Impact of Dyspnea on Adults with Respiratory Symptoms Without a Defined Diagnosis.

BACKGROUND: We investigated dyspnea, its associated risk factors, and its impact on healthcare utilization, quality of life, and work productivity in adults with undiagnosed respiratory symptoms. RESEARCH QUESTION: What is the impact of dyspnea in adults with undiagnosed respiratory symptoms? STUDY DESIGN AND METHODS: This population-based study included 2857 adults who were experiencing respiratory symptoms. These individuals had not been previously diagnosed with any lung conditions and were recruited from 17 Canadian centers using random digit-dialing. Each participant underwent spirometry testing both before and after using a bronchodilator to determine if they met the diagnostic criteria for COPD, asthma, Preserved Ratio Impaired Spirometry (PRISm), or if their spirometry results were normal. An age-matched control group (n= 231) was similarly recruited using random-digit dialing. A dyspnea impact assessment score from 0 to 100 was produced using questions from the COPD Assessment Test and St. George's Respiratory Questionnaire. RESULTS: Individuals with PRISm (n=172) reported more impactful dyspnea (mean score 63.0, 95% CI: 59.5- 66.4) than those with undiagnosed asthma (n=265, mean score 56.6, 95% CI: 53.9-59.3) or undiagnosed COPD (n=330, mean score 57.5, 95% CI: 55.1-59.9). All groups reported significantly more impactful dyspnea compared to controls (mean score 13.8, 95% CI:11.8-15.7). Subject-specific risk factors including age, sex, BMI, smoking, and comorbidities explained 20.6% of the variation in dyspnea. An additional 12.4% of the variation was explained by disease classification and another 1.7% by the severity of lung function impairment assessed with spirometry. After adjusting for age, sex, and BMI, greater dyspnea impact was associated with increased healthcare utilization, lower quality of life, and reduced work productivity. INTERPRETATION: In community-based adults with undiagnosed respiratory symptoms, those identified with PRISm experienced the greatest impact of dyspnea. Dyspnea imposes burdens on the healthcare system and is associated with impaired quality of life and work productivity.

Results from a retrospective case finding and re-engagement exercise for people previously diagnosed with hepatitis C virus to increase uptake of directly acting antiviral treatment.

BACKGROUND: Direct acting antivirals (DAAs) for the Hepatitis C virus (HCV) have shifted the World Health Organisation global strategic focus to the elimination of HCV by 2030. In England, the UK Health Security Agency (UKHSA) led a national 'patient re-engagement exercise', using routine surveillance data, which was delivered through the HCV Operational Delivery Networks (ODNs) with support from National Health Service England (NHSE), to help find and support people with a positive HCV PCR test result to access treatment. We report a quantitative evaluation of outcomes of this exercise. METHODS: Individuals with a recorded positive HCV antibody or PCR result between 1996 and 2017 were identified using UKHSA's records of HCV laboratory diagnosis. Linkage with established health-care datasets helped to enhance patient identification and minimise attempts to contact deceased or previously treated individuals. From September to November 2018 each ODN was provided with a local list of diagnosed individuals. ODNs were asked to perform further data quality checks through local systems and then write to each individual's GP to inform them that the individual would be contacted by the ODN to offer confirmatory HCV PCR testing, assessment and treatment unless the GP advised otherwise. Outcomes of interest were receipt of treatment, a negative PCR result, and death. Data were collected in 2022. RESULTS: Of 176,555 individuals with a positive HCV laboratory report, 55,329 individuals were included in the exercise following linkage to healthcare datasets and data reconciliation. Participants in the study had a median age of 51 years (IQR: 43, 59), 36,779 (66.5%) were males, 47,668 (86.2%) were diagnosed before 2016 and 11,148 (20.2%) lived in London. Of the study population, 7,442 (13.4%) had evidence of treatment after the re-engagement exercise commenced, 6,435 (11.6%) were reported as PCR negative (96% had no previous treatment records), 4,195 (7.6%) had prescription data indicating treatment before the exercise commenced or were reported to have been treated previously by their ODN, and 2,990 (5.4%) had died. The status of 32,802 (59.3%) people remains unknown. CONCLUSIONS: A substantial number of those included had treatment recorded after the exercise commenced, however, many more remain unengaged. Evaluation of the exercise highlighted areas that could be streamlined to improve future exercises.

Missed opportunities in the prevention and diagnosis of pediatric tuberculosis: a scoping review

Abstract Objectives: Identify potential barriers, delays, and missed opportunities in the prevention and diagnosis of childhood TB. Methods: Scoping review according to the PRISMA extension. The definitions considered for the selection followed the acronym PCC where the population (P) is children under 18years of age with TB disease, the concept (C) refers to missed opportunities for prevention and diagnosis, and context (C) is defined as a diagnosis of TB disease. The authors searched systematically in the databases; VHL/Lilacs, Medline via PubMed, Cochrane, Scopus, and Web of Science, without date or language limitation. Results: Seven studies were included. In developed countries, with low disease burden, the main shortcoming is the delay in diagnosing bacilliferous adults in contact with young children. This problem is concentrated in the portion of the population with socioeconomic vulnerability. In underdeveloped countries, with a high burden of disease, the biggest challenge is tracking children who come into contact with bacilliferous patients. Conclusions: There are still many missed opportunities in the prevention and diagnosis of childhood TB. The positive legacy of the COVID-19 pandemic should be taken advantage of and the encouragement of scientific development in the management of infectious diseases should be taken.

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.

Feasibility of eliminating tuberculosis by shortening the diagnostic delay: A retrospective analysis and modelling study in China during the pre-COVID-19 era.

Objective: Delays in the diagnosis and treatment of pulmonary tuberculosis (PTB) can increase the risk of transmission, thereby posing a significant risk to public health. Early diagnosis is considered to play a crucial role in eliminating TB. Rapid testing, active case finding, and health education are effective strategies for reducing tuberculosis diagnosis delays (TDDs). This study aimed to quantitatively compare the impact of reducing the TDD on incidence rates among student and non-student groups, thus exploring the efficacy of shortening the TDD for ending the TB epidemic and providing a reference for achieving the target incidence rate for ending TB. Methods: We used unsupervised hierarchical clustering analysis and non-parametric tests to characterize the epidemiological characteristics of TDD. Additionally, a dynamic transmission model was used to quantify the impact of shortening the TDD on the incidence rates of TB among the two groups. Results: There was an initial increase in the TDD, followed by a decrease. Longer TDDs were observed in the northeastern region of China. Farmers, middle and high school students, middle-aged, elderly individuals and males exhibited relatively longer TDDs. A significant reduction in the incidence rate of PTB was observed when the TDD was decreased by 50 %. However, only reducing the TDD among non-students could achieve the goal of ending TB (i.e., achieving a minimum reduction of 63.00 %). Conclusions: TDD remains a serious risk to public health, and non-students were shown to experience longer TDD. Shortening the TDD is crucial for reducing the incidence rates of TB, especially among non-students. It is essential to develop a highly sensitive and effective system for eliminating TB among non-students.

Expanding Xpert MTB/RIF Ultra® and LF-LAM testing for diagnosis of tuberculosis among HIV-positive adults admitted to hospitals in Tanzania and Mozambique: a randomized controlled trial (the EXULTANT trial).

INTRODUCTION: Tuberculosis (TB) is an important cause of morbidity and mortality among people living with HIV (PLHIV). Current WHO-recommended strategies for diagnosing TB among hospitalized PLHIV rely on symptom screening and disease severity to assess eligibility for urine lipoarabinomannan lateral flow (LF-LAM) and molecular testing. Despite these recommendations, autopsy studies show a large burden of undiagnosed TB among admitted PLHIV. The EXULTANT trial aims to assess the impact of an expanded screening strategy using three specimens (sputum, stool, and urine) for TB diagnosis among PLHIV admitted to hospitals in two high HIV and TB burden African countries. METHODS: This is a multicenter, pragmatic, individually randomized controlled trial conducted across eleven hospitals in Tanzania and Mozambique. Participants in the intervention arm will be tested with Xpert MTB/RIF Ultra® from expectorated sputum, stool, and urine samples, with additional urine LF-LAM testing in the first 24 h after hospital admission, irrespective of the presence of the symptoms. The control arm will implement the WHO standard of care recommendations. Hospitalized adults (≥ 18 years) with a confirmed HIV-diagnosis, irrespective of antiretroviral (ART) therapy status or presence of TB symptoms will be assessed for eligibility at admission. Patients with a pre-existing TB diagnosis, those receiving anti-tuberculosis therapy or tuberculosis preventive treatment in the 6 months prior to enrolment, and those transferred from other hospitals will not be eligible. Also, participants admitted for traumatic reasons such as acute abdomen, maternal conditions, scheduled surgery, having a positive SARS-CoV2 test will be ineligible. The primary endpoint is the proportion of participants with microbiologically confirmed TB starting treatment within 3 days of enrolment. DISCUSSION: The EXULTANT trial investigates rapid implementation after admission of a new diagnostic algorithm using Xpert MTB/RIF Ultra® in several non-invasive specimens, in addition to LF-LAM, in hospitalized PLHIV regardless of TB symptoms. This enhanced strategy is anticipated to detect frequently missed TB cases in this population and is being evaluated as an implementable and scalable intervention. TRIAL REGISTRATION: Trial reference number: NCT04568967 (ClinicalTrials.gov) registered on 2020-09-29.

Using a Knowledge and Awareness Survey to Engage and Inform a Community-Based Tuberculosis Intervention among Nomads in Adamawa State, Nigeria.

BACKGROUND: Nomadic populations are frequently isolated and vulnerable to diseases including tuberculosis (TB) and human immunodeficiency virus (HIV) due to limited access to health-related information and services, poverty, and social exclusion. We designed and implemented community-driven and -based outreach for TB and HIV based on the results of a TB knowledge, attitude, and practices (KAP) survey in Adamawa, Nigeria. METHODS: We conducted a cross-sectional study on KAP among nomads using an adapted WHO survey. A TB and HIV community-level active case-finding intervention among nomadic populations was planned and delivered based on the KAP survey results. RESULTS: Among 81 respondents, 26 (32.1%) knew what caused TB. More than 60% reported no health facilities in their community. Radio and healthcare workers were primary sources of information on health. Using community input, we developed and broadcasted radio jingles to sensitize people to TB services. Outreach initiatives led to the verbal screening of 61,891 individuals and 306 were diagnosed with TB. Additionally, 4489 people underwent HIV testing, and 69 were HIV-positive, all of whom were linked to treatment. CONCLUSIONS: The results of KAP surveys can inform the design of evidence-based TB and HIV community-driven and -based case-finding interventions in rural Nigeria among nomadic populations.

Yield of TB screening in prisons in Tajikistan.

BACKGROUND: The rate of TB in prison institutions is estimated to be 23 times higher than in the general population. Limited documentation exists regarding TB screening in Tajikistan's prisons. This study aims to report findings from a TB screening conducted in prison facilities in Tajikistan. METHODS: A systematic TB screening was conducted between July 2022 and September 2023, following a locally adapted algorithm based on WHO recommendations. The screening yield was calculated as the proportion of confirmed TB cases, with categorical variables compared using a χ2 test. RESULTS: A total of 7,223 screenings were conducted, identifying 31 TB cases, including 17 drug-susceptible TB cases, eight drug-resistant TB cases, and six clinically diagnosed cases. The overall screening yield was 0.43%. Notably, the screening yield was 3.4% among individuals with at least one TB symptom and 0.03% among those without TB symptoms (P < 0.001). CONCLUSION: The identified rate of TB in these prisons is five times higher than in the general population. Symptomatic individuals had a higher likelihood of TB diagnosis, and using chest X-rays significantly improved screening yield. We recommend increasing the capacity for chest X-ray testing to enhance TB prevention and control within prison settings.

CONTEXTE: On estime que le taux de TB dans les établissements pénitentiaires est 23 fois plus élevé que dans la population générale. Il existe peu de documentation sur le dépistage de la TB dans les prisons du Tadjikistan. Cette étude vise à rendre compte des résultats d'un dépistage de la TB mené dans des établissements pénitentiaires au Tadjikistan. MÉTHODES: Un dépistage systématique de la TB a été réalisé entre juillet 2022 et septembre 2023, selon un algorithme adapté localement et basé sur les recommandations de l'OMS. Le rendement du dépistage a été calculé comme la proportion de cas confirmés de TB, avec des variables catégorielles comparées à l'aide d'un test χ2. RÉSULTATS: Au total, 7 223 dépistages ont été effectués, permettant d'identifier 31 cas de TB, dont 17 cas de TB sensible aux médicaments, 8 cas de TB résistante aux médicaments et 6 cas diagnostiqués cliniquement. Le rendement global du criblage était de 0,43%. Notamment, le rendement du dépistage était de 3,4% chez les personnes présentant au moins un symptôme de la TB et de 0,03% chez celles ne présentant pas de symptômes de la TB (P < 0,001). CONCLUSION: Le taux de TB identifié dans ces prisons est cinq fois plus élevé que dans la population générale. Les personnes symptomatiques avaient une probabilité plus élevée d'être diagnostiquées comme atteintes de TB, et l'utilisation de radiographies pulmonaires améliorait considérablement le rendement du dépistage. Nous recommandons d'augmenter la capacité de dépistage par radiographie thoracique afin d'améliorer la prévention et le contrôle de la TB en milieu carcéral.

Exploring Active Case Detection Approaches for Leprosy Diagnosis in Varied Endemic Settings: A Comprehensive Scoping Review.

(1) Background: The global burden of leprosy is not shared equally; with the majority of cases being diagnosed in Brazil, India, and Indonesia. Understanding the methods of active case detection (ACD) used in high and low endemic regions is vital for the development of future screening programs. (2) Methods: A systematic search of three databases, PubMed, Embase and Web of Science, was conducted for English language papers, published since the year 2000, which discussed the use of active case detection methods for leprosy screening. The paper utilised the Integrated Screening Action Model (I-SAM) as a tool for the analysis of these methods. (3) Results: 23 papers were identified from 11 different countries. The papers identified 6 different methods of active case detection: Household contact/social contact identification; door-to-door case detection; screening questionnaire distribution; rapid village surveys; school-based screening; and prison-based screening. 15 were located in high endemic regions and 8 of these were located in low endemic regions. (4) Conclusions: For selecting the appropriate methods of active case finding, the leprosy endemicity must be taken into consideration. The findings contribute to policy decision making allowing for more successful future leprosy case detection programs to be designed, ultimately reducing the global burden of the disease, and achieving the WHO's aim of zero leprosy.

External validation of the Hong Kong Chinese non-laboratory risk models and scoring algorithm for case finding of prediabetes and diabetes mellitus in primary care.

AIMS/INTRODUCTION: Two Hong Kong Chinese non-laboratory-based prediabetes/diabetes mellitus (pre-DM/DM) risk models were developed using logistic regression (LR) and machine learning, respectively. We aimed to evaluate the models' validity in case finding of pre-DM/DM in a Chinese primary care (PC) population. We also evaluated the validity of a risk-scoring algorithm derived from the LR model. MATERIALS AND METHODS: This was a cross-sectional external validation study on Chinese adults, without a prior DM diagnosis, who were recruited from public/private PC clinics in Hong Kong. A total of 1,237 participants completed a questionnaire on the models' predictors. Of that, 919 underwent blood glucose testing. The primary outcome was the models' and the algorithm's sensitivity in finding pre-DM/DM cases. The secondary outcomes were the models' and the algorithm's specificity, positive/negative predictive values, discrimination and calibration. RESULTS: The models' sensitivity were 0.70 (machine learning) and 0.72 (LR). Both showed good external discrimination (area under the receiver operating characteristic curve: machine learning 0.744, LR 0.739). The risks estimated by the models were lower than the observed incidence, indicating poor calibration. Both models were more effective among participants with lower pretest probabilities; that is, age 18-44 years. The algorithm's sensitivity was 0.77 at the cut-off score of ≥16 out of 41. CONCLUSION: This study showed the validity of the models and the algorithm for finding pre-DM/DM cases in a Chinese PC population in Hong Kong. They can facilitate more cost-effective identification of high-risk individuals for blood testing to diagnose pre-DM/DM in PC. Further studies should recalibrate the models for more precise risk estimation in PC populations.

Optimizing Trichiasis Case Finding to Attain the Elimination of Trachoma as a Public Health Problem.

BACKGROUND: As national trachoma programmes increase efforts to reduce the burden of trachomatous trichiasis (TT), TT case finding and referral are critical public health programme components. Our research aimed to explore the most effective and efficient approaches to finding, referring, and managing TT cases. METHODS: This was a prospective descriptive study, utilizing both routine programme data and primary data collection. This study compared four different approaches to finding TT cases across three different local government areas (LGAs) in Kano State, Nigeria. Each of the study LGAs was divided into four sub-units to accommodate the four different approaches. RESULTS: The number of outreach attendees was 4795 across the four case finding approaches, and this varied hugely, with the smallest number and proportion (403, 0.26%) in settings only employing house-to-house case finding and the largest number and proportion (1901, 0.99%) when town criers were used. That said, the proportion of TT cases among people presenting at outreach was highest (32.5%) when house-to-house case finding was used and lowest (10.3%) when town criers were used. More female TT patients were found (53-70%) and had surgery (79-85%) compared to male cases, across all approaches. The average project expenditure for finding one TT case was similar for approaches that included house-to-house case finding (USD 5.4-6.3), while it was 3.5 times higher (USD 21.5 per TT case found) when town criers were used. DISCUSSION: This study found that the house-to-house TT case finding approaches were the most efficient method with the highest yield of TT cases. Including other eye condition and/or vision testing yielded similar results but required more personnel and cost.

Long-term Cost-effectiveness of Case Finding and Mass Screening for Celiac Disease in Children.

BACKGROUND & AIMS: Celiac disease (CD) is a common yet underdiagnosed autoimmune disease with substantial long-term consequences. High-accuracy point-of-care tests for CD antibodies conducted at youth primary health care centers may enable earlier identification of CD, but evidence about the cost-effectiveness of such strategies is lacking. We estimated the long-term cost-effectiveness of active case finding and mass screening compared with clinical detection in the Netherlands. METHODS: A decision tree and Markov model were used to simulate a cohort of 3-year-old children with CD according to each strategy, taking into account their impact on long-term costs (from a societal perspective) and quality-adjusted life-years (QALYs). Model parameters incorporated data from the GLUTENSCREEN project, the Dutch Celiac Society, the Dutch Pediatric Surveillance Unit, and published sources. The primary outcome was the incremental cost-effectiveness ratio (ICER) between strategies. RESULTS: Mass-screening produced 7.46 more QALYs and was €28,635 more costly compared with current care (ICER: €3841 per QALY), and case finding produced 4.33 more QALYs and was €15,585 more costly compared with current care (ICER: €3603 per QALY). At a willingness to pay of €20,000 per QALY, both strategies were highly cost-effective compared with current care. Scenario analyses indicated that mass screening is likely the optimal strategy, unless no benefit in detecting asymptomatic cases is assumed. CONCLUSIONS: An earlier identification of CD through screening or case finding in children using a point-of-care tests leads to improved health outcomes and is cost-effective in the long-term compared with current care. If the feasibility and acceptability of the proposed strategies are successful, implementation in Dutch regular care is needed.

A novel method to monitor rheumatoid arthritis prevalence using hospital and medication databases.

BACKGROUND: Most estimates of rheumatoid arthritis (RA) prevalence, including all official figures in Australia and many other countries, are based on self-report. Self-report has been shown to overestimate RA, but the 'gold standard' of reviewing individual medical records is costly, time-consuming and impractical for large-scale research and population monitoring. This study provides an algorithm to estimate RA cases using administrative data that can be adjusted for use in multiple contexts to provide the first approximate RA cohort in Australia that does not rely on self-report. METHODS: Survey data on self-reported RA and medications from 25 467 respondents of the Australian Longitudinal Study on Women's Health (ALSWH) were linked with data from the national medication reimbursement database, hospital and emergency department (ED) episodes, and Medicare Benefits codes. RA prevalence was calculated for self-reported RA, self-reported RA medications, dispensed RA medications, and hospital/ED RA presentations. Linked data were used to exclude individuals with confounding autoimmune conditions. RESULTS: Of 25 467 survey respondents, 1367 (5·4%) women self-reported disease. Of the 26 840 women with hospital or ED presentations, 292 (1·1%) received ICD-10 codes for RA. There were 1038 (2·8%) cases by the medication database definition, and 294 cases (1·5%) by the self-reported medication definition. After excluding individuals with other rheumatic conditions, prevalence was 3·9% for self-reported RA, 1·9% based on the medication database definition and 0·5% by self-reported medication definition. This confirms the overestimation of RA based on self-reporting. CONCLUSIONS: We provide an algorithm for identifying individuals with RA, which could be used for population studies and monitoring RA in Australia and, with adjustments, internationally. Its balance of accuracy and practicality will be useful for health service planning using relatively easily accessible input data.

Test-treat-track-test-treat (5T) approach for Schistosoma haematobium elimination on Pemba Island, Tanzania.

BACKGROUND: After decades of praziquantel mass drug administration (MDA), several countries approach schistosomiasis elimination. Continuing MDA in largely uninfected populations no longer seems justified. Alternative interventions to maintain the gains or accelerate interruption of transmission are needed. We report results, strengths, and shortcomings of novel test-treat-track-test-treat (5T) interventions in low Schistosoma haematobium prevalence areas on Pemba, Tanzania. METHODS: School- and household-based surveys were conducted in 2021 and 2022 to monitor the S. haematobium and microhematuria prevalence and assess the impact of interventions. In 2021, 5T interventions were implemented in 15 low-prevalence areas and included: (i) testing schoolchildren in primary and Islamic schools for microhematuria as a proxy for S. haematobium, (ii) treating positive children, (iii) tracking them to their households and to water bodies they frequented, (iv) testing individuals at households and water bodies, and (v) treating positive individuals. Additionally, test-and-treat interventions were implemented in the 22 health facilities of the study area. RESULTS: The S. haematobium prevalence in the school-based survey in 15 low-prevalence implementation units was 0.5% (7/1560) in 2021 and 0.4% (6/1645) in 2022. In the household-based survey, 0.5% (14/2975) and 0.7% (19/2920) of participants were infected with S. haematobium in 2021 and 2022, respectively. The microhematuria prevalence, excluding trace results, in the school-based survey was 1.4% (21/1560) in 2021 and 1.5% (24/1645) in 2022. In the household-based survey, it was 3.3% (98/2975) in 2021 and 5.4% (159/2920) in 2022. During the 5T interventions, the microhaematuria prevalence was 3.8% (140/3700) and 5.8% (34/594) in children in primary and Islamic schools, respectively, 17.1% (44/258) in household members, and 16.7% (10/60) in people at water bodies. In health facilities, 19.8% (70/354) of patients tested microhematuria-positive. CONCLUSIONS: The targeted 5T interventions maintained the very low S. haematobium prevalence and proved straightforward and feasible to identify and treat many of the few S. haematobium-infected individuals. Future research will show whether 5T interventions can maintain gains in the longer-term and expedite elimination. TRIAL REGISTRATION: ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493 .

Population-wide active case finding as a strategy to end TB.

Tuberculosis (TB) is the leading infectious cause of morbidity and mortality globally. Despite available tools for preventing, finding, and treating TB, many people with TB remain undiagnosed. In high-incidence settings, TB transmission is ubiquitous within the community, affecting both high-risk groups and the general population. In fact, most people who develop TB come from the general population. To disrupt the chain of transmission that sustains the TB epidemic, we need to find and treat everyone with infectious TB as early as possible, including those with minimal symptoms or subclinical TB who are unlikely to present for care. Important elements of an effective active case-finding strategy include effective social mobilisation and community engagement, using sensitive screening tools that can be used at scale, and embracing population-wide screening in high-incidence ('hot spot') areas. We require a better description of feasible delivery models, 'real-life' impact and cost effectiveness to enable wider implementation.

Active Case Finding among Adults using an Individual's Vulnerability Score for Pulmonary Tuberculosis in a Rural Village of Goa: A Cross-sectional Study.

Background: "Detect-Treat-Prevent-Build" to achieve tuberculosis (TB)-free India is envisaged in the National Tuberculosis Elimination Program (NTEP). To be able to achieve this, it is important to address the fact that the most vulnerable and hard-to-reach groups need to undertake screening. The present review aimed to examine the vulnerability in connection with TB disparities faced by distinct sub-populations generally viewed as vulnerable and follow these for testing. Materials and Methods: The community-based cross-sectional study was conducted in the field practice area of sub-center Carambolim in a rural area of Goa for 3 months. The households were visited, and data collected via personal interviews were recorded on the questionnaire study tool. Based on the data, the participants' vulnerability mapping was done per the parameters identified. Results: Among 223 households, 528 persons were screened for vulnerability. The 47 highly vulnerable participants were advised sputum CBNAAT, of which 9 (19%) tested positive for pulmonary TB, while of the 86 moderately vulnerable participants, 4 (5%) tested positive for pulmonary TB. Among the 34 with symptoms suggestive of TB, 3 (9%) tested positive for pulmonary TB. Conclusions: The study detected 16 new TB patients from the population and found a higher incidence of pulmonary TB among the vulnerable group with no symptoms of Pulmonary TB. A further state-wide survey is recommended to diagnose such cases.

A mixed-methods study on impact of active case finding on pulmonary tuberculosis treatment outcomes in India.

BACKGROUND: Tuberculosis (TB) remains a significant public health burden in India, with elimination targets set for 2025. Active case finding (ACF) is crucial for improving TB case detection rates, although conclusive evidence of its association with treatment outcomes is lacking. Our study aims to investigate the impact of ACF on successful TB treatment outcomes among pulmonary TB patients in Gujarat, India, and explore why ACF positively impacts these outcomes. METHODS: We conducted a retrospective cohort analysis in Gujarat, India, including 1,638 pulmonary TB cases identified through ACF and 80,957 cases through passive case finding (PCF) from January 2019 to December 2020. Generalized logistic mixed-model compared treatment outcomes between the ACF and PCF groups. Additionally, in-depth interviews were conducted with 11 TB program functionaries to explore their perceptions of ACF and its impact on TB treatment outcomes. RESULTS: Our analysis revealed that patients diagnosed through ACF exhibited 1.4 times higher odds of successful treatment outcomes compared to those identified through PCF. Program functionaries emphasized that ACF enhances case detection rates and enables early detection and prompt treatment initiation. This early intervention facilitates faster sputum conversion and helps reduce the infectious period, thereby improving treatment outcomes. Functionaries highlighted that ACF identifies TB cases that might otherwise be missed, ensuring timely and appropriate treatment. CONCLUSION: ACF significantly improves TB treatment outcomes in Gujarat, India. The mixed-methods analysis demonstrates a positive association between ACF and successful TB treatment, with early detection and prompt treatment initiation being key factors. Insights from TB program functionaries underscore the importance of ACF in ensuring timely diagnosis and treatment, which are critical for better treatment outcomes. Expanding ACF initiatives, especially among hard-to-reach populations, can further enhance TB control efforts. Future research should focus on optimizing ACF strategies and integrating additional interventions to sustain and improve TB treatment outcomes.

Drug-Resistant Tuberculosis Case-Finding Strategies: Scoping Review.

BACKGROUND: Finding individuals with drug-resistant tuberculosis (DR-TB) is important to control the pandemic and improve patient clinical outcomes. To our knowledge, systematic reviews assessing the effectiveness, cost-effectiveness, acceptability, and feasibility of different DR-TB case-finding strategies to inform research, policy, and practice, have not been conducted and the scope of primary research is unknown. OBJECTIVE: We therefore assessed the available literature on DR-TB case-finding strategies. METHODS: We looked at systematic reviews, trials, qualitative studies, diagnostic test accuracy studies, and other primary research that sought to improve DR-TB case detection specifically. We excluded studies that included patients seeking care for tuberculosis (TB) symptoms, patients already diagnosed with TB, or were laboratory-based. We searched the academic databases of MEDLINE, Embase, The Cochrane Library, Africa-Wide Information, CINAHL (Cumulated Index to Nursing and Allied Health Literature), Epistemonikos, and PROSPERO (The International Prospective Register of Systematic Reviews) using no language or date restrictions. We screened titles, abstracts, and full-text articles in duplicate. Data extraction and analyses were carried out in Excel (Microsoft Corp). RESULTS: We screened 3646 titles and abstracts and 236 full-text articles. We identified 6 systematic reviews and 61 primary studies. Five reviews described the yield of contact investigation and focused on household contacts, airline contacts, comparison between drug-susceptible tuberculosis and DR-TB contacts, and concordance of DR-TB profiles between index cases and contacts. One review compared universal versus selective drug resistance testing. Primary studies described (1) 34 contact investigations, (2) 17 outbreak investigations, (3) 3 airline contact investigations, (4) 5 epidemiological analyses, (5) 1 public-private partnership program, and (6) an e-registry program. Primary studies were all descriptive and included cross-sectional and retrospective reviews of program data. No trials were identified. Data extraction from contact investigations was difficult due to incomplete reporting of relevant information. CONCLUSIONS: Existing descriptive reviews can be updated, but there is a dearth of knowledge on the effectiveness, cost-effectiveness, acceptability, and feasibility of DR-TB case-finding strategies to inform policy and practice. There is also a need for standardization of terminology, design, and reporting of DR-TB case-finding studies.

Artificial Intelligence Applied to Forced Spirometry in Primary Care.

Introduction: This study aims to create an artificial intelligence (AI) based machine learning (ML) model capable of predicting a spirometric obstructive pattern using variables with the highest predictive power derived from an active case-finding program for COPD in primary care. Material and methods: A total of 1190 smokers, aged 30-80 years old with no prior history of respiratory disease, underwent spirometry with bronchodilation. The sample was analyzed using AI tools. Based on an exploratory data analysis (EDA), independent variables (according to mutual information analysis) were trained using a gradient boosting algorithm (GBT) and validated through cross-validation. Results: With an area under the curve close to unity, the model predicted a spirometric obstructive pattern using variables with the highest predictive power: FEV1_theoretical_pre values. Sensitivity: 93%. Positive predictive value: 94%. Specificity: 97%. Negative predictive value: 96%. Accuracy: 95%. Precision: 94%. Conclusion: An ML model can predict the presence of an obstructive pattern in spirometry in a primary care smoking population with no prior diagnosis of respiratory disease using the FEV1_theoretical_pre values with an accuracy and precision exceeding 90%. Further studies including clinical data and strategies for integrating AI into clinical workflow are needed.

Introducción: Este estudio tiene como objetivo crear un modelo de aprendizaje automático (ML) basado en inteligencia artificial (IA) capaz de predecir un patrón obstructivo espirométrico utilizando variables con el mayor poder predictivo derivado de un programa activo de búsqueda de casos de enfermedad pulmonar obstructiva crónica (EPOC) en Atención Primaria. Materiales y métodos: Un total de 1.190 fumadores, de entre 30 y 80 años, sin antecedentes de enfermedad respiratoria, fueron sometidos a espirometría con IA artificial. Sobre la base de un análisis de datos exploratorio (EDA), las variables independientes (según el análisis de información mutua) se entrenaron utilizando un algoritmo de gradiente de aumento (GBT) y se validaron mediante validación cruzada. Resultados: Con un área bajo la curva cercana a la unidad, el modelo predijo un patrón obstructivo espirométrico utilizando los valores del FEV1 prebroncodilatador. Sensibilidad: 93%. Valor predictivo positivo: 94%. Especificidad: 97%. Valor predictivo negativo: 96%. Precisión: 95%. Precisión: 94%. Conclusión: Un modelo ML puede predecir la presencia de un patrón obstructivo en la espirometría en una población fumadora de atención primaria sin diagnóstico previo de enfermedad respiratoria utilizando los valores FEV1 prebroncodilatadores con una exactitud y precisión superiores al 90%. Se necesitan más estudios que incluyan datos clínicos y estrategias para integrar la IA en el flujo de trabajo clínico.