Prevalence of non-communicable diseases among household contacts of people with tuberculosis: A systematic review and individual participant data meta-analysis.

OBJECTIVE: To investigate the prevalence of non-communicable diseases among household contacts of people with tuberculosis. METHODS: We conducted a systematic review and individual participant data meta-analysis. We searched Medline, Embase and the Global Index Medicus from inception to 16 May 2023. We included studies that assessed for at least one non-communicable disease among household contacts of people with clinical tuberculosis. We estimated the non-communicable disease prevalence through mixed effects logistic regression for studies providing individual participant data, and compared it with estimates from aggregated data meta-analyses. Furthermore, we compared age and sex-standardised non-communicable disease prevalence with national-level estimates standardised for age and sex. RESULTS: We identified 39 eligible studies, of which 14 provided individual participant data (29,194 contacts). Of the remaining 25 studies, 18 studies reported aggregated data suitable for aggregated data meta-analysis. In individual participant data analysis, the pooled prevalence of diabetes in studies that undertook biochemical testing was 8.8% (95% confidence interval [CI], 5.1%-14.9%, four studies). Age-and sex-standardised prevalence was higher in two studies (10.4% vs. 6.9% and 11.5% vs. 8.4%) than the corresponding national estimates and similar in two studies. Prevalence of diabetes mellitus based on self-report or medical records was 3.4% (95% CI 2.6%-4.6%, 14 studies). Prevalence did not significantly differ compared to estimates from aggregated data meta-analysis. There were limited data for other non-communicable diseases. CONCLUSION: The prevalence of diabetes mellitus among household contacts was high while that of known diabetes was substantially lower, suggesting the underdiagnosis. tuberculosis household contact investigation offers opportunities to deliver multifaceted interventions to identify tuberculosis infection and disease, screen for non-communicable diseases and address shared risk factors.

Active case-finding of tuberculosis compared with symptom-driven standard of care: a modelling analysis.

BACKGROUND: In settings with large case detection gaps, active case-finding (ACF) may play a critical role in the uberculosis (TB) response. However, ACF is resource intensive, and its effectiveness depends on whether people detected with TB through ACF might otherwise spontaneously resolve or be diagnosed through routine care. We analysed the potential effectiveness of ACF for TB relative to the counterfactual scenario of routine care alone. METHODS: We constructed a Markov simulation model of TB natural history, diagnosis, symptoms, ACF and treatment, using a hypothetical reference setting using data from South East Asian countries. We calibrated the model to empirical data using Bayesian methods, and simulated potential 5-year outcomes with an 'aspirational' ACF intervention (reflecting maximum possible effectiveness) compared with the standard-of-care outcomes. RESULTS: Under the standard of care, 51% (95% credible interval, CrI: 31%, 75%) of people with prevalent TB at baseline were estimated to be diagnosed and linked to care over 5 years. With aspirational ACF, this increased to 88% (95% CrI: 84%, 94%). Most of this difference represented people who were diagnosed and treated through ACF but experienced spontaneous resolution under standard-of-care. Aspirational ACF was projected to reduce the average duration of TB disease by 12 months (95% CrI: 6%, 18%) and TB-associated disability-adjusted life-years by 71% (95% CrI: 67%, 76%). CONCLUSION: These data illustrate the importance of considering outcomes in a counterfactual standard of care scenario, as well as trade-offs between overdiagnosis and averted morbidity through earlier diagnosis-not just for TB, but for any disease in which population-based screening is recommended.

Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software.

BACKGROUND: Computer-aided detection (CAD) can help identify people with active tuberculosis left undetected. However, few studies have compared the performance of commercially available CAD products for screening in high tuberculosis and high HIV settings, and there is poor understanding of threshold selection across products in different populations. We aimed to compare CAD products' performance, with further analyses on subgroup performance and threshold selection. METHODS: We evaluated 12 CAD products on a case-control sample of participants from a South African tuberculosis prevalence survey. Only those with microbiological test results were eligible. The primary outcome was comparing products' accuracy using the area under the receiver operating characteristic curve (AUC) against microbiological evidence. Threshold analyses were performed based on pre-defined criteria and across all thresholds. We conducted subgroup analyses including age, gender, HIV status, previous tuberculosis history, symptoms presence, and current smoking status. FINDINGS: Of the 774 people included, 516 were bacteriologically negative and 258 were bacteriologically positive. Diverse accuracy was noted: Lunit and Nexus had AUCs near 0·9, followed by qXR, JF CXR-2, InferRead, Xvision, and ChestEye (AUCs 0·8-0·9). XrayAME, RADIFY, and TiSepX-TB had AUC under 0·8. Thresholds varied notably across these products and different versions of the same products. Certain products (Lunit, Nexus, JF CXR-2, and qXR) maintained high sensitivity (>90%) across a wide threshold range while reducing the number of individuals requiring confirmatory diagnostic testing. All products generally performed worst in older individuals, people with previous tuberculosis, and people with HIV. Variations in thresholds, sensitivity, and specificity existed across groups and settings. INTERPRETATION: Several previously unevaluated products performed similarly to those evaluated by WHO. Thresholds differed across products and demographic subgroups. The rapid emergence of products and versions necessitates a global strategy to validate new versions and software to support CAD product and threshold selections. FUNDING: Government of Canada.

Study protocol: diagnostic accuracy study comparing Cy-Tb and STANDARD F TB-Feron FIA tests for tuberculosis infection diagnosis in Vietnam.

INTRODUCTION: The large reservoir of tuberculosis (TB) infections is one of the main reasons for the persistent incidence of TB. Accurate diagnostic tests are crucial to correctly identify and treat people with TB infection, which is vital to eliminate TB globally. The rdESAT-6 and rCFP-10 (Cy-Tb) injection ('Cy-Tb'), a TB-specific antigen skin test and STANDARD F TB-Feron FIA ('Standard F TB') measuring interferon-gamma by fluorescence immunoassay assay are two novel tools for the diagnosis of TB infection which offer advantages compared with current tests in low-resource settings and reduced costs to both health systems and TB-affected people. The proposed study aims to evaluate the diagnostic accuracy of these two new tests for TB infection diagnosis. METHODS AND ANALYSIS: This cross-sectional study aims to assess the diagnostic accuracy for TB infection of the Cy-Tb skin test and Standard F TB assay (investigational tests) compared with the QuantiFERON-TB Gold Plus (QFT-Plus) assay as the immunological reference standard. Three different cohorts of study participants will be recruited at the Vietnam National Lung Hospital: adults with bacteriologically confirmed pulmonary TB (n=100), household contacts of people with TB (n=200) and people without TB infection (n=50). All consenting participants will undergo simultaneous testing with Cy-Tb, Standard F TB and QFT-Plus. The primary endpoint is the diagnostic accuracy of the Cy-Tb skin test and Standard F TB assay, expressed as sensitivity and specificity against the reference standard. ETHICS AND DISSEMINATION: Ethical approval was granted by the Vietnam National Lung Hospital Institutional Review Board (65/23/CN-HDDD-BVPTU) and the Swedish Ethical Review Authority (Dnr 2023-04271-01). Study results will be disseminated to the scientific community and policymakers through scientific publications. TRIAL REGISTRATION NUMBER: NCT06221735.

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries.

Background: In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics. Methods: We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage. Results: In each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries. Conclusions: Using AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings. Supplementary Information: The online version contains supplementary material available at 10.1186/s44263-024-00081-2.

Is convenience really king? Comparative evaluation of catastrophic costs due to tuberculosis in the public and private healthcare sectors of Viet Nam: a longitudinal patient cost study.

BACKGROUND: In Viet Nam, tuberculosis (TB) represents a devastating life-event with an exorbitant price tag, partly due to lost income from daily directly observed therapy in public sector care. Thus, persons with TB may seek care in the private sector for its flexibility, convenience, and privacy. Our study aimed to measure income changes, costs and catastrophic cost incurrence among TB-affected households in the public and private sector. METHODS: Between October 2020 and March 2022, we conducted 110 longitudinal patient cost interviews, among 50 patients privately treated for TB and 60 TB patients treated by the National TB Program (NTP) in Ha Noi, Hai Phong and Ho Chi Minh City, Viet Nam. Using a local adaptation of the WHO TB patient cost survey tool, participants were interviewed during the intensive phase, continuation phase and post-treatment. We compared income levels, direct and indirect treatment costs, catastrophic costs using Wilcoxon rank-sum and chi-squared tests and associated risk factors between the two cohorts using multivariate regression. RESULTS: The pre-treatment median monthly household income was significantly higher in the private sector versus NTP cohort (USD 868 vs USD 578; P = 0.010). However, private sector treatment was also significantly costlier (USD 2075 vs USD 1313; P = 0.005), driven by direct medical costs which were 4.6 times higher than costs reported by NTP participants (USD 754 vs USD 164; P < 0.001). This resulted in no significant difference in catastrophic costs between the two cohorts (Private: 55% vs NTP: 52%; P = 0.675). Factors associated with catastrophic cost included being a single-person household [adjusted odds ratio (aOR = 13.71; 95% confidence interval (CI): 1.36-138.14; P = 0.026], unemployment during treatment (aOR = 10.86; 95% CI: 2.64-44.60; P < 0.001) and experiencing TB-related stigma (aOR = 37.90; 95% CI: 1.72-831.73; P = 0.021). CONCLUSIONS: Persons with TB in Viet Nam face similarly high risk of catastrophic costs whether treated in the public or private sector. Patient costs could be reduced through expanded insurance reimbursement to minimize direct medical costs in the private sector, use of remote monitoring and multi-week/month dosing strategies to avert economic costs in the public sector and greater access to social protection mechanism in general.

La tuberculosis: Introducción / Tuberculosis: Introduction

El presente módulo trata acerca de la historia de la tuberculosis (TB)y de la manera en que está afectando a la población, tanto a nivel mundial como en el Perú. Asimismo, explica cómo se propaga la TB de persona a persona (transmisión) y cómo se desarrolla en el organismo la enfermedad de la TB (patogénesis). Además, deberá conocer sobre la transmisión, patogénesis y el tratamiento de la TB. Como trabajador de salud, deberá comprender estos conceptos, de manera que los pueda poner en conocimiento a los pacientes que atiende

Detección de casos de TB / TB detection of cases of

La presente publicación describe sobre la detección de casos, una de las actividades más importantes para controlar la tuberculosis, ya que a través de ella podrá conocer quién o quiénes han desarrollado la enfermedad y, por lo tanto, saber con qué pacientes iniciar el tratamiento antituberculosis para cortar la cadena epidemiológica de transmisión de la enfermedad y recuperar la salud de las personas afectadas

Tratamiento de Personas con TB / People with TB Treatment

El presente módulo describe cómo tratar a las personas con TB y TB MDR. Para tratar a las personas con TB es necesario identificar el tipo de paciente (nuevo o antes tratado), identificar qué características o condiciones tiene e indicar el esquema de tratamiento que le corresponde. El personal de salud tiene que conocer los medicamentos antituberculosis que el paciente toma y cómo manejará los efectos adversos que puedan ocasionar. Además, tiene que saber administrar el tratamiento y monitorizar el progreso del paciente a través de exámenes de control, para saber si el paciente se está curando o si es necesario tomar otra acción

Manejo de medicamentos y suministros para TB / Operation of drugs and supplies for TB

El presente módulo proporciona los esquemas completos de medicamentos antituberculosis para todos los pacientes con TB. Los medicamentos antituberculosos y otros suministros para detectar y tratar laTB en un establecimiento de salud son los siguientes:1. Medicamentos para el tratamiento de TB y para la quimioprofilaxis, 2. Suministros relacionados con el tratamiento (jeringas, agujas y agua destilada para inyecciones); 3. Envases de plástico para muestras de esputo; 4. Formularios y registros; 5. Insumos de laboratorio (láminas y reactivos). El manejo de los medicamentos y suministros implica asegurar que estén disponibles en cantidades suficientes y que su almacenamiento se mantenga en buenas condiciones. La cantidad de medicamentos o suministros debe programarse el año anterior

Garantizar la continuación del tratamiento de TB / Ensure the continuation of TB treatment

El presente módulo describe los métodos que el trabajador de salud puede utilizar para conocer a sus pacientes, evaluar su capacidad y disposición para cumplir el tratamiento, utilizar métodos comprobados para mejorar la adherencia del paciente y resolver problemas comunes que se presenten durante el tratamiento. A través de la puesta en práctica de las recomendaciones de este Módulo, el trabajador de atención de salud estará en capacidad de ayudar a que sus pacientes permanezcan adherentes y a que terminen exitosamente sus esquemas de tratamiento para la TB

Consejería en TB / Counseling on TB

El consejo y la información sobre la TB, tanto a las personas con TB como a sus familias, es una parte decisiva del tratamiento. El trabajador de salud debe comunicarse con las personas con TB y sus familiares de manera clara, empleando estrategias de comunicación efectivas y debe brindarles apoyo desde el momento del diagnóstico, durante todo el proceso de tratamiento, hasta que el paciente se cure y salga de alta

Guía del tutor / Tutor's Guide

El presente módulo ha sido diseñado como guía para trabajadores de salud que participan en el manejo integral de personas con TB. Estos trabajadores de salud pueden ser técnicos de enfermería, enfermeras o médicos tratantes. Los trabajadores de salud pueden ser hombres o mujeres que se desempeñan en puestos, centros de salud, hospitales e institutos especializados (todos los que se denominan “establecimientos de salud”). Se promueve el trabajo en equipo para saber todo lo que hacen los demás miembros del equipo multidisciplinario

Indicadores para monitorizar el manejo de la TB / Indicators for monitoring the management of TB

El presente módulo se centra en cómo un establecimiento de salud podría monitorizar algunas de sus propias actividades. Este monitoreo revelará los logros o los problemas del establecimiento de salud que se necesiten resolver. Los resultados de este automonitoreo son para el uso propio del establecimiento de salud. Cuando se identifican los problemas, el establecimiento de salud deberá investigar las causas y tomar acciones para resolver los problemas