk for TBM, particularly at more advanced stages of immunosuppression [ 20 ]. Moreover, TBM in PLWH has a poor prognosis, with no appreciable difference in survival probability based on ART timing [ 21 ]. Navarro-Flores et al. found that the prevalence of HIV was positively associated with the prevalence of TBM, identifying HIV infection as a moderator in the prevalence of TBM among hospitalized patients [ 13 ]. Moreover, a meta-analysis conducted by Stadelman et al. also suggested that the mortality of adult TBM was high and is influenced by HIV status [ 22 ]. Our study demonstrated that TMB-associated case fatality is high in PLWH, consistent with previous research on patients with TB [ 4 ].

Several risk factors influence the outcomes of CNS OIs in PLWH, including region distribution, age, sex, prophylactic history, and CD4 + T cell counts [ 23 ]. Our study analysed the related risk factors, including age, sex (the proportion of women), the current median/mean CD4 + T cell counts, and financial situation among PLWH and TBM. However, we did not find significant results for prevalence.

In addition, we found a marginal correlation effect (coefficient: -1.16; p = 0.02) between case fatality and socioeconomic status, indirectly indicating the region’s impact on case fatality. The changes in outcomes influenced by regional distribution are consistent with previous studies on TB/HIV coinfection, which showed that high morbidity and mortality rates were observed among PLWH and TB in resource-limited countries such as those in sub-Saharan Africa [ 24 ].

In our study, another factor influencing case fatality was the proportion of females, which suggests that as the proportion of females increases, so does the case fatality rate. The worldwide incidence of TB has consistently been higher in men compared with women, although the male-to-female ratio varies per region [ 25 ]. However, HIV infection significantly contributed to the epidemic rates of TB in women, leading to a 5.3-fold increase, which was notably higher compared to men. Since there are only a few studies on sex in patients with TBM, we speculate that our findings could be attributed to the increased rates of TBM in women with the onset of HIV and more susceptibility to HIV.

In certain cohorts, the mortality rate among HIV patients coinfected with TBM exceeds 50% [ 26 ]. Important contributing factors include the level of immunosuppression due to HIV and immune reconstitution inflammatory syndrome (IRIS) resulting from ART [ 27 , 28 ]. In our study, we used CD4 + T cell counts to measure the degree of immunosuppression in PLWH and found that the current CD4 + T cell counts ranged from 13 to 96 cells/µl among PLWH and 12–142 cells/µl among PLWH with TBM, suggesting that these populations are severely immunocompromised. The CD4 + T cell counts may be associated with the case fatality of PLWH and TBM in our study. However, our study did not mention other potential risk factors among PLWH and TBM, such as drug-resistant TB, specific anti-TB regimens, disease duration, and the presence of accompanying pulmonary TB or other systemic TB, which could also be critical in determining the case fatality rate.

This study had several limitations. First, the number of included studies was limited, which restricted the generalizability of the results. Second, PLWH with TBM typically experience severe immunosuppression, characterized by significantly low CD4 + T cell counts. Therefore, it may affect the generalization of our findings to all PLWH. Third, the incomplete and discrepant data in the original articles, coupled with a dearth of detailed information from individual studies, resulted in inadequate subgroup analyses. For example, age and CD4 + T cell counts showed no remarkable difference in the prevalence and case fatality. This lack of significance could be attributed to several factors: (1) in all studies, the mean age was approximately 30 years, which is consistent with the peak age at onset of TB; and (2) since the population in our study was PLWH and TBM, the CD4 + T cell counts in each study were relatively low, with the highest not exceeding 150 cells/µl, leading to low statistical power in this subgroup analysis. In addition, the regional distribution is limited owing to few relevant studies. Thus, our findings of regional differences do not reflect the global distribution and lack validity and generalizability. For example, the outcomes of the regional distribution in the population suggested that Europe has the most significant number of studies, the prevalence of TBM in PLWH is generally high (up to 13%), and the prevalence in Africa and South America is nearly 10%. In contrast, the prevalence in Asia is as high as 55.3% (Supplement Fig. 1 ); the case fatality in Africa was the highest (up to 60%); this disparity may be linked to limited access to treatment, poverty, gender inequality, and societal stigma towards HIV in Africa [ 29 , 30 ]. When compared to other regions, this situation is more widespread in Africa [ 31 , 32 ] (Supplement Fig. 2 ). Fourth, the heterogeneity in this meta-analysis was high (Q: 72.081; I²: 81.97%; p < 0.001), likely due to significant differences in study design, including variations in sample sizes, methodologies, and population characteristics. This heterogeneity may contribute to limited generalizability and potential biases in our study.

Meta-analysis of prevalence of TBM among PLWH

Meta-analysis of incidence of TBM among PLWH

Meta-analysis of case fatality of TBM among PLWH

In conclusion, this systematic review and meta-analysis provided a comprehensive epidemiological landscape of TBM in PLWH exhibiting low prevalence and incidence rates alongside high case fatality rates, particularly those from economically disadvantaged areas. Additionally, meta-regressions were performed to investigate the pertinent risk factors influencing TBM prevalence and case fatality rates among PLWH. Notably, the financial situation and the proportion of females were identified as significant factors influencing these outcomes. This study underscores the critical necessity for immediate public health interventions to enhance patient care for individuals affected by PLWH and TBM.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

Tuberculous meningitis

Tuberculous

People living with HIV

Central nervous system

Opportunistic infections

Antiretroviral therapy

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Comprehensive Meta-Analysis

Agency of Healthcare Research and Quality

Gross domestic product

Progressive multifocal leukoencephalopathy

Immune reconstitution inflammatory syndrome

Jain S, Tobin D, Tucker E, Venketaraman V, Ordonez A, Jayashankar L, Siddiqi O, Hammoud D, Prasadarao N, Sandor M, et al. Tuberculous meningitis: a roadmap for advancing basic and translational research. Nat Immunol. 2018;19(6):521–5.

Article CAS PubMed PubMed Central Google Scholar

Marais S, Thwaites G, Schoeman J, Török M, Misra U, Prasad K, Donald P, Wilkinson R, Marais B. Tuberculous meningitis: a uniform case definition for use in clinical research. Lancet Infect Dis. 2010;10(11):803–12.

Article PubMed Google Scholar

Wilkinson R, Rohlwink U, Misra U, van Crevel R, Mai N, Dooley K, Caws M, Figaji A, Savic R, Solomons R, et al. Tuberculous meningitis. Nat Reviews Neurol. 2017;13(10):581–98.

Article Google Scholar

Graham S, Donald P. Death and disability: the outcomes of tuberculous meningitis. Lancet Infect Dis. 2014;14(10):902–4.

Dian S, Rahmadi R, van Laarhoven A, Ganiem A, van Crevel R. Predicting Mortality of Tuberculous Meningitis. Clin Infect Diseases: Official Publication Infect Dis Soc Am. 2018;67(12):1954–5.

Thwaites G, van Toorn R, Schoeman J. Tuberculous meningitis: more questions, still too few answers. Lancet Neurol. 2013;12(10):999–1010.

Article CAS PubMed Google Scholar

Huynh J, Donovan J, Phu N, Nghia H, Thuong N, Thwaites G. Tuberculous meningitis: progress and remaining questions. Lancet Neurol. 2022;21(5):450–64.

Tenforde M, Mokomane M, Leeme T, Tlhako N, Tsholo K, Chebani T, Stephenson A, Hutton J, Mitchell H, Patel R, et al. Mortality in adult patients with culture-positive and culture-negative meningitis in the Botswana national meningitis survey: a prevalent cohort study. Lancet Infect Dis. 2019;19(7):740–9.

Article PubMed PubMed Central Google Scholar

Berenguer J, Moreno S, Laguna F, Vicente T, Adrados M, Ortega A, González-LaHoz J, Bouza E. Tuberculous meningitis in patients infected with the human immunodeficiency virus. N Engl J Med. 1992;326(10):668–72.

Bell L, Noursadeghi M. Pathogenesis of HIV-1 and Mycobacterium tuberculosis co-infection. Nat Rev Microbiol. 2018;16(2):80–90.

Heemskerk A, Bang N, Mai N, Chau T, Phu N, Loc P, Chau N, Hien T, Dung N, Lan N, et al. Intensified antituberculosis therapy in adults with tuberculous meningitis. N Engl J Med. 2016;374(2):124–34.

Garg R, Sinha M. Tuberculous meningitis in patients infected with human immunodeficiency virus. J Neurol. 2011;258(1):3–13.

Navarro-Flores A, Fernandez-Chinguel JE, Pacheco-Barrios N, Soriano-Moreno DR, Pacheco-Barrios K. Global morbidity and mortality of central nervous system tuberculosis: a systematic review and meta-analysis. J Neurol. 2022;269(7):3482–94.

Nataprawira HM, Gafar F, Risan NA, Wulandari DA, Sudarwati S, Marais BJ, Stevens J, Alffenaar J-WC, Ruslami R. Treatment outcomes of Childhood Tuberculous meningitis in a real-world retrospective cohort, Bandung, Indonesia. Emerg Infect Dis. 2022;28(3):660–71.

Merkler AE, Reynolds AS, Gialdini G, Morris NA, Murthy SB, Thakur K, Kamel H. Neurological complications after tuberculous meningitis in a multi-state cohort in the United States. J Neurol Sci. 2017;375:460–3.

Purmohamad A, Azimi T, Nasiri MJ, Goudarzi M, Zangiabadian M, Sedighian H, Fooladi AAI. HIV-Tuberculous meningitis Co-infection: a systematic review and Meta-analysis. Curr Pharm Biotechnol. 2021;22(7):960–8.

Moher D, Liberati A, Tetzlaff J, Altman D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

Shrestha DB, Budhathoki P, Gurung B, Subedi S, Aryal S, Basukala A, Aryal B, Adhikari A, Poudel A, Yadav GK et al. Epidemiology of dengue in SAARC territory: a systematic review and meta-analysis. Parasite Vector 2022, 15(1).

WHO. Global tuberculosis report 2023. 2023.

Vinnard C, Macgregor RR. Tuberculous meningitis in HIV-infected individuals. Curr HIV/AIDS Rep. 2009;6(3):139–45.

Lawn S, Wood R. Poor prognosis of HIV-associated tuberculous meningitis regardless of the timing of antiretroviral therapy. Clin Infect Diseases: Official Publication Infect Dis Soc Am. 2011;52(11):1384–7.

Stadelman AM, Ellis J, Samuels THA, Mutengesa E, Dobbin J, Ssebambulidde K, Rutakingirwa MK, Tugume L, Boulware DR, Grint D, et al. Treatment outcomes in adult tuberculous meningitis: a systematic review and Meta-analysis. Open Forum Infect Dis. 2020;7(8):ofaa257.

Agnihotri S. Central Nervous System opportunistic infections. Semin Neurol. 2019;39(3):383–90.

Osman M, Welte A, Dunbar R, Brown R, Hoddinott G, Hesseling A, Marx F. Morbidity and mortality up to 5 years post tuberculosis treatment in South Africa: a pilot study. Int J Infect Diseases: IJID : Official Publication Int Soc Infect Dis. 2019;85:57–63.

Google Scholar

WHO. Global tuberculosis report. 2021.

Thao LTP, Heemskerk AD, Geskus RB, Mai NTH, Ha DTM, Chau TTH, Phu NH, Chau NVV, Caws M, Lan NH, et al. Prognostic models for 9-Month Mortality in Tuberculous Meningitis. Clin Infect Diseases: Official Publication Infect Dis Soc Am. 2018;66(4):523–32.

Article CAS Google Scholar

Marais S, Lai RPJ, Wilkinson KA, Meintjes G, O’Garra A, Wilkinson RJ. Inflammasome Activation Underlying Central Nervous System Deterioration in HIV-Associated Tuberculosis. J Infect Dis. 2017;215(5):677–86.

CAS PubMed Google Scholar

Thwaites GE, N DB, N HD, H TQ, D TTO, N TCT, N QH, N TT, N NH, N TNL, et al. The influence of HIV infection on clinical presentation, response to treatment, and outcome in adults with tuberculous meningitis. J Infect Dis. 2005;192(12):2134–41.

Harrison A, Colvin CJ, Kuo C, Swartz A, Lurie M. Sustained high HIV incidence in Young Women in Southern Africa: social, behavioral, and structural factors and emerging intervention approaches. Curr HIV/AIDS Rep. 2015;12(2):207–15.

Delva W, Abdool Karim Q. The HIV epidemic in Southern Africa - is an AIDS-free generation possible? Curr HIV/AIDS Rep 2014, 11(2).

Shah G, Ewetola R, Etheredge G, Maluantesa L, Waterfield K, Engetele E, Kilundu A. Risk factors for TB/HIV coinfection and consequences for patient outcomes: evidence from 241 clinics in the Democratic Republic of Congo. Int J Environ Res Public Health 2021, 18(10).

Dong K, Thabethe Z, Hurtado R, Sibaya T, Dlwati H, Walker B, Wilson D. Challenges to the success of HIV and Tuberculosis care and treatment in the public health sector in South Africa. J Infect Dis 2007:S491–496.

Download references

Acknowledgements

Not applicable.

This research was funded by the Beijing Natural Science Foundation (Z220018, 7222095); the Capital’s Funds for Health Improvement and Research (2022-1-1151), the National Key R&D Program of China (2023YFE0116000, 2023YFC2308300), the National Natural Science Foundation of China (81571178, 81873761, 82072271); the Climbing the Peak (Deng feng) Talent Training Program of the Beijing Hospitals Authority (DFL20191701); the Beijing Health Technologies Promotion Program (BHTPP2020); and the Beijing Key Laboratory for HIV/AIDS Research (BZ0089); Beijing research center for respiratory infectious diseases project (BJRID2024-001).

Author information

Xue Chen, Jiaqi Wei, Mei Zhang these authors contributed equally to this work.

Authors and Affiliations

Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Beijing Key Laboratory for HIV/AIDS Research, Capital Medical University, Beijing, 100069, China

Xue Chen, Jiaqi Wei, Mei Zhang, Bin Su, Meixin Ren & Tong Zhang

Beijing Youan Hospital, Beijing Institute of Hepatology, Capital Medical University, Beijing, 100069, China

Department of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, China

Miaotian Cai & Yulin Zhang

Beijing Research Center for Respiratory Infectious Diseases, Beijing, 100069, China

Yulin Zhang

You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: XC, JW; methodology and software; analysis: JW and MZ; writing—original draft preparation: XC, JW; writing—review and editing: XC, MR, BS and MC; supervision and funding acquisition: YZ, TZ. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to Yulin Zhang or Tong Zhang .

Ethics declarations

Ethics approval consent to participate, consent for publication, competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Reprints and permissions

About this article

Cite this article.

Chen, X., Wei, J., Zhang, M. et al. Prevalence, incidence, and case fatality of tuberculous meningitis in adults living with HIV: a systematic review and meta-analysis. BMC Public Health 24 , 2145 (2024). https://doi.org/10.1186/s12889-024-19683-4

Download citation

Received : 12 March 2024

Accepted : 02 August 2024

Published : 07 August 2024

DOI : https://doi.org/10.1186/s12889-024-19683-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Epidemiology
Meta-analysis

BMC Public Health

ISSN: 1471-2458

General enquiries: [email protected]

Loading metrics

Open Access

Peer-reviewed

Research Article

Proportion of active tuberculosis among HIV-infected children after antiretroviral therapy in Ethiopia: A systematic review and meta-analysis

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected] , [email protected]

Affiliation College of Health Sciences, Debre Markos University, Debre Markos, Ethiopia

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

Roles Resources, Software, Supervision, Validation, Visualization, Writing – review & editing

Affiliation College of Health Sciences, Debre Berhan University, Debre Berhan, Ethiopia

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation College of Social Science Bahir Dare University, Bahir Dare, Ethiopia

Fassikaw Kebede Bizuneh,
Dejen Tsegaye,
Belete Negese Gemeda,
Tsehay Kebede Bizuneh

Published: August 2, 2024
https://doi.org/10.1371/journal.pgph.0003528
Peer Review
Reader Comments

Despite effectiveness of antiretroviral therapy in reducing mortality of opportunistic infections among HIV infected children, however tuberculosis (TB) remains a significant cause for morbidity and attributed for one in every three deaths. HIV-infected children face disproportionate death risk during co-infection of TB due to their young age and miniatures immunity makes them more vulnerable. In Ethiopia, there is lack of aggregated data TB and HIV mortality in HIV infected children. We conducted an extensive systematic review of literature using Preferred Reporting of Systematic Review and Meta-Analysis (PRISMA) guideline. Five electronic databases were used mainly Scopus, PubMed, Medline, Web of Science, and Google scholar for articles searching. The pooled proportion of TB was estimated using a weighted inverse variance random-effects meta-regression using STATA version-17. Heterogeneity of the articles was evaluated using Cochran’s Q test and I2 statistic. Subgroup analysis, sensitivity test, and Egger’s regression were conducted for publication bias. This met-analysis is registered in Prospero-CRD42024502038. In the final met-analysis report, 13 out of 1221 articles were included and presented. During screening of 6668 HIV-infected children for active TB occurrence, 834 cases were reported after ART was initiated. The pooled proportion of active TB among HIV infected children was found 12.07% (95% CI: 10.71–13.41). In subgroup analysis, the Oromia region had 15.6% (95%CI: 10.2–20.6) TB burden, followed by southern Ethiopia 12.8% (95%CI: 10.03–15.67). During meta-regression, missed isoniazid Preventive therapy (IPT) (OR: 2.28), missed contrimoxazole preventive therapy (OR: 4.26), WHO stage III&IV (OR: 2.27), and level of Hgb ≤ 10gm/dl (OR = 3.11.7) were predictors for active TB. The systematic review found a higher proportion of active TB in HIV-infected children in Ethiopia compared to estimated rates in end TB strategy. To prevent premature death during co-infection, implement effective TB screening and cases tracing strategies in each follow up is needed.

Citation: Kebede Bizuneh F, Tsegaye D, Negese Gemeda B, Kebede Bizuneh T (2024) Proportion of active tuberculosis among HIV-infected children after antiretroviral therapy in Ethiopia: A systematic review and meta-analysis. PLOS Glob Public Health 4(8): e0003528. https://doi.org/10.1371/journal.pgph.0003528

Editor: Sanghyuk S. Shin, University of California Irvine, UNITED STATES OF AMERICA

Received: November 28, 2023; Accepted: July 3, 2024; Published: August 2, 2024

Copyright: © 2024 Kebede Bizuneh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: TB, uberculosis; WHO, World Health Organization; FMOH, Federal Ministry of Health; HIV, human immune deficiency virus; HAAR, highly active antiretroviral therapy; IPT, isoniazid preventive Therapy; CPT, co-trimoxazole preventive therapy

Introduction

People living with the Human Immune deficiency virus (PLHIV) are more susceptible to tuberculosis (TB), which is a leading cause of mortality [ 1 , 2 ]. There is a strong synergy between HIV infection and TB, while PLHIV is at high risk of dying from TB and HIV infection is the biggest risk factor for active TB incidence through declining cellular immunity and increased endogenous reactivation of latent TB bacilli in the lungs [ 3 , 4 ]. HIV infected children are at increased risk of acquiring active TB. HIV-infected persons are sixteen times more likely to be co-infected by TB disease as compared to HIV-negative person [ 5 ].

Tuberculosis continued to be the leading cause of morbidity and mortality for people living with HIV (PLHIV) worldwide [ 6 ]. Globally, in 2022, an estimated 1.3 million children (aged 0–14 years) were diagnosed with TB, accounting for approximately 12% of the total TB cases of 10.6 million [ 5 , 7 ]. The co-infection of HIV and TB is particularly dangerous, with around 214,000 children dying from TB disease in 2022 where 31,000 of those were attributed to children TB and HIV infections [ 5 ]. The burden of TB infection varies significantly across each continents, African and Southeast Asian regions attributed for 81% of global TB deaths in 2022 [ 8 ]. In Sub-Saharan African countries, 10% to 15% of HIV-infected children suffer from the dual burden of HIV and TB, with a lifetime risk of 21% and two-thirds of cases remain undiagnosed [ 5 , 9 – 11 ].

By the end of 2022, only 46% of children (aged 0–14 years) who were receiving antiretroviral therapy (ART) were able to achieve viral load suppression, which is a crucial factor in reducing the occurrence of new opportunistic infections [ 5 , 8 , 11 ]. However, TB infection remains responsible for one in every third deaths of HIV infected children in source-limited setting [ 7 , 12 , 13 ]. Ethiopia is one of the top 30 countries burdened by tuberculosis (TB) and experiences a significant distribution of TB and HIV co-infection across all regions. The incidence rates was estimated as 0.17 cases per 1000 population for HIV and 1.64 per 1000 for TB [ 1 , 2 ]. Previous national level study finding among 1,830,880 HIV and 192,359 TB patients reported,7.34% of TB patient had HIV infection with a significant regional variation across regions [ 14 ]. The prevalence of TB/HIV co-infection varies considerably in across each regions including 7.2% in Amhara region (Northern Ethiopia) [ 15 ] to 23.6% southern Ethiopian (SNNR) [ 16 ]. The differences in healthcare accessibility and socio-demographic factors including wealth index and literacy rate contribute to variations in TB/HIV co-infection prevalence [ 14 ]. HIV-infected children face a higher risk of morbidity and mortality during co-infection due to their young age and immature immune makes them more vulnerable [ 4 , 17 ].

Previous studies finding in Ethiopia [ 7 , 18 , 19 ] reported that multifactorial causative factors were attributed for active TB occurrence among HIV infected children including underweight, advanced WHO clinical stages, missed IPT and CPT [ 5 , 7 , 13 , 20 ]. However, CD4 count being ≤200 cells/ml serves as a proxy indicator for incidence of active TB [ 13 ]. Concomitant administration of ART with isoniazid preventive Therapy (IPT) had significantly effect of reducing active TB cases by over 80% HIV infected Children [ 21 ]. However, IPT completion rate and adherence of ART has affected by caregivers and regimen characteristic [ 18 ]. Although several small-scale studies have reported on the epidemiology of TB/HIV co-infection among HIV-infected children in various parts of Ethiopia [ 5 , 12 , 13 ]; however, there is a lack of aggregated data on co-infection after HIV-infected children started antiretroviral therapy. Therefore, this systematic review and meta-analysis aimed to estimate the pooled burden of active TB among HIV-infected children.

Study area and setting

This study was conducted in Ethiopia from January 1, 2013, to December 30, 2022, spanning a period of 10 years. In Ethiopia, there are nine regions including Tigray, Afar, Amhara, Oromia, SNNR, Somalia, Gambella, Benishangul Gumuz, Harari and two city administrative [ 13 ].

Searching strategy and protocol.

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline was followed to report the findings of the selected articles presented clearly described in ( S1 Checklist ) [ 22 ].

Additionally, this systematic review and meta-analysis have registered in the Prospero protocol with CRD42024502038 ( https://www.crd.york.ac.uk/prospero/#recordDetails ).

Furthermore, this systematic review was used five international electronic databases were mainly used including Scopus, PubMed, Medline, Web of Science, and Google scholar. The searching was focused on English language published articles and the searching was done. We employed controlled vocabulary terms (MeSH) and free text to extract articles ( S1 Text ) .

The search included topics such as active tuberculosis, pulmonary TB, extra pulmonary TB, HIV infection, individuals, children, pediatrics, neonates, lymphadenitis, disseminated TB, and Ethiopia. The search terms used to identify relevant studies included "Epidemiology" OR "Incidence" OR "Case fatality" "Tuberculosis" OR "Pulmonary Tuberculosis" OR "Disseminated Tuberculosis" OR "Lymphadenitis" AND "HIV" OR "AIDS" AND "Children" OR "Pediatrics" OR "Infant" AND "Ethiopia". Furthermore, this systematic review and meta-analysis employed the PICO (Population, Intervention, Comparison, and Outcomes) framework to assess the eligibility of the articles and enhance evidence-based medicine and research by facilitating the structuring of clinical or research questions. This included as follows (P) Population of interest: Children living with HIV on anti-retroviral therapy in Ethiopia,(I) Intervention; all children HIV infected children started Anti-retroviral therapy, (C) Comparison; children without active TB with stand on HIV cohort (O) Outcome of interest: active TB in HIV-infected children found in Ethiopia were used for PICO frameworks.

Eligibility criteria

Inclusion criteria..

This systematic review and meta-analysis report had included a given articles with defined outcome of any TB types in HIV infected children with the following inclusion criteria. 1) scientific papers reporting co-infections of TB and HIV in HIV-infected children in Ethiopia, 2) articles containing burden or incidence reports of active TB in HIV-infected children, 3) studies published within the past ten years with cross-sectional or cohort designs and published in English, and 4) study subjects limited to children aged ≤15 years.

Exclusion criteria.

Studies that reported lacking abstracts and/or full-text, anonymous reports, editorials, and qualitative studies were excluded from the analysis. Furthermore, prior to the analysis, unfitted articles without a journal name and/or author, lacked the year of publication, and citations without abstracts and/or full-text were removed.

Outcome ascertainment.

The first outcome was the proportion of active TB cases (including all types of TB) among HIV infected children after anti-retroviral therapy. The proportions of TB burden was calculated by the number of children who developed active TB during on ART treatment divided by the total children from thirteen study and multiplied it by 100. Identifying independent predictors for active TB occurrence in HIV infected children on ART was the second objective. Accordingly, we collected significant predictors reported from included articles with their adjusted odd ratio with its 95% confidence interval was extracted from original studies and to computed the pooled odds ratio for final predictors.

Operational words

Advanced hiv disease..

Defined as WHO clinical stages III and IV in children older than five years. However, in children younger than five years living with HIV, they are considered to have advanced HIV disease regardless of their clinical stages. Mild WHO clinical stages refer to stages II and I in HIV-positive children. ART adherence for children; is categorized as follows: Good (>95%) if ≤2 doses are missed out of 30 doses or ≤3 doses out of 60 doses and Fair (85–94%) if 3–4 doses are missed out of 30 doses and poor (<85%) if >5 doses are missed out of 30 doses of ART drug [ 23 ].

Data extraction.

Four Authors (FK, BN, DT, and TK) extracted articles and evaluated the quality of each study by determining the eligibility based on given criteria for selection of studies. The discussion was used to settle any disagreement or uncertainty that arose during the article extraction and removing duplication process. These reviewers assessed the full-text articles; if one or more of them believed an article could be significant, it qualified after the article was carefully examined its titles, abstracts, and full text by three authors (FK, TK, and DT) used a Microsoft Excel spreadsheet to extract the specifics of each article. Three independent reviewers assessed each included article’s quality using the JBI checklists given for all articles as described in ( S1 Table ) [ 24 , 25 ]. All eligible studies approved by all authors’ agreements about principal investigators, year of publication, study period, study setting, study population, and sample size retrieved from the identified articles. The biases of primary studies checked, assessed and screened by three authors (FK, BN and TK), evaluated, and screened ( S2 Table ). Any disagreements among reviewers regarding the critical appraisal were settled through discussion and building consensus for submission.

Software and statistical-analysis.

Using End-Note Aversion 8.1, all detected and potentially suitable published article citations were exported and gathered; duplications were eliminated during the selection and screening processes. Two independent reviewers (FK, and TK) first reviewed the abstracts of the publications before moving on to the full-text articles, which they then evaluated following the particular standards for ultimate inclusion and modifying the data on a Microsoft Excel spreadsheet, and employed the STATA version 17 for further analysis. Descriptive statistics, and weighted inverse variance random-effects meta-regression were used to present the review’s results to estimate pooled burden of active TB in HIV infected children [ 26 ]. The eligible articles were extracted using Meta-XL Excel version 5.3sheet [ 27 ] using identified risk factors from each selected studies and made combined each categorical variables and estimated risk factors for active TB [ 26 ]. The Higgs I 2 statistics were utilized to detect heterogeneity among studies and elaborated using Cochran’s Q test [ 28 ]. The degrees of statistical heterogeneity between the studies were assessed using I2 statistics; values of 25%, 50%, and 75% were thought to indicate modest, medium, and high levels of heterogeneity, respectively [ 38 ]. The source of heterogeneity among studies was examined using the subgroup and sensitivity analysis. The random effect regression model was used for the data-identified heterogeneous analysis [ 26 ]. The publication biases were assessed by visual inspection of funnel plots of the graph and quantitative using Egger’s weighted regression at p <0.1 [ 29 , 30 ].

Descriptive characteristics of the studies

A total of 1221 primary studies were identified including 43 from Web of Science, 631 from PubMed, 352 from Medline, 15 from Scopus, and 162 articles from Google Scholar. After care full screening throughout the articles titles and abstracts, 1208 articles excluded. Thirteen (N = 13) individual studies that met inclusion criteria were included for the final meta-analysis reported [ 4 , 15 – 17 , 31 – 39 ] as presented and described in PRISMA diagram ( Fig 1 ) .

PPT PowerPoint slide
PNG larger image
TIFF original image

https://doi.org/10.1371/journal.pgph.0003528.g001

Regarding to include articles description all are published in scientific journals from December 30, 2012 to January 1 st , 2023. Regionally seven(N = 7)of articles among eligible articles were from Amhara region (Northern parts of Ethiopia) [ 15 , 31 – 33 , 38 , 39 ] and three articles were from southern nation nationalities region (SNNRs) of Ethiopia [ 16 , 34 ], two of the remaining articles were from Benishangul Gumuz (North west) part of Ethiopia [ 4 , 17 ], and one were from Oromia [ 37 ] regions which is clearly described in ( Table 1 ) .

https://doi.org/10.1371/journal.pgph.0003528.t001

Description reports of included studies

From included 13 individual studies, 6668 HIV infected children were participated and 834 cases of TB among HIV, infected children reported. The mean (±SD age of the participants was reneged from 8.2(±3.6) years. Of the total, nine(9/13) included articles were employed cohort design [ 16 , 17 , 32 , 34 , 38 , 39 ], whereas four of the included articles data were collected by correctional recorded review of follow up design [ 4 , 15 , 31 , 35 , 38 ] were used. The highest number of active TB cases (23.6%) was reported from the SNNPR region (Southern Ethiopia) [ 16 ] and the lowest number (7.2%) of active TB cases was from Amhara region (North West Ethiopia) [ 15 ] regions respectively.

Pooled prevalence of TB in HIV infected children on ART

In the final meta-analysis report, utilizing 13 published studies, we discovered that the estimated pooled burden of active TB among HIV-infected children in Ethiopia was 12.1% (95% CI: 10.7–13.4; I 2 = 63.4%, P = 0.001) as described in ( Fig 2 ) .

https://doi.org/10.1371/journal.pgph.0003528.g002

Factors associated with active TB in HIV infected children on ART

In our final report, there was significant heterogeneity observed among the studies included in the meta-analysis (I2 = 63.4%, P <0.001 as depicted in pooled proportion of active TB in HIV infected children. Accordingly, the pooled TB prevalence was slightly lower in hospital setups at 11.05% (95%CI: 9.4–12.3) compared to health center studies, which reported 14.1% (95%CI: 11.74–16.33) ( Fig 3 ). Likewise, the pooled TB burden among HIV-infected children was significantly higher in studies conducted in the Oromia region at 15.6% (95%CI: 10.2–20.6) compared to studies included from the SNNR, which had a result of 12.8% (95%CI: 10.03–15.67) as described in ( Fig 3 ) .

https://doi.org/10.1371/journal.pgph.0003528.g003

In this report, the duration of follow-up periods was found to be significantly associated with the occurrence of active TB. Sub-group analysis revealed that the pooled burden of TB among HIV-infected children with a follow-up period of ≤10 years was significantly higher at 13.67% (95%CI: 11.24–15.1) compared to those with a follow-up period of >10 years, which had estimation of 10.9% (95%CI: 9.1–12.8) as described in ( Fig 4 ) .

https://doi.org/10.1371/journal.pgph.0003528.g004

In this systematic review, to identify factors associated with active TB we analyzed adjusted odds ratios from primary studies and made grouped significant categorical variables from previous studies by themes, including WHO advanced clinical stages (III&IV), baseline CD4 count, missed isoniazid preventive therapy (IPT), missed cotrimoxazole preventive therapy (CPT), level of hemoglobin, antiretroviral therapy (ART) adherence status, and functional status of children. But, it is noted that only missed IPT, missed CPT, WHO advanced clinical stages (III&IV) and level of hemoglobin were found predictors for TB as shown in ( Table 2 ) .

https://doi.org/10.1371/journal.pgph.0003528.t002

Accordingly, studies containing HIV infected children who missed IPT was double fold increase the odds of active TB occurrence compared with ever given children (OR: 2.28; 95% CI: 1.99–3.08) and also the likelihood of active TB occurrence in HIV infected children who are on advanced WHO clinical stage (III&IV) was 2.27 times (OR: 2.27; 95% CI: 1.81–2.73) higher than with children were on WHO clinical stage II and I. Furthermore, the probability of TB co-infection for HIV-infected children was 3.11 times higher (OR = 3.11, 95% CI: 1.57–4.7) for cases having hemoglobin≤10 mg/dl compared to children with a Hgb >10 mg/dl as described in ( Fig 5 ) . Furthermore HIV-infected children who missed CPT had 4 time higher odds of TB co-infection than counter group (OR: 4.26, 95% CI: 3.47–5.28) clearly depicted in ( Fig 6 ) .

https://doi.org/10.1371/journal.pgph.0003528.g005

https://doi.org/10.1371/journal.pgph.0003528.g006

Publication bias assessment

The publication bias was assessed graphically using funnel plots, and the findings revealed no systematic deviation as depicted in ( Fig 7 ) .

https://doi.org/10.1371/journal.pgph.0003528.g007

In addition, Quantitative analysis we had conducted and assessed using Begg’s and Egger’s tests for biases. Egger’s regression was performed, and the report indicated the absence of publication bias for using two factors sample size and follow up periods as elaborated in ( Table 3 ) .

https://doi.org/10.1371/journal.pgph.0003528.t003

This systematic review and meta-analysis revealed the pooled burden of active (TB) among HIV-infected children in Ethiopia and further identified predictors associated with active TB.

In the final report of 13 individual studies with including 5834 participants, 834 TB and HIV co-infected cases were found at national level. This made the pooled estimated prevalence of active TB was 12.07% (95%CI: 10.73–13.4). This finding is higher than previously reported 0.78% in Ethiopia [ 40 ], 43% in SSA countries [ 41 ], and 1.03% in Portugal [ 42 ]. The findings indicate a significantly high burden of active and need for immediate attention to meet the targets set by the End TB Strategy to achieved the goal of a 90% reduction should to be (≤ 10 TB cases per 100,000 population) by 3035 requires urgent action [ 1 , 2 ]. Conversely, this report is lower than the previous meta-analysis finding 15% in middle-income countries [ 43 , 44 ] and 32% meta-analysis reported in Nigeria [ 45 ]. The variation in the pooled estimate of active TB among the included studies may be attributed to differences in study time TB control measures, and variations among the studies in Nigeria and in Ethiopia [ 46 ].Also the variation in healthcare infrastructure, treatment practices, and regional differences also influence pooled prevalence rates.

This systematic review and meta-analysis revealed that HIV-infected children with advanced WHO clinical stage (III&IV) have a twofold increased likelihood of experiencing active TB compared with mild advanced WHO clinical stage. This finding is supported by previous meta-analyses conducted in Ethiopia [ 47 – 50 ]. This possible justification for this finding is that children with advanced HIV disease may have compromised immune systems due to their clinical stage III&IV, which is associated with low CD4 counts and could lead to an increased risk of developing opportunistic infections, including TB [ 51 ].

The report of this meta-analysis revealed that, the risk of developing active TB was four fold increased for HIV infected children with Hgb ≤10 gm/dl than in those with Hgb >10 gm /dl. This is consistent with the previous study finding [ 52 – 54 ]. This could be attributed to the fact that anemia can indeed impair the immune response and the bactericidal activity of leukocytes, making individuals more vulnerable to infections, including tuberculosis.

The odds of developing active TB among HIV infected children who missed CPT had a four-fold risk as compared ever given children. This is consistent with previously reported meta-analysis in finding in Ethiopia [ 53 , 55 , 56 ]. This might be due to cotrimoxazole, is prescribed to HIV-infected children to prevent lethal opportunistic by preventing production of nucleic acids and proteins essential for the growth of opportunistic infections including PCP, and toxoplasmosis thus helping to counteract immunosuppression and disease progression.

Consistent with previous studies finding in [ 12 , 17 , 32 , 33 , 38 , 57 – 60 ],concurrent administering of IPT after ruled-out of active TB symptoms with ART demoted more than 90% of active TB-associated incidence of morbidity [ 3 , 61 , 62 ]. In the final report of this systematic review and meta-analysis, it was found that HIV-infected children who did not receive IPT (preventive therapy) were at a twofold higher risk compared to the control group. This might be IPT (Isoniazid Preventive Therapy) has the potential to reduce the burden of latent mycobacteria in the lungs. This is because Isoniazid preventive therapy can effectively stop the progression of latent TB infection from developing into active TB disease [ 17 , 63 ].

In contrast to previous systematic review findings [ 53 , 55 ] and primary studies reported [ 12 , 17 , 32 , 33 , 38 , 57 – 60 ] this meta-regression found no significant association between declined CD4 count (≤200 cells/cml), age of patients, duration of follow-up, comorbidity status, and functional status with the risk developing active TB in HIV co-infection children. This might be related to the methodological differences, heterogeneity of included study populations, sample size limitations, publication bias, unaccounted factors, and further experimental studies are highly needed to better understand this relationship.

Strengths and limitations of the study

The strengths of this study include an extensive search strategy, clear inclusion criteria, and the involvement of five independent authors in the quality, inclusion and analysis for this systematic review and meta-analysis. However, there are several methodological limitations including focusing on articles published only on English were included and the extracted articles were from four Ethiopian regions were included in the analysis, such that some of the region may not be represented. In addition, limitations such as reliance on clinical stratification or non-laboratory-supported staging, sub-standard diagnostic capacities in health facilities, a small number of included studies, and the use of retrospective data may potentially affect the validity of the results.

Conclusion and recommendation

This systematic review found a higher prevalence of active TB in HIV-infected children in Ethiopia compared to the estimated rates in the end TB strategy. Risk factors for active TB were identified included WHO clinical stages IV and III, low hemoglobin, missed IPT, and missed CPT were predictors. To reduce the risk of active TB, it is crucial to implement effective strategies such as regular IPT mission and addressing the gaps in treatment, and routine screening for active TB during follow-ups to prevent premature death.

Supporting information

S1 checklist. prisma 2020 chiecklist..

https://doi.org/10.1371/journal.pgph.0003528.s001

S1 Text. Article searching strategy for one of PubMed date base.

https://doi.org/10.1371/journal.pgph.0003528.s002

S1 Table. The JBI quality assessment check list for included studies.

https://doi.org/10.1371/journal.pgph.0003528.s003

S2 Table. Minimal data set for this met-analysis.

https://doi.org/10.1371/journal.pgph.0003528.s004

Acknowledgments

Author contributions.

Fassikaw Kebede Bizune’s ; Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing–original draft, Writing–review & editing.

Dejen Tsegaye’s ; Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization.

Belete Negese; Resources, Software, Supervision, Validation, Visualization, Writing -review & editing.

Tsehay Kebede’s Bizueneh: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Validation, Visualization, Writing–original draft, Writing–review & editing.

View Article
Google Scholar
PubMed/NCBI
23. Ethiopia National Guidelines For Comprehensive Hiv Prevention, Care And Treatment. Guideline 2017;Art Management Gudeline Accessed 27 / 05/2024( https://www.childrenandaids.org/sites/default/files/2018-05/Ethiopia_Nat%20Guidelines%20ART_2017.pdf )

Disclaimer: Early release articles are not considered as final versions. Any changes will be reflected in the online version in the month the article is officially released.

Volume 30, Number 9—September 2024

Research Letter

Confirmed case of autochthonous human babesiosis, hungary.

EID Search Options
– Search articles by author and/or keyword.
– Search articles by the topic country.
– Search articles by article type and issue.

Metric Details

Article views: 57.

Data is collected weekly and does not include downloads and attachments. View data is from .

What is the Altmetric Attention Score?

The Altmetric Attention Score for a research output provides an indicator of the amount of attention that it has received. The score is derived from an automated algorithm, and represents a weighted count of the amount of attention Altmetric picked up for a research output.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
J Multidiscip Healthc
PMC11318598

A Machine Learning Method for Differentiation Crohn’s Disease and Intestinal Tuberculosis

1 Department of Gastroenterology, Third Xiangya Hospital, Central South University., Changsha, Hunan, People’s Republic of China

2 Department of Gerontology, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China., Changsha, Hunan, People’s Republic of China

Jingshu Chi

3 Department of Gastroenterology, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China., Changsha, Hunan, People’s Republic of China

Associated Data

All relevant ML methods and codes can be freely accessed at https://github.com/philiplaw1984/IBD/ .

Whether machine learning (ML) can assist in the diagnosis of Crohn’s disease (CD) and intestinal tuberculosis (ITB) remains to be explored.

We collected clinical data from 241 patients, and 51 parameters were included. Six ML methods were tested, including logistic regression, decision tree, k-nearest neighbor, multinomial NB, multilayer perceptron, and XGBoost. SHAP and LIME were subsequently introduced as interpretability methods. The ML model was tested in a real-world clinical practice and compared with a multidisciplinary team (MDT) meeting.

XGBoost displays the best performance among the six ML models. The diagnostic AUROC and the accuracy of XGBoost were 0.946 and 0.884, respectively. The top three clinical features affecting our ML model’s result prediction were T-spot, pulmonary tuberculosis, and onset age. The ML model’s accuracy, sensitivity, and specificity in clinical practice were 0.860, 0.833, and 0.871, respectively. The agreement rate and kappa coefficient of the ML and MDT methods were 90.7% and 0.780, respectively (P<0.001).

We developed an ML model based on XGBoost. The ML model could provide effective and efficient differential diagnoses of ITB and CD with diagnostic bases. The ML model performs well in real-world clinical practice, and the agreement between the ML model and MDT is strong.

Graphical Abstract

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0001.jpg

Introduction

Inflammatory bowel disease (IBD) is a chronic inflammation of the gastrointestinal tract. Ulcerative colitis (UC) and Crohn’s disease (CD) are the principal forms of IBD. IBD is a global disease. In 2020, newly industrialized countries were at a stage where the incidence increased, and the prevalence was relatively low. The incidence of this disease is stable in Western countries, but its prevalence is rapidly increasing. 1 Intestinal tuberculosis (ITB) is also a chronic inflammatory gastrointestinal disease caused by mycobacterium tuberculosis. Tuberculosis is the second leading cause of death caused by an infectious disease after COVID-19, contributing to 1.5 million deaths in 2020. Intestinal tuberculosis is one of the most common forms of extrapulmonary tuberculosis. 2 The global burden of CD and ITB will continue to increase in future decades.

CD is a complex chronic inflammatory gastrointestinal condition with variable clinical manifestations. ITB shares many clinical features with CD. Distinguishing these two diseases can be complicated. IBD diagnosis is especially difficult at hospitals lacking medical resources and staff. This situation is even worse in some developing and newly industrialized countries.

Multidisciplinary team (MDT) meetings play an established role in managing multiple chronic diseases, including IBD and ITB. Most MDT encounters were successful from both a process and a clinical outcome perspective. 3 The Inflammatory Bowel Disease Group of the Chinese Gastroenterology Society strongly recommends MDT meetings, especially for patients whose diagnosis is difficult. 4 However, MDT meetings usually depend on experienced doctors and advanced medical equipment.

In recent years, machine learning (ML) technology has shown promising applications in gastroenterology. Based on clinical data, ML methods were able to predict upper gastrointestinal bleeding and gastric cancer risk in patients after Helicobacter pylori eradication. 5 , 6 ML models outperform traditional statistical models that use routinely available clinical data for risk prediction in patients with IBD. 7 Waljee AK et al developed an ML model to identify patients with Crohn’s disease likely to respond durably to ustekinumab. 8 The ML model could substantially improve the ability to predict IBD-related hospitalization and outpatient steroid use. 9 However, there are still limitations in the current literature. First, few studies have investigated the differentiation of CD and ITB. Second, few studies have evaluated the performance of ML models in real-world clinical practice.

In this study, we first developed an ML model to assist in diagnosing of CD and ITB. The performance was subsequently compared with that of MDTs in real-world clinical practice.

Materials and Methods

Study design.

This study was divided into two stages. Stage 1: ML model development. Using six different ML methods, a training model is trained for CD and ITB differential diagnoses based on retrospective clinical data. Stage 2: Test the ML model in real-world clinical practice. After the MDT meeting, the MDT candidates were diagnosed with ITB or CD by the MDT group. The clinical data of these patients were entered into the ML model developed in stage 1, and the diagnostic results were output accordingly. After six months of follow-up, considering the effect after treatment, the final diagnosis was confirmed. The performance of the ML model was recorded, analyzed, and compared with that of the MDT model. Figure 1 shows the flow chart.

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0002.jpg

Study flow chart.

This study was conducted in the Gastroenterology Department of the Third Xiangya Hospital of Central South University. This research was conducted in accordance with the Declaration of Helsinki and national and institutional standards. The clinical research ethics committee of the Third Xiangya Hospital of Central South University (No.22272) approved the study protocol. Informed consent was obtained from all the MDT candidates. The study is complete and is registered at http://www.chictr.org.cn (ChiCTR2200066847).

Data Collection and Dataset Establishment

In the stage of ML model development, clinical data were collected from Jan 2013 to Jun 2021. The diagnosis was based on clinical performance, endoscopic and pathological characteristics, as well as the response to Crohn’s disease treatment and anti-tuberculosis therapy. All cases were confirmed based on the Chinese consensus and British guidelines for IBD by two experienced gastroenterologists. 10 , 11 For ML model development, we collected 51 parameters from 123 patients with ITB and 118 patients with CD, including four demographic data points, six symptoms, 20 laboratory results, one comorbidity, two complications, 12 endoscopic characteristics and six pathological characteristics. The variables included were widely available in the diagnosis of ITB and CD. The included endoscopic and pathological characteristics were based on European consensus. 12 , 13 The descriptive statistics of the clinical ML data are shown in Table 1 .

Descriptive Statistics for Machine Learning

	ITB (N=123)	CD (N=118)

Onset age(years)	41.22±16.41	28.24±11.25	<0.001**
Age at diagnosis(years)	43.04±16.91	30.58±11.68	<0.001**
Course of disease(years)	1.74±2.48	2.60±2.92	0.15
Male	76 (61.8%)	78(66.1%)	0.488

Abdominal pain	98 (79.7%)	89(75.4%)	0.431
Diarrhea	19(15.4%)	49(41.5%)	<0.001**
Hematochezia	6(4.9%)	12(10.2%)	0.119
Constipation	5(4.1%)	6(5.1%)	0.706
Fatigue	9(7.3)	4(3.4%)	0.179
Fever	5(4.1%)	5(4.2%)	0.947

OB	28(22.8%)	65(55.1%)	<0.001**
ALT(U/L)	19.45±15.89	15.23±17.32	0.050
AST(U/L)	24.11±14.70	17.10±10.88	<0.001**
BUN(mmol/L)	5.03±3.90	4.48±5.40	0.370
Cr(umol/L)	80.16±93.94	68.01±15.52	0.167
UA(umol/L)	299.01±128.11	313.72±88.84	0.303
PLT(10 /L)	286.63±127.92	334.19±142.84	0.007**
RBC(10 /L)	4.17±0.85	4.34±0.69	0.086
WBC(10 /L)	7.13±3.54	7.26±2.71	0.752
Hb(g/L)	113.17±25.74	114.17±24.60	0.759
HCT(%)	0.37±0.27	0.35±0.06	0.439
ESR(mm/H)	42.19±31.65	42.03±34.34	0.970
Elevated CRP	58/89(65.2%)	82/106(77.4%)	0.059
Elevated HsCRP	71/89(79.8%)	93/106(87.7%)	0.129
ALB(g/L)	34.59±7.68	35.08±6.80	0.602
Na(mmol/L)	138.06±4.22	140.15±2.53	<0.001**
K(mmol/L)	4.00±0.53	3.94±0.47	0.371
T-spot	62/92(67.4%)	6/79(7.6%)	<0.001**
ANCA	2/92(2.8%)	8/79(10.1%)	0.027*
ANA	13/92(14.1%)	18/79(22.8%)	0.143

Terminal ileum	33/82(40.2%)	87/118(73.7%)	<0.001**
Ileocecal junction	51/82(62.2%)	88/118(74.6%)	0.061
Ascending colon	43/82(52.4%)	75/118(63.6%)	0.116
Transverse colon	32/82(39.0%)	79/118(67.0%)	<0.001**
Descending colon	23/82(28.0%)	75/118(63.6%)	<0.001**
Sigmoid colon	30/82(36.6)	88/118(74.6%)	<0.001**
Rectum	32/82(39.0%)	93/118(78.8%)	<0.001**
Erythema or Friability	50/82(61.0%)	113/118(95.8%)	<0.001**
Erosion or Ulcer	60/82(73.2%)	109/118(92.4%)	<0.001**
Post-inflammatory polyps	25/82(30.5%)	33/118(28.0%)	0.699
Stenosis	23/82(28.0%)	30/118(25.4%)	0.679
Longitudinal ulcer or Cobblestone	0/82(0.0%)	33/118(28.0%)	<0.001**

Acute inflammation	53/77(68.8%)	114/118(96.6%)	<0.001**
Granulomas	43/77(55.8%)	67/118(56.8%)	0.898
Crypt architectural irregularity	16/77(20.8%)	68/118(57.6%)	<0.001**
Lymphoid aggregates	30/77(39.0%)	72/118(61.0%)	0.003**
Caseous necrosis	7/77(9.1%)	0/118(0.0%)	<0.001**
Epithelioid-cell granulomas	0/77(0.0%)	32/118(27.1%)	0.001**

Pulmonary tuberculosis	52(42.3%)	1(0.8%)	<0.001**
Intestinal obstruction or perforation	23(18.7%)	19(16.1%)	0.597
Crissum abscess or Perianal fistula	0(0.0%)	18(15.3%)	<0.001**

Notes : *P<0.05; **P<0.001.

Abbreviations : OB, occult blood in stool; ALT, alanine transaminase; AST, glutamic-oxaloacetic transaminase; BUN, blood urea nitrogen; Cr, creatinine; UA, uric acid; PLT, blood platelet; RBC, red blood cell; WBC, white blood cell; Hb, hemoglobin; HCT, hematocrit; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; HsCRP, high-sensitivity C-reactive protein; ALB, albumin; Na, sodium ion; K, potassium ion; T-spot, tuberculosis-spot test; ANCA, anti-neutrophil cytoplasmic antibodies; ANA: antinuclear antibodies.

Study Population and Sample Estimation

In stage 2, the research hypothesis is that the ML model’s area under the receiver operating characteristic curve (AUROC) is greater than 0.5 for MDT candidates. The AUC of the ML model for patients who were difficult to diagnose was 0.78 in the previous experiment, with alpha=0.05 (one-sided) and beta=0.1. Based on the relevant studies at home and abroad, the ratio between the ITB and CD groups was 1:2–1:4. 14 , 15 A review of the historical records of MDT patients in our hospital revealed that the ratio of ITB to CD patients was approximately 1:3. Therefore, in this study, the ratio between the ITB and CD groups was 1:3. The sample size of this study was calculated via PASS11. The number of samples was estimated to be at least 11 ITB patients and 31 CD patients.

Fifty MDT candidates were ultimately included in the study from Sep 2021 to Oct 2022. After the MDT meeting, seven patients with other diseases were excluded, and 43 patients who were diagnosed with ITB or CD by the MDT group were included. The inclusion and exclusion criteria are as follows:

The inclusion criteria were: 1. Patients highly suspected of having CD or ITB; 2. Clinical data were complete, and the MDT was completed; 3. Post follow-up, the final diagnosis was CD or ITB.

Exclusion criteria: 1. Patients with confirmed CD or ITB who do not need an MDT; 2. Other diseases were confirmed after the MDT.

In the ML model development stage, we tested six different mainstream ML methods, including logistic regression (LR), decision tree (DT), K-nearest neighbor (KNN), multinomialNB (MNB), multilayer perceptron (MLP), and XGBoost. LR is a process of modeling the probability of a discrete outcome given an input variable. DT learning is a predictive algorithm that uses both categorical and numerical data to assign samples to specific classes. 16 KNN is a non-parametric approach; for an input x, KNN identifies k objects in the training data closest to x with a predefined metric and makes a prediction by majority vote from the classes of the k objects. 17 MNB is a probabilistic algorithm that is commonly used to categorize text. An MLP is a feed-forward artificial neural network model that maps sets of input data onto a set of appropriate outputs. XGBoost implements ML algorithms under the gradient boosting framework; it provides parallel tree boosting that quickly and accurately solves many data science problems. 18

Missing data is a common problem that has a greater impact on data analysis. The multiple imputation method Miceforest is a non-parametric imputation method that can cope with different types of variables simultaneously and is widely used in medical data analysis. 19 , 20 Therefore, this study uses Miceforest to input the missing data. All relevant ML methods and codes can be freely accessed at https://github.com/philiplaw1984/IBD/ .

Interpretability for ML

Understanding why an AI model makes a certain prediction is important for doctors when making clinical decision. This study introduces the SHapley Additive exPlanations (SHAP) method and the Local Interpretable Model-agnostic Explanations (LIME) method to explain our ML model. SHAP is a method to explain individual predictions, and it is based on the game’s theoretically optimal Shapley values. LIME explains a prediction of an ML model (classification or regression) for a query point by finding important predictors and fitting a simple interpretable model.

A senior professor of Gastroenterology led the MDT group. Other members include an associate professor of Gastroenterology, a professor of gastrointestinal surgery, a professor of radiology, an associate professor of pathology, a senior IBD specialist nurse, and a coordinator in charge of management.

Experimental Settings and Evaluation Values

All the ML experiments in this study were performed on a personal computer (Windows 10). The experiments were performed in Python 3.8 via PyCharm and Jupyter Notebook Integrated Development Environment.

In stage 1, the evaluation values of the ML methods were AUROC, accuracy, average precision (AP), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The dataset used for ML model development was divided into a training set, a validation set, and a test set at a ratio of 6:2:2. A five-fold cross-validation method was adopted.

In stage 2, the primary outcome measures were accuracy, sensitivity, specificity, PPV, and NPV. The secondary outcome measures were the agreement rate and the kappa coefficient.

Statistical Analysis

Statistical analyses were performed via SPSS version 22.0 (IBM SPSS Statistics, IBM Corporation, Armonk, NY, USA). Categorical variables were described by frequencies and proportions (%), and continuous variables were described by means and standard deviations (SDs) unless otherwise stated. Continuous variables were compared via Student’s t test or one-way analysis of variance, and categorical variables were compared using the χ2 test. Non-normal data or data without variance homogeneity were analyzed using non-parametric tests (Mann–Whitney test). A two-tailed P value < 0.05 was considered statistically significant.

ML Method Assists in the Diagnosis of ITB and CD Based on Clinical Data

XGBoost performs the best among the six ML models. The diagnostic AUROC, accuracy, AP, sensitivity, specificity, PPV, and NPV of XGBoost were 0.946, 0.884, 0.834, 0.889, 0.878, 0.877, and 0.899, respectively. Figure 2 shows the average AUROC of the XGBoost method after 5-fold cross-validation. The performance of all six ML classification methods is shown in Table 2 .

Performance of All 6 ML Classification Methods

	AUROC	Accuracy	AP	Sensitivity	Specificity	PPV	NPV

LR	0.894	0.846	0.791	0.847	0.846	0.845	0.859
DT	0.829	0.826	0.763	0.819	0.83	0.818	0.843
KNN	0.631	0.602	0.553	0.653	0.552	0.579	0.633
MNB	0.778	0.639	0.607	0.391		0.777	0.601
MLP	0.863	0.78	0.721	0.730	0.829	0.799	0.772
					0.878

Note : The best result of each evaluation indicator is indicated in bold.

Abbreviations : AUROC, area under the receiver operating characteristic curve; AP, average precision; PPV, positive predictive value; NPV, negative predictive value; LR, logistic regression; DT, decision tree; KNN, k-nearest neighbor; MNB, multinomial NB; MLP, multilayer perceptron.

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0003.jpg

The average AUROC of the XGBoost method after 5-fold cross validation.

In this study, we introduce the SHAP and LIME methods to explain our ML models. Figure 3 shows how the SHAP method explains our ML models. As shown in Figure 3A , each point represents a case. ITB and CD were coded as 0 and 1, respectively in our ML experiment. A different color represents a different value of the clinical data; red indicates higher values for continuous variables, whereas blue indicates lower values. For categorical variables, red represents positive variables, and blue represents negative variables. The horizontal coordinate represents each clinical data of every case corresponding to a SHAP value. The ML model calculates all variables’ SHAP values together. In the output phase, a high SHAP value indicates that the prediction probability of CD increases. Instead, a low SHAP value indicates that the prediction probability of ITB would increase. Figure 3B shows the weights of all the clinical data included in the ML model. The top 5 variables that may affect result prediction in our ML model were T-spot, pulmonary tuberculosis, onset age, OB, and terminal ileum affected. Figure 3C is a screenshot from a global explain program based on SHAP, which can display every individual case’s predicted result and its corresponding SHAP value.

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0004.jpg

SHAP method to explain our ML models.

However, the SHAP method could explain how the ML model predicts every patient’s result. To better understand how our ML model works, we introduce another method of visualization and explanation called LIME. The LIME method calculates the predicted value according to the feature value and weight. Figure 4 shows two examples of how the LIME method predicts results. Figure 4A shows an ITB patient’s prediction, and Figure 4B shows a CD patient’s prediction. Clinical features in orange indicate that the prediction is prone to CD, and clinical features in blue indicate that the prediction is prone to ITB.

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0005.jpg

LIME method to explain our ML models.

ML Model in Real-World Clinical Practice

Forty-three patients were diagnosed with ITB or CD by the MDT group. The clinical data of these patients were input into the ML model. The output diagnoses were 14 ITB and 29 CD cases. The descriptive statistics of the clinical data for ML are shown in Supplementary file 1 . The individual prediction results of the ML model are shown in Supplementary file 2 .

After a six-month follow-up, the final diagnoses were 12 ITBs and 31 CDs. The accuracy, sensitivity, specificity, PPV, and NPV were 0.860, 0.833, 0.871, 0.714, and 0.931, respectively.

The accuracy, sensitivity, specificity, PPV, and NPV of the MDT group were 0.953%, 0.917, 0.968, 0.917, and 0.968, respectively. The results of the ML model and MDT are shown in Figure 5 and Table 3 .

Results of the ML Model and MDT in Clinical Practice

	ML (N=43)	MDT (N=43)	value	Fold change (95% CI)
Accuracy	86.0% (37/43)	95.3% (41/43)	0.265	0.902 (0.787–1.035)
Sensitivity	83.3% (10/12)	91.7% (11/12)	1.000	0.909 (0.670–1.234)
Specificity	87.1% (27/31)	96.8% (30/31)	0.354	0.900 (0.755–1.046)
PPV	71.4% (10/14)	91.7% (11/12)	0.330	0.779 (0.537–1.131)
NPV	93.1% (27/29)	96.8% (30/31)	0.606	0.962 (0.855–1.083)

Abbreviations : ML, machine learning; MDT, multidisciplinary team; PPV, positive predictive value; NPV, negative predictive value.

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0006.jpg

Results of the ML model and MDT in clinical practice.

The agreement rate and kappa coefficient of the ML and MDT methods were 90.7% and 0.780, respectively (P<0.001). The confusion matrix used for calculating the kappa coefficient is shown in Figure 6 .

An external file that holds a picture, illustration, etc.
Object name is JMDH-17-3835-g0007.jpg

Confusion matrix used for calculating the kappa coefficient.

In this study, we developed an AI method to assist in the diagnosis of ITB and CD based on an ML method and a DL method with good performance. The ML explanatory methods SHAP and LIME could help doctors understand how the ML model works. The ML model \ performed well in real-world clinical practice, and the agreement between the ML model and MDT was strong.

XGBoost achieves state-of-The-art results on many ML challenges. In this study, XGBoost outperformed the other prediction models to diagnose ITB and CD. Other studies have confirmed that XGBoost performs excellently in predicting diabetes and cardiovascular disease. 21 , 22 XGBoost is a scalable end-to-end tree boosting system, a novel sparsity-aware algorithm for sparse data, and a weighted quantile sketch for approximate tree learning. In addition, it combines cache access patterns, data compression, and sharding to build a scalable tree-boosting system. 18 The diagnostic AUROC of our XGBoost model was 0.946. Another similar study with 160 CD and 40 ITB patients with 32 clinical features reported that the AUROC of the XGBoost model was 0.891 14 we speculate that this may be because our study included more ITB patients and clinical features.

ML methods revealed that the top 5 clinical features of the ML model were T-spot, pulmonary tuberculosis, age of disease onset, OB, and Terminal ileum. T-spot-positive and concomitant pulmonary tuberculosis were acknowledged features of a diagnosis of ITB. However, hematochezia is more common in patients with CD. 23 , 24 Although hematochezia is not the key feature, OB positivity is an important feature that suggests CD in our model; this is probably due to the retrospective nature of the study. When patient files are reviewed, missing symptom information is more common than missing laboratory results. A ten-year hospital-based observational study in China revealed that the onset age of CD was 32.0 years, and a study in Western Hungary reported that the onset age of CD was 32.5 years. 25 , 26 The age of onset for patients in our CD and ITB groups was 28.2 and 41.2 years, respectively. This discrepancy may be due to the fact that the number of pediatric and adolescent patients with CD is increasing, and tuberculosis is more common in elderly patients. Thus, age of onset could be an important feature of the ML model. A retrospective study of ITB patients in East China revealed that the rate of terminal ileum affected was 47.1%. 27 This result was very close to our findings. In our study, the percentage of terminal ileum affected in the ITB group (40.2%) was lower than that in the CD group (73.7%). Therefore, the terminal ileum affected may be a key variable of the ML model.

This is the first study conducted to evaluate the performance of the ML-based model for differentiating CD and ITB in MDT candidates. The results show that the ML model could differentiate between CD and ITB. However, the performance slightly decreased compared to previous retrospective clinical data; this is largely because MDT candidates are usually difficult to diagnose. An MDT meeting is recommended for patients whose diagnosis is difficult. 4 In this study, after the MDT meeting, the accuracy of diagnosis reached 95.3%. Compared with the MDT model, the agreement rates and kappa coefficients of the ML model and MDT model are strongly consistent. Therefore, the model could help doctors differentiate CD and ITB effectively, improve the accuracy of diagnosis, and improve the ability to identify ITB and CD in primary hospitals.

Our study had several limitations. First, in stage 1, the study was limited by its retrospective nature and was a secondary analysis of single-center medical data. Second, in stage 2, the sample size was small. Third, we did not conduct ablation experiments or LASSO regression to extract the variables. Finally, this study did not include all the clinical data, such as CT, double-balloon enteroscopy, and capsule endoscopy results.

In conclusion, in this study, we developed an ML model based on XGBoost. The ML model could provide effective and efficient differential diagnosis of ITB and CD with diagnostic bases. The ML model performed well in real-world clinical practice, and the agreement between the ML model and MDT was strong. The proposed model may greatly reduce the burden on doctors, relieve the suffering of patients, and improve the ability to identify ITB and CD in primary hospitals.

Acknowledgment

The authors would like to thank Mr. Ziyi Gao from the Institute of Interdisciplinary Information Science, Tsinghua University, for helpful suggestions.

Funding Statement

Hunan Provincial Innovation Foundation for Postgraduates (NO. QL20220061). Science Foundation of Changsha Central Hospital, China (YNKY202401).

Abbreviations

IBD, Inflammatory bowel disease; UC, Ulcerative colitis; CD, Crohn’s disease; ITB, Intestinal tuberculosis; AI, Artificial intelligence; ML, machine learning; KNN, K nearest neighbor; MLP, Multilayer perceptron; AUROC, Area under the receiver operating characteristic curve; PPV, Positive predictive value; NPV, Negative predictive value; SHAP, SHapley Additive exPlanations; LIME, Local interpretable model-agnostic explanations.

Data Sharing Statement

Ethics approval and consent to participate.

This study was conducted in the Gastroenterology Department of the Third Xiangya Hospital of Central South University. This research was conducted in accordance with the Declaration of Helsinki and national and institutional standards. The study protocol was approved by the clinical research ethics committee of the Third Xiangya Hospital of Central South University (No.22272). Informed consent was obtained from all the MDT candidates. The study is complete and is registered at http://www.chictr.org.cn (ChiCTR2200066847).

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

The authors declare that they have no competing interests.

Health Tech
Health Insurance
Medical Devices
Gene Therapy
Neuroscience
H5N1 Bird Flu
Health Disparities
Infectious Disease
Mental Health
Cardiovascular Disease
Chronic Disease
Alzheimer's
Coercive Care
The Obesity Revolution
The War on Recovery
Adam Feuerstein
Matthew Herper
Jennifer Adaeze Okwerekwu
Ed Silverman
CRISPR Tracker
Breakthrough Device Tracker
Generative AI Tracker
Obesity Drug Tracker
2024 STAT Summit
All Summits
STATUS List
STAT Madness
STAT Brand Studio

Don't miss out

Subscribe to STAT+ today, for the best life sciences journalism in the industry

Morning Rounds: Getting healthier in the checkout aisle and the alcohol aisle

By Brittany Trang Aug. 12, 2024

Want to stay on top of health news? Sign up to get our Morning Rounds newsletter in your inbox.

It’s Brittany subbing for Theresa this fine Monday. Thank you for all of the excellent song recommendations over the weekend. If you want to check out my road trip playlist, you can find it here .

In today’s newsletter, we introduce you to neffy, the nasal spray alternative to the EpiPen. In my mind, it looks kind of like Microsoft’s Clippy, but for allergies.

Meet neffy, the nasal spray version of the EpiPen

On Friday, the Food and Drug Administration announced it had approved the first epinephrine nasal spray for treating anaphylaxis, the sometimes life-threatening allergic reaction to things like bee stings, crab, or peanuts.

The spray, called neffy, was approved for adults and kids over 30 kg, or 66 pounds. A nasal spray was previously hard to achieve because the drug is not well absorbed through the nose, but neffy uses a compound, Intravail, that helps open up tight junctions in mucous membranes.

The nasal spray opens up a needle-free alternative to the EpiPen and may undercut it on price, too. The CEO of neffy’s manufacturer, ARS Pharmaceuticals, told STAT in September that a two-pack would not cost more than $199, and for people with insurance, coupons would drive copays down to $25 per two-pack.

Read more about the approval from STAT’s Isa Cueto, and check out her previous story on the opportunities neffy presents — including its smaller size. (If you’re on the fence, the story includes the quote “Who has the pockets for this thing? I’m not gonna wear a fanny pack, dude” re: the EpiPen.)

CDC ups bird flu alarm — but only slightly

From STAT’s Helen Branswell : The CDC issued a new risk assessment of the H5N1 bird flu virus circulating in dairy cows Friday, increasing slightly its estimate of the chance the virus poses of triggering a pandemic. But the new assessment, developed using the agency’s influenza risk assessment tool or IRAT, still gauges the risk in the lower half of the moderate rate. Previous assessments of some swine influenza viruses and of the H7N9 bird flu virus have scored higher using the IRAT risk assessment.

Vivien Dugan, director of the CDC’s influenza division, told STAT this tool was designed to help the federal government prioritize its pandemic preparedness efforts, and isn’t meant to forecast whether a given flu virus will go on to cause a pandemic. The virus analyzed in the new assessment was taken from the first human H5N1 case in the U.S. this year, a farmworker in Texas whose infection was reported at the beginning of April. The previous H5N1 risk assessment was based on a 2023 outbreak of H5N1 in mink in Spain. Read more from Helen here , and keep up with STAT’s H5N1 coverage here .

Decreasing the amount of candy in the checkout aisle

What’s your favorite candy to eye in the checkout aisle? Or are you more tempted by chips? In March 2021, Berkeley, Calif., became the first town in the world to implement a “healthy checkout policy,” which set standards for what items are allowed to be displayed in that high-engagement-time area within three feet of a checkout register.

The policy allows only beverages without sweeteners (whether calorie-free or not) and foods with five or fewer grams of added sugars and 200 or fewer milligrams of sodium per serving in the following categories: sugar-free gum and mints, fruit, vegetables, nuts, seeds, legumes, yogurt or cheese, and whole grains.

A recent study in JAMA Network Open showed that after one year, the increase in healthy food and beverage displays compared to cities without the policy went from 29% to 62%, suggesting that similar policies would be effective in increasing the healthfulness of store checkout areas.

Don’t miss a STAT First Opinion on this topic by Anne Thorndike, a Mass Gen primary care physician not involved in the study.

The fight for better alcohol risk labels

You might be surprised to learn that most alcohol products are not regulated by a health-related agency like the FDA. Instead, the Alcohol and Tobacco Tax and Trade Bureau — a section of the Department of the Treasury — is in charge of labels on alcohol. But it doesn’t have a public health charge, such as warning consumers about health risks of alcohol or mandating nutrition facts. Its main function is as a tax collection agency.

As such, the TTB hasn’t taken a huge interest in changing the fine-print warnings on alcohol bottles to something like the colorful “Alcohol can cause cancer” labels that a Canadian study showed were effective in changing consumers’ alcohol buying habits. But that may be changing soon.

STAT’s Isa Cueto takes us on a journey through consumer and public interest groups’ two-decade-long fight to get stronger warning labels on alcohol, the science supporting alcohol warning labels, and how the alcohol industry is fighting back. Read the story here .

Happy summer — watch out for rabies

Another from STAT’s Helen Branswell : Campers waking up with bats in their tents. Cattle in Minnesota succumbing to rabies, likely transmitted by skunks. A local health department warning of a rabies-infected raccoon. Seeing these kinds of stories at this time of year isn’t a surprise; the risk of being exposed to rabies increases in the summer, Ryan Wallace, rabies program lead at the CDC, told STAT. That risk extends both to people and pets, which underscores the importance of vaccinating dogs and cats. Of more than 7,000 rabid dogs and cats detected in the U.S. over the past 20 years, 99% were unvaccinated, Wallace said.

Some parts of the country are seeing an increase in rabies detections this year — skunks in Minnesota and Iowa, and gray foxes in Arizona, New Mexico, and California. Wallace said that every year about 60,000 people in the U.S. are deemed to need post-exposure rabies vaccination. The country’s effort to reduce rabies risk is massive and expensive, but has real impact. There hasn’t been a detected human case of rabies in the past 2.5 years, Wallace said. “I’m knocking on wood.”

Helping stem cells come out of their bone homes

For anyone donating stem cells for a bone marrow transplant (or becoming their own donor , as recipients of the new gene therapies for sickle cell disease and beta thalassemia do), it’s necessary to undergo stem cell collection.

However, convincing enough stem cells to exit their niches in the bone marrow and enter the bloodstream, where they can be collected, is difficult. New research in Science looking at mouse and human cells explains one way blood cells resist entering the bloodstream. The study found that cells with certain macrophage markers on their surface were better at staying in the bone marrow and that cells could use a process called trogocytosis to attach these sticky markers to themselves. However, drugs used to push stem cells out of the bone marrow help turn off trogocytosis, and this new understanding gives a new target for future drugs that might improve stem cell collection efficiency.

What we’re reading

Three MDMA therapy papers are retracted over data integrity concerns — on the heels of the FDA’s rejection of the psychedelic treatment for PTSD, STAT
Judge orders CDC to stop deleting emails of departing staff, calling it ‘likely unlawful’, Politico
This athlete’s favorite part of the Olympics? Free health care, The 19th
Why Trump’s mifepristone comments were a gift to the Harris campaign, STAT
In South Africa, long Covid is an afterthought to tuberculosis, The Sick Times
Is COVID endemic yet? Yep, says the CDC. Here’s what that means, NPR

About the Author Reprints

Brittany trang.

Health Tech Reporter

Brittany Trang, Ph.D., is a health tech reporter at STAT. Follow her on Threads , Mastodon , and Bluesky .

chronic disease

infectious disease

public health

STAT encourages you to share your voice. We welcome your commentary, criticism, and expertise on our subscriber-only platform, STAT+ Connect

To submit a correction request, please visit our Contact Us page .

Morning Rounds: The billionaire who wants you angry about the food supply

Morning Rounds: Another Ebola outbreak?

STAT Plus: Health Care's Colossus: How UnitedHealth turned a questionable artery-screening program into a gold mine

STAT Plus: Health Care's Colossus: How UnitedHealth harnesses its physician empire to squeeze profits out of patients

STAT Plus: The race to build better CRISPR delivery vehicles is heating up

IMAGES

SOLUTION: Tuberculosis Case Study Presentation
case study in tuberculosis
Pulmonary Tuberculosis Case Study Presentation Example
Pulmonary Tuberculosis Case Study Presentation Example
SOLUTION: Tuberculosis case presentation
Tuberculosis- Study of illness condition

COMMENTS

Verification of Diagnosis in Tuberculosis: A Case Report and Discussion
Introduction. Tuberculosis (TB) is caused by strains of Mycobacterium tuberculosis (M. Tuberculosis). TB is a primarily pulmonary infection spread by airborne droplet transmission. The development and spread of drug-resistant strains of M. tuberculosis greatly jeopardize TB control efforts. In the US, 91 cases of MDR-TB were reported in 2014.
Tuberculosis
Read chapter 34 of Infectious Diseases: A Case Study Approach online now, exclusively on AccessPharmacy. AccessPharmacy is a subscription-based resource from McGraw Hill that features trusted pharmacy content from the best minds in the field. ... Tuberculosis. In: Cho JC. Cho J.C.(Ed.), Ed. Jonathan C. Cho. eds. Infectious Diseases: A Case ...
A case-report of a pulmonary tuberculosis with lymphadenopathy
Clinical and radiological manifestations of tuberculosis (TB) are heterogeneous, and differential diagnosis can include both benign and malignant diseases (e.g., sarcoidosis, metastatic diseases, and lymphoma). Diagnostic dilemmas can delay appropriate therapy, favoring Mycobacterium tuberculosis transmission.We report on a case of TB in an immunocompetent, Somalian 22-year-old boy admitted in ...
TB Case Study Example
Case Study. A 44-year-old man presented to the TB Clinic with symptoms of progressive shortness of breath and cough with greenish sputum production. His sputum test results showed that he had atypical TB ( Mycobacterium Avium Complex MAC infection ). He was HIV negative at this time. Past history revealed that he was in good health till 1991 ...
Community-based active case-finding interventions for tuberculosis: a
We systematically reviewed the literature for studies that reported the effects of active case-finding interventions on tuberculosis epidemiological indicators. Our literature search was an update of a 2013 systematic review by Kranzer and colleagues, 3 which covered the period between Jan 1, 1980, and Oct 13, 2010, with additional searches by ...
A case report of persistent drug-sensitive pulmonary tuberculosis after
Background Mycobacterium tuberculosis (Mtb) has been found to persist within cavities in patients who have completed their anti-tuberculosis therapy. The clinical implications of Mtb persistence after therapy include recurrence of disease and destructive changes within the lungs. Data on residual changes in patients who completed anti-tuberculosis therapy are scarce. This case highlights the ...
Treatment of Highly Drug-Resistant Pulmonary Tuberculosis
Patients with highly drug-resistant forms of tuberculosis have limited treatment options and historically have had poor outcomes. In an open-label, single-group study in which follow-up is ongoing ...
Tuberculosis in older adults: case studies from four countries with
The Western Pacific Region has one of the fastest-growing populations of older adults (≥ 65 years) globally, among whom tuberculosis (TB) poses a particular concern. This study reports country case studies from China, Japan, the Republic of Korea, and Singapore reflecting on their experiences in managing TB among older adults.
Living with tuberculosis: a qualitative study of patients' experiences
Although tuberculosis (TB) is a curable disease, treatment is complex and prolonged, requiring considerable commitment from patients. This study aimed to understand the common perspectives of TB patients across Brazil, Russia, India, China, and South Africa throughout their disease journey, including the emotional, psychological, and practical challenges that patients and their families face.
PDF Self-Study Modules On Tuberculosis Module 1: Transmission and
Mo1ransmission and Pathogenesis of Tuberculosis 5 Lorem ipsum. 1. MODULE. D History of TB . Tuberculosis — a disease also historically known as consumption, wasting disease, and the white plague — has afected humans for centuries. Until the mid-1800s, people thought that tuberculosis, or TB, was hereditary or attributable to an unhealthy life.
Covid-19's Devastating Effect on Tuberculosis Care
Ensuring Continuity of Tuberculosis Care during Social Distancing through Integrated Active Case Finding at COVID-19 Vaccination Events in Vietnam: A Cohort Study, Tropical Medicine and Infectious ...
Tuberculosis active case-finding: looking for cases in all the right
report findings of a systematic review summarising the evidence for population-level effectiveness of active case-finding for tuberculosis. The authors appraised 36 studies published between Jan 1, 1980, and April 13, 2020, of adult populations from 16 countries that were exposed to different active case-finding interventions.
Community-based active case-finding interventions for tuberculosis: a
Studies of active case-finding in the general population, in populations perceived to be at high risk for tuberculosis, and in closed settings were included, whereas studies of tuberculosis screening at health-care facilities, among household contacts, or among children only, and studies that screened fewer than 1000 people were excluded.
A case study of a patient with multidrug-resistant tuberculosis
Abstract. In this case study, a nurse presents her reflections on the challenges of supporting a patient through his treatment journey for multidrug-resistant tuberculosis. The patient has significant comorbidities and social issues, such as diabetes and homelessness. There was also a language barrier. All these aspects made the management of ...
(PDF) CASE STUDY ON PULMONARY TUBERCULOSIS
case study on pulmonary tubercul osis Vedha Pal Jeyamani.S 1 , Angel.P 1 , Bhavya.E 1 , Balaji.P 1 , Muruga n.M 2 1 Department of Pharmacology , Ja ya College of Pharmacy, Chennai, T amilnadu, India
PDF Case Studies in Tuberculosis
Case Studies in Tuberculosis: Training in Nurse Case Management. Introduction Dear Healthcare Professional, Prior to reviewing the content of this book, it is highly recommended that you complete the Centers for Disease Control and Prevention (CDC) Self-Study Modules on Tuberculosis (TB). The modules contain
Personal Stories from TB Survivors
Personal Stories from TB Survivors - My Journey fighting TB. 3 June 2020. Tuberculosis (TB) is the world's top infectious killer today. It is airborne and can affect any one of us. Over 5 000 women, men and children still die each day from TB. The social and economic impacts are devastating, including poverty, stigma and discrimination.
Tuberculosis in older adults: case studies from four countries with
The Western Pacific Region has one of the fastest-growing populations of older adults (≥ 65 years) globally, among whom tuberculosis (TB) poses a particular concern. This study reports country case studies from China, Japan, the Republic of Korea, and Singapore reflecting on their experiences in managing TB among older adults. Across all four countries, TB case notification and incidence ...
Severe Pleural Tuberculosis: a Case Report and Management ...
INTRODUCTION: Tuberculosis (TB) is a highly infectious disease caused by Mycobacterium tuberculosis (MTB) that primarily affects the respiratory system. It is the second leading cause of infectious disease-related deaths. In the US, there were 7,882 cases of active TB in 2021. Pleural tuberculosis, a complication of active TB that can be life ...
Case Report: Pulmonary tuberculosis and...
Tuberculosis is the biggest infectious disease killer in the world 1, and is endemic in Nepal with the national prevalence at 416 cases per 100000 population 2. Pulmonary tuberculosis is the most common form. In Nepal, tuberculosis prevalence is more in productive age group (25-64 years) and men. Poverty, malnutrition, overcrowding ...
Two Cases of Pulmonary Tuberculosis Caused by Mycobacterium
The Mycobacterium tuberculosis complex includes the following mycobacteria, which are characterized by a slow growing rate: M. tuberculosis, M. africanum, M. bovis, and M. microti ().In recently published reports of two cases of lymphatic node tuberculosis (TB), the strains were recognized as belonging to a new taxon of M. tuberculosis (2,3).These isolates were characterized by a highly ...
Case-based TB surveillance
Digital, case-based, real-time surveillance for TB: status of progress. Tuberculosis (TB) surveillance is the continuous and systematic collection, analysis and reporting of data related to TB infection and TB disease in the population. To support countries to implement national surveillance systems for TB in a consistent and comparable way ...
Lesson 3 Case Study
CASE STUDY. Now that you have learned how people are tested for TB, apply your knowledge with the following case study. ...
A study on factors influencing delayed sputum conversion in ...
A retrospective study of sputum conversion in sputum positive 1782 pulmonary tuberculosis (PTB) was conducted from 2021 to 2022 in Beijing, China. ... China. We also designed a case-matched study ...
Prevalence, incidence, and case fatality of tuberculous meningitis in
Tuberculous meningitis (TBM) emerges as a grave complication of tuberculosis in people living with HIV (PLWH). The diagnosis and treatment of TBM pose significant challenges, leading to elevated mortality rates. ... Case fatality. Twelve studies reported on the case fatality of patients with TBM. The combined ER was 38.1% (95% CI: 24.3-54.1%
Proportion of active tuberculosis among HIV-infected children after
Previous national level study finding among 1,830,880 HIV and 192,359 TB patients reported,7.34% of TB patient had HIV ... The search terms used to identify relevant studies included "Epidemiology" OR "Incidence" OR "Case fatality" "Tuberculosis" OR "Pulmonary Tuberculosis" OR "Disseminated Tuberculosis" OR "Lymphadenitis" AND "HIV" OR "AIDS ...
Confirmed Case of Autochthonous Human Babesiosis, Hungary
Since the first description of human babesiosis caused by Babesia divergens protozoa in 1956 in the former Yugoslavia, 2 other zoonotic species, B.venatorum and B.microti, have been isolated in Europe.Unlike in North America, where most identified human cases have been caused by B. microti, the predominent pathogen causing babesiosis in Europe is B. divergens ().
Multiple liver, splenic and psoas abscesses due to melioidosis: A case
We report a case of melioidosis presenting with multiple liver, spleen, and psoas abscesses. Case presentation A 50-year-old male manual labourer from Sri Lanka, with a history of diabetes mellitus presented with a history of the left hip and back pain for a 1-month duration associated with on and off mild fever, generalized malaise and loss of ...
A Machine Learning Method for Differentiation Crohn's Disease and
Tuberculosis is the second leading cause of death caused by an infectious disease after COVID-19, contributing to 1.5 million deaths in 2020. ... shows how the SHAP method explains our ML models. As shown in Figure 3A, each point represents a case. ITB and CD were coded as 0 and 1, respectively in our ML experiment. ... Other studies have ...
Getting healthier in the checkout aisle and the alcohol aisle
There hasn't been a detected human case of rabies in the past 2.5 years, Wallace said. ... The study found that cells with certain macrophage markers on their surface were better at staying in ...

34: Tuberculosis

Jump to a Section

Chief Complaint

History of Present Illness

Past Medical History

Surgical History

Family History

Social History

Home Medications

Physical Examination

Cardiovascular

Genitourinary

A case report of persistent drug-sensitive pulmonary tuberculosis after treatment completion

Case presentation

Conclusions

Discussion and conclusions

Availability of data and materials

Abbreviations

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Consent for publication

Competing interests

Additional information

Rights and permissions

About this article

Share this article

BMC Infectious Diseases

Save citation to file

Add to My Bibliography

A case study of a patient with multidrug-resistant tuberculosis

Similar articles

Related information

CASE STUDY ON PULMONARY TUBERCULOSIS

Section navigation

Digital, case-based, real-time surveillance for TB: status of progress

Fig. 1 Countries with national, case-based digital surveillance systems for TB, 2020

Fig. 2 Global status of implementation and use of the WHO TB DHIS2 packages for health facility and case-based data, 2017–2020

Fig. 3 An illustration of a unified, digital environment for TB surveillance, along the pathway of care

A study on factors influencing delayed sputum conversion in newly diagnosed pulmonary tuberculosis based on bacteriology and genomics

Similar content being viewed by others

Targeted next-generation sequencing of sputum for diagnosis of drug-resistant TB: results of a national survey in Democratic Republic of the Congo

Sputum culture reversion in longer treatments with bedaquiline, delamanid, and repurposed drugs for drug-resistant tuberculosis

Prevalence and factors associated with multidrug-resistant tuberculosis in South India

Study design and ethics statement

Bacteria subculture, species identification and DST

WGS and analysis

Statistical analysis

Statistics on sputum conversion at the end of ATT of 1782 PTB

Basic description of the study population

Delayed sputum conversion patients present more extensive and complex drug resistance

Changes of drug resistance among delayed sputum conversion patients after ATT

Genomic changes in series clinical isolates from delayed sputum conversion patients

Data availability

Author information

Authors and Affiliations

Contributions

Corresponding authors

Ethics declarations

Additional information

Supplementary Information

About this article

Share this article

Quick links

Prevalence, incidence, and case fatality of tuberculous meningitis in adults living with HIV: a systematic review and meta-analysis

Conclusions

Trial registration

Search strategy

Selection criteria

Data extraction

Statistical analysis

Quality assessment

Meta regression

Search results

Study characteristics

Meta-analysis of prevalence, incidence and case fatality of TBM

Case fatality

Meta-regression