The Role of Youths in Within-Household Tuberculosis Transmission

Who

• Participants:

  • Index patients: 2,771 individuals aged 15–60 years with microbiologically confirmed pulmonary TB.

  • Household contacts (HHCs): 10,745 contacts aged 0–60 years (participants >60 excluded).

• Key subgroups:

  • Index patients categorized as Youth (15–24 years) or Adults (25–60 years).

  • HHCs categorized as Children (0–14 years), Youth (15–24 years), and Adults (25–60 years).

---

What

• Main findings:

  • Child household contacts exposed to youth index patients had a lower prevalence of TB infection at enrollment compared with those exposed to adult index patients (adjusted PRR = 0.77; 95% CI: 0.67–0.87).

  • Index patient age was not associated with the incidence of TB infection among household contacts over 12 months.

  • Children and youth contacts had significantly lower incidence of TB infection than adult contacts, regardless of index patient age.

  • Whole-genome sequencing (WGS) showed a lower proportion of genetically linked transmission pairs for youth index patients compared with adults, though this difference was not statistically significant.

• Interpretation:

  • Youths appear to contribute less to within-household TB transmission than adults, suggesting that their transmission risk may occur more often outside the household.

---

When

• Study period: September 2009 to August 2012.

• Follow-up duration: 12 months after household enrollment.

---

Where

• Setting: Lima, Peru.

• Healthcare context: 106 public health centers serving approximately 3 million people.

---

Why

• To determine whether the age of TB index patients, particularly youth (15–24 years), influences the risk of TB transmission to household contacts, with a focus on children as a marker of recent transmission.

• To address gaps in understanding age-specific transmission dynamics and inform targeted TB control strategies.

---

How

• Study design: Prospective household cohort study.

• TB infection assessment:

  • Baseline tuberculin skin test (TST) to measure prevalence.

  • Repeat TSTs at 6 and 12 months to measure incidence.

• TB disease classification:

  • Co-prevalent TB (≤14 days after enrollment) vs secondary TB (>14 days).

• Transmission confirmation:

  • Whole-genome sequencing of Mycobacterium tuberculosis isolates to assess genetic linkage between index and secondary cases.

• Analysis:

• Multivariable regression and survival analyses adjusting for demographic, behavioral, socioeconomic, and nutritional factors.

Source: Brooks, M.B., Lecca, L., Becerra, M.C., Calderon, R.I., Contreras, C.C., Jimenez, J., Yataco, R.M., Zhang, Z., Murray, M.B. and Huang, C.C., 2025. The Role of Youths in Within-Household Tuberculosis Transmission: A Household Contact Cohort Study. Clinical Infectious Diseases, p.ciaf490.

Microbiological aspects and clinical impact of lower lung field TB in Peru

Who

• Participants: Individuals aged ≥14 years with newly diagnosed, microbiologically confirmed pulmonary tuberculosis (PTB).

• Sample size: 1,316 patients with abnormal baseline chest X-rays (CXRs); 84 (6%) had lower lung field (LLF) TB and 1,232 (94%) had non-LLF TB.

• Key characteristics: LLF TB patients were more likely to be women, have BMI >25 kg/m², be sputum smear–negative, have lower baseline St. George’s Respiratory Questionnaire (SGRQ) scores, and be infected with Mycobacterium tuberculosis (MTB) Lineage 2.

What

• Focus: The association between microbiological characteristics (sputum smear and culture status, MTB lineage) and radiographic localization of TB (LLF vs non-LLF), and the impact of LLF disease on treatment response and outcomes.

• Main findings:

  • LLF TB was independently associated with sputum smear negativity and infection with MTB Lineage 2.

  • Patients with LLF TB showed significantly less improvement in SGRQ scores after 2 months of treatment compared with non-LLF TB patients.

  • Final treatment outcomes appeared better in LLF TB but were not statistically significant after adjustment.

• Implications: LLF TB may be underdiagnosed using conventional sputum-based tests and is associated with slower early clinical improvement, suggesting a risk of ongoing transmission and the need for improved diagnostic strategies.

When

• Study period: October 2020 to December 2022.

Where

• Setting: Primary care health centers across 16 districts in Lima, Peru, including urban, peri-urban, and informal shantytown areas.

Why

• Rationale: Lower lung field TB can be difficult to detect with routine diagnostic approaches and may differ biologically and clinically from typical upper-lung TB. The study aimed to clarify microbiological correlates of LLF TB and assess whether LLF localization affects treatment response and outcomes.

How

• Design: Prospective cohort study.

• Diagnostics: Microbiological confirmation by GeneXpert MTB/RIF and/or sputum culture; drug susceptibility testing per WHO definitions.

• Radiography: Baseline and 2-month posteroanterior CXRs classified as LLF or non-LLF TB by radiologists.

• Molecular methods: Whole-genome sequencing of culture-positive isolates; MTB lineage determined using a 62-SNP barcode.

• Outcomes: Treatment response assessed by change in SGRQ score from baseline to 2 months; end-of-treatment outcomes classified by WHO criteria.

• Analysis: Multivariable regression adjusting for demographic and clinical covariates.

Source: Tan, Q., Huang, C.C., Calderon, R., Lecca, L., Mendoza, M., Rocha, G.R., Tintaya, K., Tovar, X., Feng, J.Y., Pan, S.W. and Tseng, Y.H., 2025. Microbiological aspects and clinical impact of lower lung field tuberculosis: An observational cohort study in Peru. International Journal of Infectious Diseases, 150, p.107284.

The social determinants of tuberculosis in Peru

---

Who

• Cases: 2,337 individuals aged ≥15 years diagnosed with pulmonary or extrapulmonary tuberculosis (with or without bacteriological confirmation). Median age 31 years (IQR 23–47); 64% male.

• Controls: 981 individuals aged ≥15 years from randomly selected households in the same communities. Median age 38 years (IQR 25–54); 40% male.

• Setting population: Residents of 32 high–tuberculosis-burden communities (~900,000 people).

• Healthcare context: Communities served by Ministry of Health (MINSA)-run health posts.

---

What

• The study examined how household-level poverty and interrelated personal risk factors (e.g., smoking, alcohol use, undernutrition, education, incarceration, social capital) increase the risk of tuberculosis.

• Key findings:

  • Household poverty was strongly associated with tuberculosis (adjusted odds ratio [aOR] 3.1 for poorer vs. less poor households).

  • Tuberculosis risk increased non-linearly with worsening poverty; 21% of cases were in the poorest poverty decile.

  • Population attributable fractions (PAFs) suggested that nearly 47% of tuberculosis burden could be reduced if poorer households achieved poverty levels comparable to the less poor.

  • Several personal risk factors independently contributed to tuberculosis risk even after adjusting for poverty, including low education, alcohol excess, underweight, smoking, HIV, diabetes, prior tuberculosis, incarceration, and low social capital.

  • Most personal risk factors showed clear social gradients, being more prevalent among poorer households, except HIV (no gradient) and diabetes/other immunosuppression (more prevalent in less poor households).

---

When

• Communities were followed from 2013 onward.

• Recruitment and detailed data collection occurred during the study period up to 2019.

• Tuberculosis notification data refer to 2019.

---

Where

• Callao, Peru, a metropolitan area bordering Lima.

• Specifically, 32 of 45 communities in Callao with high tuberculosis rates.

---

Why

• To address gaps in understanding how household poverty and downstream personal risk factors interact to shape tuberculosis risk.

• The study aimed to move beyond single risk factors and explicitly apply a social epidemiological framework to tuberculosis transmission and vulnerability.

---

How

• Study design: Case–control study nested within the PREVENT TB study.

• Case identification: Passive case finding through MINSA-run health posts; cases recruited at diagnosis or during treatment.

• Control selection: Randomly selected households using satellite mapping and random number tables; all household members invited after adult consent.

• Data collection: Structured questionnaires administered by trained research nurses.

  • Household poverty assessed across physical, human, and financial capital dimensions using the Sustainable Livelihood Framework and principal component analysis (PCA).

  • Personal risk factors grouped into five domains: education/behavioural, exposure, biological, nutritional, and psychosocial.

• Analysis: Directed acyclic graphs (DAGs) guided causal assumptions; multivariable regression estimated adjusted odds ratios and population attributable fractions.

Source: Saunders, M.J., Montoya, R., Quevedo, L., Ramos, E., Datta, S. and Evans, C.A., 2025. The social determinants of tuberculosis: a case-control study characterising pathways to equitable intervention in Peru. Infectious diseases of poverty, 14(1), p.53.

Factors Influencing Adherence to Anti-tuberculosis Treatment

Who

The study involved patients with pulmonary tuberculosis receiving treatment at Puskesmas Nibung. The population consisted of 97 patients treated in 2023. The study sample included 35 pulmonary tuberculosis patients in 2024 who had been diagnosed with tuberculosis and had undergone treatment for at least two months.

What

The study examined medication adherence to anti-tuberculosis treatment and identified factors associated with adherence. The results showed that 57.1% of respondents were adherent to their medication. Multivariate analysis revealed that gender was the most dominant factor associated with medication adherence. Statistically significant relationships were found between medication adherence and gender, education level, knowledge, employment status, family support, and attitude.

When

Data collection was conducted from March 3 to May 12, 2024.

Where

The study was conducted at the Nibung Community Health Center (UPTD Puskesmas Nibung), North Musi Rawas Regency, Indonesia.

Why

The study was conducted to address the need for understanding medication adherence among pulmonary tuberculosis patients and to identify key factors influencing adherence to anti-tuberculosis treatment.

How

A quantitative analytic survey with a cross-sectional design was used. Total sampling based on inclusion criteria was applied. Data were analyzed using univariate and multivariate analyses to determine factors associated with medication adherence.

Source: Fitri, V.K., Zaman, C., Priyanto, A.D. and Ekawati, D., 2025. Analysis Factor of Compliance With Taking Anti-Pulmonary Tuberculosis Drugs in Patients With Pulmonary Tuberculosis. Lentera Perawat, 6(1), pp.59-68.

Occurence and risk factors of TB infection in orphanage children in Bali

Who

• Participants: Children residing in orphanages

• Sample size: 175 children initially screened; 172 included in analysis

• Age: <18 years (median age 15 years; only 1 child <5 years)

• Sex: Case group: 46.1% male, 53.1% female

• Exclusions: Children with prior TB infection or TB treatment

---

What

• Focus: Prevalence (occurrence) and risk factors of tuberculosis (TB) infection among orphanage children

• Findings:

  • 49 children (28.0%) had positive tuberculin test results and were classified as TB infection cases

  • No child had clinically confirmed TB disease

  • Environmental factors were strongly associated with TB infection

• Conclusions:

  • TB infection among orphanage children in Bali is high

  • Poor ventilation and indoor humidity are the main independent risk factors

• Implications:

  • Improving indoor environmental conditions in orphanages is critical for TB prevention

---

When

• Study period: March to August 2022

---

Where

• Setting: 12 orphanages in Bali, Indonesia

---

Why

• There is a lack of accurate data on TB infection prevalence among orphanage children in Indonesia

• TB burden in orphanages, especially in Bali, is poorly understood despite high vulnerability

• Accurate screening is needed to prevent TB transmission, morbidity, and mortality

---

How

• Study design: Observational-analytic case–control study

• Sampling: Consecutive sampling

• TB assessment:

  • TB scoring system (clinical signs, history, and chest X-ray)

  • Tuberculin skin test (≥10 mm induration = positive)

• Measurements:

  • Demographics, nutrition (BMI-for-age, height-for-age using World Health Organization standards), TB contact history, BCG status

  • Environmental factors: room density, ventilation/room area ratio, humidity, lighting

• Analysis:

  • Bivariate and multivariate analysis of risk factors

• Key independent risk factors:

• Ventilation/room area ratio <10% (OR 2.7; p=0.011)

• Indoor humidity ≥73% (OR 3.9; p=0.001)

Source: Clearesta, K.E., Mayangsari, A.S.M., Wati, D.K., Purniti, N.P.S., Suwarba, I.G.N.M. and Artana, I.W.D., 2024. Occurence and risk factors of tuberculosis infection in orphanage children in Bali. Paediatrica Indonesiana, 64(2), pp.152-9.

Safety of pyrazinamide in elderly patients with TB in Japan

Who

• Participants: Hospitalized patients with tuberculosis (TB) in Japan

• Sample size:

  • 69,474 TB hospitalizations identified

  • 19,930 patients met inclusion criteria

  • 3,578 propensity score–matched pairs (7,156 patients)

• Age: Mean age ≈ 80 years after matching; subgroup analyses for ≥75 vs <75 years

• Key exclusions: Patients <15 years, pregnant patients, early deaths/discharges (≤2 days), and those not started on standard TB therapy promptly

---

What

• Main finding: Adding pyrazinamide (PZA) to the initial TB regimen was not associated with increased in-hospital mortality in elderly patients.

• Adverse events:

  • Overall adverse events were more frequent with PZA-containing regimens, driven mainly by allergic reactions.

  • No significant differences in hepatotoxicity, gout attacks, gastrointestinal intolerance, length of hospital stay, or 90-day readmission.

• Conclusion: Advanced age alone should not be a reason to avoid PZA in TB treatment, though clinicians should monitor for allergic reactions.

---

When

• Study period: July 2010 to March 2022

---

Where

• Setting: Nationwide inpatient acute-care hospitals across Japan

• Context: Japanese policy mandates hospitalization for sputum smear–positive TB until smear conversion

---

Why

• Rationale:

  • PZA is often avoided in elderly TB patients due to safety concerns.

  • Existing evidence was limited to small studies with poor generalizability.

  • This study aimed to provide robust, nationwide evidence on the safety of PZA in older adults with TB.

---

How

• Design: Retrospective nationwide cohort study

• Data source: Japanese Diagnosis Procedure Combination inpatient database

• Exposure groups:

  • HRE (isoniazid, rifampicin, ethambutol)

  • HREZ (isoniazid, rifampicin, ethambutol, pyrazinamide)

• Analysis:

• Propensity score matching to balance baseline characteristics

• Primary outcomes: in-hospital mortality and composite adverse events

• Secondary outcomes: length of stay, readmission, and medication use for complications

• Sensitivity analyses stratified by age (≥75 vs <75 years)

Source: Taniguchi, J., Jo, T., Aso, S., Matsui, H., Fushimi, K. and Yasunaga, H., 2024. Safety of pyrazinamide in elderly patients with tuberculosis in Japan: A nationwide cohort study. Respirology, 29(10), pp.905-913.

Stool-based Xpert test on childhood tuberculosis diagnosis in Nigeria

Who

• Population: Children aged 0–14 years presumed to have tuberculosis (TB).

• Sample size: 52,117 children who submitted stool specimens and 391,217 children who submitted sputum specimens.

• Setting: 1082 health facilities (11 tertiary, 126 secondary, 945 primary).

• Key demographics:

  • Stool testing: 59.7% aged 0–4 years; 40.3% aged 5–14 years

  • Higher referral and diagnosis among males, especially in the 0–4 age group

  • Drug-resistant TB (DR-TB) proportion higher in the 5–14 age group

---

What

• Focus: Evaluation of the impact of stool-based Xpert MTB/RIF testing on childhood TB diagnosis.

• Key findings:

  • Stool-based Xpert testing diagnosed 4.8% of evaluated stool samples with TB.

  • Approximately 1.1% of stool-diagnosed TB cases were drug-resistant.

  • 94.6% of stool-diagnosed TB cases were initiated on treatment.

  • Stool testing contributed up to 17% of all bacteriologically confirmed childhood TB cases in 2022–2023.

• Conclusion: Decentralized stool-based Xpert testing significantly improved childhood TB detection and notification, particularly among younger children and at lower healthcare levels.

---

When

• Implementation period:

  • Method modification and verification: Q3 2020

  • Nationwide implementation: Q4 2020 onward

  • Major awareness scale-up: Q3 2022

• Trend observation: Increased TB detection over time, except during the 2020 COVID-19 period.

---

Where

• Country: Nigeria

• Geographic coverage: 14 states (Anambra, Imo, Delta, Akwa Ibom, Rivers, Cross River, Nasarawa, Benue, Plateau, Taraba, Kano, Kaduna, Katsina, Bauchi).

• Program context: States supported by the USAID-funded TB Local Organization Network (LON) 1 & 2 project implemented by KNCV Nigeria.

---

Why

• Childhood TB in Nigeria has historically low bacteriological confirmation rates due to difficulty obtaining sputum samples from children.

• A 2020 national stakeholder meeting identified the need to decentralize stool-based testing to peripheral health facilities where most children seek care.

• The goal was to improve access, reduce diagnostic delays, lower costs, and increase TB case notification among children.

---

How

• Study design: Cross-sectional analysis of secondary programmatic data.

• Eligibility: Children <15 years with TB symptoms who could not produce sputum were offered stool testing.

• Laboratory method:

  • Modified one-step stool-based Xpert MTB/RIF Ultra method

  • Hard-formed stool emulsified with saline, incubated, treated with sample reagent, filtered, and processed on GeneXpert

• Implementation strategies:

  • Revision of national TB guidelines and laboratory SOPs

  • Nationwide webinars and training of laboratory staff

  • Dissemination of instructional YouTube videos

  • Continuous awareness creation and capacity building

• Outcome definition: TB diagnosis based on positive GeneXpert results; both bacteriologically confirmed and clinically diagnosed cases were treated.

Source: Nwokoye, N., Odume, B., Nwadike, P., Anaedobe, I., Mangoro, Z., Umoren, M., Ogbudebe, C., Chukwuogo, O., Useni, S., Nongo, D. and Eneogu, R., 2024. Impact of the stool-based Xpert test on childhood tuberculosis diagnosis in selected states in Nigeria. Tropical Medicine and Infectious Disease, 9(5), p.100.

The LTBI survey using 2 IGRA tests among the elderly in Eastern China

Who

• Study population: 1,583 elderly individuals aged ≥65 years

• Setting: Community-dwelling older adults attending routine health check-ups

• Subgroup for agreement analysis: 108 participants aged ≥65 years

• Sex distribution: Male-to-female ratio ≈ 0.95:1 in the main study

---

What

• Primary outcomes:

  • The prevalence of latent tuberculosis infection (LTBI) among elderly adults was 26.78%.

  • Risk factors positively associated with LTBI included:

    • Male sex (Adjusted OR = 1.64; 95% CI: 1.25–2.15)

    • Former smoking (Adjusted OR = 1.42; 95% CI: 1.01–2.01)

    • Exercising at least once per week (Adjusted OR = 2.21; 95% CI: 1.03–4.75)

• Diagnostic agreement findings:

  • The domestic AIMTB Rapid Test Assay showed high agreement with QFT-Plus:

    • Overall agreement: 92.59%

    • AUC for AIMTB: 0.952

    • Optimal AIMTB cutoff: 24.02 pg/mL IFN-γ

• Authors’ conclusion: LTBI burden among the elderly is substantial and warrants targeted screening. AIMTB demonstrates strong diagnostic performance and may reduce screening costs in high-TB-burden, resource-limited settings.

---

When

• Data collection period: Not specified

• Conducted during recent years following implementation of the Tuberculosis-Free Community project.

---

Where

• Location: Lanxi City

• Region: Central Zhejiang Province (Jinhua area), China

• Context: Rural/suburban setting with high pulmonary TB notification rates among the elderly

---

Why

• To address the high burden of TB and LTBI in older adults in aging populations.

• To identify factors associated with LTBI in the elderly.

• To evaluate agreement between a domestic LTBI assay (AIMTB) and a conventional interferon-gamma release assay (IGRA), supporting scalable screening strategies in developing countries.

---

How

• Study design: Community-based cross-sectional study with an embedded diagnostic agreement analysis

• Sampling: Random selection of two subdistricts; daily recruitment of eligible elderly residents

• Sample size: Calculated minimum 1,261; final enrollment 1,583

• Data collection:

  • Structured questionnaire (demographics, BMI, smoking, alcohol use, exercise, diabetes)

  • LTBI testing using:

    • QFT-Plus

    • AIMTB Rapid Test Assay

• Statistical analysis:

• Multivariable logistic regression for risk factors

• Agreement analysis (kappa, correlation, Bland–Altman)

• ROC curve to optimize AIMTB cutoff values

Source: Jiang, X., Feng, Y., Yu, Z., Chen, B., Wang, W., Jiang, G., Hu, L., Tong, W., Chen, Q., Zhang, M. and Zhu, Y., 2025. The latent tuberculosis infection survey using two interferon γ release assay tests among the elderly in a well-confined rural county in Eastern China. BMC geriatrics, 25(1), p.1035.

Treatment success and associated factors among drug-susceptible TB patients

Who

• Study population: Individuals diagnosed with drug-susceptible tuberculosis (TB) and initiated on TB treatment.

• Sample size: 1,009 individuals included in final analysis (from 1,062 records).

• Demographics:

  • Median age: 45 years (IQR 28–60)

  • 9.5% <15 years; 48.1% aged 15–49 years

  • 52.9% male

  • 30.9% HIV-positive

• Exclusions: Individuals with incomplete key data, unknown HIV status, or rifampicin-resistant TB.

---

What

• Focus: Determination of TB treatment success rate (TSR) and factors associated with treatment success among drug-susceptible TB patients.

• Key findings:

  • Overall TSR was 91.9% (95% CI: 90.0–93.4%), exceeding prior regional estimates and aligning with the national target.

  • Treatment success comprised 47.4% treatment completion and 44.5% cure.

  • Unsuccessful outcomes included death (5.1%), lost to follow-up (0.3%), and not evaluated (2.8%).

• Associated factors: Older age (>49 years), male sex, and HIV positivity were associated with lower treatment success.

• Implications: Despite a historically lower TSR in the Teso region, current outcomes are strong; however, targeted interventions are needed for older adults, males, and people living with HIV to sustain progress toward the End TB Strategy by 2030.

---

When

• TB treatment period reviewed: 1 October 2021 – 30 December 2023

• Data collection period: 1 March 2025 – 28 March 2025

---

Where

• Setting: Five large public health facilities in the Teso region, Northeastern Uganda.

• Districts: Kumi, Serere, Bukedea, and Ngora

• Facilities: Atutur Hospital, Kumi HC IV, Serere HC IV, Bukedea HC IV, and Ngora HC IV

• Context: Predominantly rural population with subsistence farming livelihoods and low HIV prevalence relative to the national average.

---

Why

• The Teso region has a high TB burden but historically suboptimal TSR compared to national averages.

• Understanding drivers of treatment success and failure in rural, resource-limited settings is essential for designing targeted interventions and achieving global TB elimination goals.

---

How

• Study design: Retrospective quantitative study.

• Data source: TB treatment registers from selected health facilities.

• Outcome definition:

  • Treatment success: Cure + treatment completion (WHO criteria).

  • Unsuccessful outcomes: Death, loss to follow-up, treatment failure, or not evaluated.

• Independent variables: Age, sex, HIV status, TB classification, treatment category, referral source, GeneXpert access, and nutritional status (MUAC).

• Analysis:

• Bivariate analysis for associations.

• Modified Poisson regression with robust standard errors to estimate adjusted prevalence ratios (aPR), chosen due to outcome prevalence >10%.

Source: Ssentongo, S.M., Oryokot, B., Opito, R., Ochieng, G., Sekiranda, P., Bakashaba, B. and Mugisha, K., 2025. Treatment success and associated factors among drug-susceptible tuberculosis patients in Teso region, Uganda: a retrospective study. Therapeutic Advances in Infectious Disease, 12, pp.1-12.

A Clinical Prediction Model for Atypical TB Manifestations Among Older Adults

Who

• Population: Older adults aged ≥75 years

• Sample size: 5,651 patients with culture-confirmed pulmonary tuberculosis (aPTB) and atypical symptom presentation

• Subgroups:

  • Group a (Ga): 1,155 patients with aPTB not initially suspected by non-pulmonologists

  • Group b (Gb): 4,496 non-TB comparators within the first 24 hours

• Setting of care: Evaluated initially by non-chest physicians

• Radiology review: 2 radiologists + 1 pulmonologist (blinded)

---

What

• Objective: Development and validation of a TRIPOD-compliant clinical prediction score to identify atypical pulmonary TB (aPTB) in late-elderly patients.

• Key findings:

  • Five independent predictors of delayed aPTB diagnosis were identified:

    1. Age >85 years (strongest predictor)

    2. Hypoalbuminemia (<3.5 g/dL)

    3. Cardiovascular disease

    4. Diabetes mellitus

    5. Predominant lower-lung field involvement

  • A score cutoff ≥7 showed excellent diagnostic performance:

    • AUC: 0.95–0.96

    • Sensitivity: 91–94%

    • Specificity: 97–99%

• Clinical implication: The model reliably detects aPTB even in patients without classic TB symptoms (≈70% had symptom scores ≤1).

---

When

• Derivation cohort: 2000–2020

• Temporal validation cohort: 2021–2023

• Study design: Retrospective analysis

---

Where

• Geographic setting: Chia-Yi, southern Taiwan

• Health system context: TB diagnosis following Taiwan’s tiered strategy using AFB smear, selective PCR, and culture confirmation.

---

Why

• Rationale: Atypical TB presentations are common in the late-elderly, leading to diagnostic delays, especially outside pulmonology settings.

• Existing symptom-based tools underperform in this population, and frailty markers (e.g., sarcopenia, osteoporosis) do not adequately capture risk.

• Early identification is critical to reduce missed diagnoses and improve outcomes in this vulnerable group.

---

How

• Design: Retrospective cohort study with derivation and temporal validation

• Inclusion criteria: Age ≥75 years, WHO/CDC symptom score <5, culture-confirmed TB

• Analysis:

  • Univariate screening (p < 0.05)

  • Multivariate logistic regression with stepwise selection

  • Model robustness assessed via:

    • ROC/AUC

    • Calibration plots

    • Decision curve analysis (DCA)

    • Subgroup analyses (age strata, diabetes status)

• Validation: Independent temporal cohort; no significant AUC differences (DeLong test p > 0.70)

• Reliability: Excellent inter-observer agreement for radiographic assessment (Fleiss’ κ = 0.91)

---

Overall conclusion

The study presents a simple, highly accurate, and externally validated clinical scoring tool for early detection of atypical pulmonary TB in adults aged ≥75 years. Extreme old age (>85 years) emerged as the most powerful predictor, surpassing traditional frailty indicators. Integration of this score into electronic medical records could meaningfully reduce diagnostic delays in non-pulmonology settings.

Source: Yeh, J.J., Chen, J.H., Kuo, Y.L., Tsai, C.H. and Ko, Y.E., 2025. A Clinical Prediction Model for Atypical Tuberculosis Manifestations Among Older Adults. Medicina, 61(10), p.1888.