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Item The Incidence and Risk Factors for Enterotoxigenic(2024-Mar-29) Sukwa N; Bosomprah S; Somwe P; Muyoyeta M; Mwape K; Chibesa K; Luchen CC; Silwamba S; Mulenga B; Munyinda M; Muzazu S; Chirwa M; Chibuye M; Simuyandi M; Chilengi R; Svennerholm AM; Department of Microbiology and Immunology, University of Gothenburg, 40530 Gothenburg, Sweden.; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka P.O. Box 34681, Zambia.; Department of Biostatistics, School of Public Health, University of Ghana, Accra P.O. Box LG13, Ghana.This study aimed to estimate the incidence and risk factors for EnterotoxigenicItem Prospective multicentre accuracy evaluation of the FUJIFILM SILVAMP TB LAM test for the diagnosis of tuberculosis in people living with HIV demonstrates lot-to-lot variability.(2024) Székely R; Sossen B; Mukoka M; Muyoyeta M; Nakabugo E; Hella J; Nguyen HV; Ubolyam S; Chikamatsu K; Macé A; Vermeulen M; Centner CM; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Mitarai S; Nguyen NV; Avihingsanon A; Reither K; Nakiyingi L; Kerkhoff AD; MacPherson P; Meintjes G; Denkinger CM; Ruhwald M; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.; Clinical Research Department, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Ifakara Health Institute, Dar es Salaam, Tanzania.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Taksin Hospital, Bangkok, Thailand.; Department of Mycobacterium Reference and Research, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Tokyo, Japan.; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; German Centre for Infection Research (DZIF), Partner site Heidelberg University Hospital, Heidelberg, Germany.; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital and Faculty of Medicine, Heidelberg University, Heidelberg, Germany.; National Lung Hospital, Ha Noi, Viet Nam.; HIV-NAT, Thai Red Cross AIDS Research Centre and Centre of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Swiss Tropical and Public Health Institute, Allschwil, Switzerland.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; Division of Medical Microbiology, University of Cape Town and National Health Laboratory Service, Groote Schuur Hospital, Cape Town, South Africa.; FIND, The Global Alliance for Diagnostics, Geneva, Switzerland.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, CA, United States of America.; University of Basel, Basel, Switzerland.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)There is an urgent need for rapid, non-sputum point-of-care diagnostics to detect tuberculosis. This prospective trial in seven high tuberculosis burden countries evaluated the diagnostic accuracy of the point-of-care urine-based lipoarabinomannan assay FUJIFILM SILVAMP TB LAM (FujiLAM) among inpatients and outpatients living with HIV. Diagnostic performance of FujiLAM was assessed against a mycobacterial reference standard (sputum culture, blood culture, and Xpert Ultra from urine and sputum at enrollment, and additional sputum culture ≤7 days from enrollment), an extended mycobacterial reference standard (eMRS), and a composite reference standard including clinical evaluation. Of 1637 participants considered for the analysis, 296 (18%) were tuberculosis positive by eMRS. Median age was 40 years, median CD4 cell count was 369 cells/ul, and 52% were female. Overall FujiLAM sensitivity was 54·4% (95% CI: 48·7-60·0), overall specificity was 85·2% (83·2-87·0) against eMRS. Sensitivity and specificity estimates varied between sites, ranging from 26·5% (95% CI: 17·4%-38·0%) to 73·2% (60·4%-83·0%), and 75·0 (65·0%-82·9%) to 96·5 (92·1%-98·5%), respectively. Post-hoc exploratory analysis identified significant variability in the performance of the six FujiLAM lots used in this study. Lot variability limited interpretation of FujiLAM test performance. Although results with the current version of FujiLAM are too variable for clinical decision-making, the lipoarabinomannan biomarker still holds promise for tuberculosis diagnostics. The trial is registered at clinicaltrials.gov (NCT04089423).Item Diagnostic yield as an important metric for the evaluation of novel tuberculosis tests: rationale and guidance for future research.(2024-Jul) Broger T; Marx FM; Theron G; Marais BJ; Nicol MP; Kerkhoff AD; Nathavitharana R; Huerga H; Gupta-Wright A; Kohli M; Nichols BE; Muyoyeta M; Meintjes G; Ruhwald M; Peeling RW; Pai NP; Pollock NR; Pai M; Cattamanchi A; Dowdy DW; Dewan P; Denkinger CM; Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA.; Department of Medicine, University of Cape Town, Cape Town, South Africa; Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; FIND, Geneva, Switzerland.; McGill International TB Centre, McGill University, Montreal, QC, Canada.; Division of HIV, Infectious Diseases, and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA; Center for Tuberculosis, University of California San Francisco, San Francisco, CA, USA.; The University of Sydney Infectious Diseases Institute, Sydney, NSW, Australia; Children's Hospital at Westmead, Sydney, NSW, Australia.; Centre for Infectious Diseases Research in Zambia, Lusaka, Zambia.; DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.; Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany; German Center for Infection Research, Heidelberg University Hospital, Heidelberg, Germany. Electronic address: claudia.denkinger@uni-heidelberg.de.; Boston Children's Hospital, Boston, MA, USA.; London School of Hygiene & Tropical Medicine, London, UK.; Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany; DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Faculty of Science, Stellenbosch University, Stellenbosch, South Africa.; Bill & Melinda Gates Foundation, Seattle, WA, USA.; Division of Infection and Immunity, School of Biomedical Sciences, University of Western Australia, Perth, WA, Australia.; Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany.; Department of Epidemiology, Epicentre, Paris, France.; Center for Tuberculosis, University of California San Francisco, San Francisco, CA, USA; Department of Medicine, Division of Pulmonary Diseases and Critical Care Medicine, University of California Irvine, Irvine, CA, USA.; Department of Medicine, Centre for Outcomes Research & Evaluation, McGill University, Montreal, QC, Canada.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)Better access to tuberculosis testing is a key priority for fighting tuberculosis, the leading cause of infectious disease deaths in people. Despite the roll-out of molecular WHO-recommended rapid diagnostics to replace sputum smear microscopy over the past decade, a large diagnostic gap remains. Of the estimated 10·6 million people who developed tuberculosis globally in 2022, more than 3·1 million were not diagnosed. An exclusive focus on improving tuberculosis test accuracy alone will not be sufficient to close the diagnostic gap for tuberculosis. Diagnostic yield, which we define as the proportion of people in whom a diagnostic test identifies tuberculosis among all people we attempt to test for tuberculosis, is an important metric not adequately explored. Diagnostic yield is particularly relevant for subpopulations unable to produce sputum such as young children, people living with HIV, and people with subclinical tuberculosis. As more accessible non-sputum specimens (eg, urine, oral swabs, saliva, capillary blood, and breath) are being explored for point-of-care tuberculosis testing, the concept of yield will be of growing importance. Using the example of urine lipoarabinomannan testing, we illustrate how even tests with limited sensitivity can diagnose more people with tuberculosis if they enable increased diagnostic yield. Using tongue swab-based molecular tuberculosis testing as another example, we provide definitions and guidance for the design and conduct of pragmatic studies that assess diagnostic yield. Lastly, we show how diagnostic yield and other important test characteristics, such as cost and implementation feasibility, are essential for increased effective population coverage, which is required for optimal clinical care and transmission impact. We are calling for diagnostic yield to be incorporated into tuberculosis test evaluation processes, including the WHO Grading of Recommendations, Assessment, Development, and Evaluations process, providing a crucial real-life implementation metric that complements traditional accuracy measures.Item Clinical diagnosis of TB: lessons on misdiagnosis and overdiagnosis.(2025-Jun) Singini DS; Sanjase N; Kagujje M; Shatalimi J; Chisanga CP; Lupatali ZD; Phiri D; Tatila T; Olwit W; Kerkhoff AD; Muyoyeta M; University of California, Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital, San Francisco, USA.; Uganda Cancer Institute, Kampala, Uganda.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; The Ministry of Health, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)Clinically diagnosed TB patients (n = 335) at two facilities in Lusaka, Zambia were re-evaluated within two weeks of diagnosis. This re-evaluation included sputum Xpert Ultra testing and expert reader interpretation of the chest x-rays (CXRs) used for initial diagnosis. Repeat Xpert Ultra detected TB in just 2.6% (n=6). Of the remaining patients (n=222), expert CXR re-interpretation classified 18.0% as normal; 36.0% as abnormal, consistent with TB; and 46.0% as abnormal, not consistent with TB. These findings suggest that clinical TB is frequently over diagnosed in those without detectable CXR abnormalities and misdiagnosed in those with abnormal CXRs: these abnormalities are likely due to other respiratory conditions. Such misdiagnosis leads to unnecessary treatment, failure to treat the true underlying condition and incorrect estimates of TB burden.Item A Prospective Evaluation of the Diagnostic Accuracy of the Point-of-Care VISITECT CD4 Advanced Disease Test in 7 Countries.(2025-Feb-04) Gils T; Hella J; Jacobs BKM; Sossen B; Mukoka M; Muyoyeta M; Nakabugo E; Van Nguyen H; Ubolyam S; Macé A; Vermeulen M; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Denkinger CM; Nguyen NV; Avihingsanon A; Nakiyingi L; Székely R; Kerkhoff AD; MacPherson P; Meintjes G; Reither K; Ruhwald M; Global Health Institute, University of Antwerp, Wilrijk, Belgium.; Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom.; German Centre for Infection Research, Heidelberg University Hospital, Heidelberg, Germany.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Ifakara Health Institute, Dar es Salaam, Tanzania.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Taksin Hospital, Bangkok, Thailand.; Clinical Research Unit, Swiss Tropical and Public Health Institute, Allschwil, Switzerland.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California, San Francisco, San Francisco, California, USA.; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital and Faculty of Medicine, Heidelberg University, Heidelberg, Germany.; Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.; National Lung Hospital, Ha Noi, Viet Nam.; HIV Netherlands Australia Thailand Research Collaboration, Thai Red Cross AIDS Research Centre and Center of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.; University of Basel, Basel, Switzerland.; Foundation for Innovative New Diagnostics, the Global Alliance for Diagnostics, Geneva, Switzerland.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)BACKGROUND: CD4 measurement is pivotal in the management of advanced human immunodeficiency virus (HIV) disease. VISITECT CD4 Advanced Disease (VISITECT; AccuBio, Ltd) is an instrument-free, point-of-care, semiquantitative test allowing visual identification of CD4 ≤ 200 cells/µL or >200 cells/ µL from finger-prick or venous blood. METHODS: As part of a diagnostic accuracy study of FUJIFILM SILVAMP TB LAM, people with HIV ≥18 years old were prospectively recruited in 7 countries from outpatient departments if a tuberculosis symptom was present, and from inpatient departments. Participants provided venous blood for CD4 measurement using flow cytometry (reference standard) and finger-prick blood for VISITECT (index text), performed at point-of-care. Sensitivity, specificity, and positive and negative predictive values of VISITECT to determine CD4 ≤ 200 cells/ µL were evaluated. RESULTS: Among 1604 participants, the median flow cytometry CD4 was 367 cells/µL (interquartile range, 128-626 cells/µL) and 521 (32.5%) had CD4 ≤ 200 cells/µL. VISITECT sensitivity was 92.7% (483/521; 95% confidence interval [CI], 90.1%-94.7%) and specificity was 61.4% (665/1083; 95% CI, 58.4%-64.3%). For participants with CD4 0-100, 101-200, 201-300, 301-500, and >500 cells/µL, VISITECT misclassified 4.5% (95% CI, 2.5%-7.2%), 12.5 (95% CI, 8.0%-18.2%), 74.1% (95% CI, 67.0%-80.5%), 48.0% (95% CI, 42.5%-53.6%), and 22.6% (95% CI, 19.3%-26.3%), respectively. CONCLUSIONS: VISITECT's sensitivity, but not specificity, met the World Health Organization's minimal sensitivity and specificity threshold of 80% for point-of-care CD4 tests. VISITECT's quality needs to be assessed and its accuracy optimized. VISITECT's utility as CD4 triage test should be investigated. Clinical Trials Registration. NCT04089423.Item Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage.(2024-Oct) Geric C; Tavaziva G; Breuninger M; Dheda K; Esmail A; Scott A; Kagujje M; Muyoyeta M; Reither K; Khan AJ; Benedetti A; Ahmad Khan F; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada. Electronic address: faiz.ahmadkhan@mcgill.ca.; Tuberculosis Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia; Zambart, Lusaka, Zambia.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.; Swiss Tropical and Public Health Institute, Allschwill, Switzerland; University of Basel, Basel, Switzerland.; IRD Global, Singapore.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Canada.; Tuberculosis Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa; Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Division of Infectious Diseases, Department I of Internal Medicine, University of Cologne, Cologne, Germany.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)OBJECTIVES: Computer-aided detection (CAD) software packages quantify tuberculosis (TB)-compatible chest X-ray (CXR) abnormality as continuous scores. In practice, a threshold value is selected for binary CXR classification. We assessed the diagnostic accuracy of an alternative approach to applying CAD for TB triage: incorporating CAD scores in multivariable modeling. METHODS: We pooled individual patient data from four studies. Separately, for two commercial CAD, we used logistic regression to model microbiologically confirmed TB. Models included CAD score, study site, age, sex, human immunodeficiency virus status, and prior TB. We compared specificity at target sensitivities ≥90% between the multivariable model and the current threshold-based approach for CAD use. RESULTS: We included 4,733/5,640 (84%) participants with complete covariate data (median age 36 years; 45% female; 22% with prior TB; 22% people living with human immunodeficiency virus). A total of 805 (17%) had TB. Multivariable models demonstrated excellent performance (areas under the receiver operating characteristic curve [95% confidence interval]: software A, 0.91 [0.90-0.93]; software B, 0.92 [0.91-0.93]). Compared with threshold scores, multivariable models increased specificity (e.g., at 90% sensitivity, threshold vs model specificity [95% confidence interval]: software A, 71% [68-74%] vs 75% [74-77%]; software B, 69% [63-75%] vs 75% [74-77%]). CONCLUSION: Using CAD scores in multivariable models outperformed the current practice of CAD-threshold-based CXR classification for TB diagnosis.Item Urine-Xpert Ultra for the diagnosis of tuberculosis in people living with HIV: a prospective, multicentre, diagnostic accuracy study.(2024-Dec) Sossen B; Székely R; Mukoka M; Muyoyeta M; Nakabugo E; Hella J; Van Nguyen H; Ubolyam S; Erkosar B; Vermeulen M; Centner CM; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Nguyen NV; Avihingsanon A; Kerkhoff AD; Denkinger CM; Reither K; Nakiyingi L; MacPherson P; Meintjes G; Ruhwald M; Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland.; FIND, Geneva, Switzerland; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany; Faculty of Medicine, Heidelberg University, Heidelberg, Germany; German Centre for infection Research (DZIF), partner site Heidelberg University Hospital, Heidelberg, Germany.; FIND, Geneva, Switzerland.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi; School of Health and Wellbeing, University of Glasgow, Glasgow, UK; Clinical Research Department, London School of Hygiene & Tropical Medicine, London, UK.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Wellcome Center for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Ifakara Health Institute, Dar es Salaam, Tanzania.; FIND, Geneva, Switzerland. Electronic address: morten.ruhwald@finddx.org.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; Division of HIV, Infectious Diseases, and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, CA, USA.; Taksin Hospital, Bangkok, Thailand.; Wellcome Center for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Centre for Infectious Diseases Research in Zambia, Lusaka, Zambia.; National Lung Hospital, Ha Noi, Viet Nam.; HIV-NAT, Thai Red Cross AIDS Research Centre, Bangkok, Thailand; Center of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; Division of Medical Microbiology, University of Cape Town, Cape Town, South Africa; National Health Laboratory Service, Groote Schuur Hospital, Cape Town, South Africa.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)BACKGROUND: Diagnostic delays for tuberculosis are common, with high resultant mortality. Urine-Xpert Ultra (Cepheid) could improve time to diagnosis of tuberculosis disease and rifampicin resistance. We previously reported on lot-to-lot variation of the Fujifilm SILVAMP TB LAM. In this prespecified secondary analysis of the same cohort, we aimed to determine the diagnostic yield and accuracy of Urine-Xpert Ultra for tuberculosis in people with HIV, compared with an extended microbiological reference standard (eMRS) and composite reference standard (CRS) and also compared with Determine TB LAM Ag (AlereLAM, Abbott). METHODS: In this prospective, multicentre, diagnostic accuracy study, we recruited consecutive inpatients and outpatients (aged ≥18 years) with HIV from 13 hospitals and clinics in seven countries (Malawi, South Africa, Tanzania, Thailand, Uganda, Viet Nam, and Zambia). Patients with no isoniazid preventive therapy in the past 6 months and fewer than three doses of tuberculosis treatment in the past 60 days were included. Reference and index testing was performed in real time. The primary outcome of this secondary analysis was the diagnostic yield and accuracy of Urine-Xpert Ultra compared with the eMRS and CRS. Diagnostic accuracy was compared with AlereLAM and diagnostic yield was compared with both AlereLAM and Sputum-Xpert Ultra. This study was registered with ClinicalTrials.gov, NCT04089423, and is complete. FINDINGS: Between Dec 13, 2019, and Aug 5, 2021, 3528 potentially eligible individuals were screened and 1731 were enrolled, of whom 1602 (92·5%) were classifiable by the eMRS (median age 40 years [IQR 33-48], 838 [52·3%] of 1602 were female, 764 [47·7%] were male, 937 [58·5%] were outpatients, 665 [41·5%] were inpatients, median CD4 count was 374 cells per μL [IQR 138-630], and 254 [15·9%] had microbiologically confirmed tuberculosis). Against eMRS as reference, sensitivities of Urine-Xpert Ultra and AlereLAM were 32·7% (95% CI 27·2-38·7) and 30·7% (25·4-36·6) and specificities were 98·0% (97·1-98·6) and 90·4% (88·7-91·8), respectively. Against CRS as reference, sensitivities of Urine-Xpert Ultra and AlereLAM were 21·1% (95% CI 17·6-25·1), and 30·5% (26·4-34·9), and specificities were 99·1% (98·3-99·6) and 95·1% (93·5-96·3), respectively. The combination of Sputum-Xpert Ultra with AlereLAM or Urine-Xpert Ultra diagnosed 202 (77·1%) and 204 (77·9%) of 262 eMRS-positive participants, respectively, in incompletely overlapping groups; combining all three tests diagnosed 214 (81·7%) of 262 eMRS-positive participants INTERPRETATION: Urine-Xpert Ultra could offer promising clinical utility in addition to AlereLAM and Sputum-Xpert Ultra. In inpatient settings where both AlereLAM and Urine-Xpert Ultra are possible, both should be offered to support rapid diagnosis and treatment. FUNDING: Global Health Innovative Technology Fund, KfW Development Bank, Commonwealth of Australia represented by the Department of Foreign Affairs and Trade, and the Netherlands Enterprise Agency.Item Coverage of clinic-based TB screening in South Africa may be low in key risk groups.(2016-Mar-21) McCreesh N; Faghmous I; Looker C; Dodd PJ; Plumb ID; Shanaube K; Muyoyeta M; Godfrey-Faussett P; Ayles H; White RG; Department of Clinical Research, LSHTM, London, UK.; ZAMBART Project, School of Medicine, University of Zambia, Lusaka, Zambia ; Department of Clinical Research, LSHTM, London, UK.; TB Modelling Group, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine (LSHTM), London, UK ; Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK.; ZAMBART Project, School of Medicine, University of Zambia, Lusaka, Zambia ; TB Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; ZAMBART Project, School of Medicine, University of Zambia, Lusaka, Zambia.; TB Modelling Group, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine (LSHTM), London, UK.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)The South African Ministry of Health has proposed screening all clinic attendees for tuberculosis (TB). Amongst other factors, male sex and bar attendance are associated with higher TB risk. We show that 45% of adults surveyed in Western Cape attended a clinic within 6 months, and therefore potentially a relatively high proportion of the population could be reached through clinic-based screening. However, fewer than 20% of all men aged 18-25 years, or men aged 26-45 who attend bars, attended a clinic. The population-level impact of clinic-based screening may be reduced by low coverage among key risk groups.Item Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities.(2024-Oct) Kazemzadeh S; Kiraly AP; Nabulsi Z; Sanjase N; Maimbolwa M; Shuma B; Jamshy S; Chen C; Agharwal A; Lau CT; Sellergren A; Golden D; Yu J; Wu E; Matias Y; Chou K; Corrado GS; Shetty S; Tse D; Eswaran K; Liu Y; Pilgrim R; Muyoyeta M; Prabhakara S; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.; Advanced Clinical, Deerfield, IL.; Google, Mountain View, CA, USA.BACKGROUND: Using artificial intelligence (AI) to interpret chest X-rays (CXRs) could support accessible triage tests for active pulmonary tuberculosis (TB) in resource-constrained settings. METHODS: The performance of two cloud-based CXR AI systems - one to detect TB and the other to detect CXR abnormalities - in a population with a high TB and human immunodeficiency virus (HIV) burden was evaluated. We recruited 1978 adults who had TB symptoms, were close contacts of known TB patients, or were newly diagnosed with HIV at three clinical sites. The TB-detecting AI (TB AI) scores were converted to binary using two thresholds: a high-sensitivity threshold and an exploratory threshold designed to resemble radiologist performance. Ten radiologists reviewed images for signs of TB, blinded to the reference standard. Primary analysis measured AI detection noninferiority to radiologist performance. Secondary analysis evaluated AI detection as compared with the World Health Organization (WHO) targets (90% sensitivity, 70% specificity). Both used an absolute margin of 5%. The abnormality-detecting AI (abnormality AI) was evaluated for noninferiority to a high-sensitivity target suitable for triaging (90% sensitivity, 50% specificity). RESULTS: Of the 1910 patients analyzed, 1827 (96%) had conclusive TB status, of which 649 (36%) were HIV positive and 192 (11%) were TB positive. The TB AI's sensitivity and specificity were 87% and 70%, respectively, at the high-sensitivity threshold and 78% and 82%, respectively, at the balanced threshold. Radiologists' mean sensitivity was 76% and mean specificity was 82%. At the high-sensitivity threshold, the TB AI was noninferior to average radiologist sensitivity (P<0.001) but not to average radiologist specificity (P=0.99) and was higher than the WHO target for specificity but not sensitivity. At the balanced threshold, the TB AI was comparable to radiologists. The abnormality AI's sensitivity and specificity were 97% and 79%, respectively, with both meeting the prespecified targets. CONCLUSIONS: The CXR TB AI was noninferior to radiologists for active pulmonary TB triaging in a population with a high TB and HIV burden. Neither the TB AI nor the radiologists met WHO recommendations for sensitivity in the study population. AI can also be used to detect other CXR abnormalities in the same population.Item Point-of-Care Urine Ethyl Glucuronide Testing to Detect Alcohol Use Among HIV-Hepatitis B Virus Coinfected Adults in Zambia.(2018-Jul) Vinikoor MJ; Zyambo Z; Muyoyeta M; Chander G; Saag MS; Cropsey K; Centre for Infectious Disease Research in Zambia, 5032 Great North Road, PO Box 34681, Lusaka, Zambia.; Department of Medicine, University of Alabama at Birmingham, Birmingham, USA.; Centre for Infectious Disease Research in Zambia, 5032 Great North Road, PO Box 34681, Lusaka, Zambia. mjv3@uab.edu.; Department of Medicine, University of Alabama at Birmingham, Birmingham, USA. mjv3@uab.edu.; Department of Medicine, Johns Hopkins University, Baltimore, USA.; School of Medicine, University of Zambia, Lusaka, Zambia.; Department of Psychiatry, University of Alabama at Birmingham, Birmingham, USA.; School of Medicine, University of Zambia, Lusaka, Zambia. mjv3@uab.edu.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)In an HIV-hepatitis B virus (HIV-HBV) coinfection cohort in Zambia, we piloted a qualitative point-of-care (POC) test for urine Ethyl glucuronide (uEtG), assessed concordance between uEtG and alcohol use disorders identification test-consumption (AUDIT-C), and identified epidemiological factors associated with underreporting (defined as uEtG-positivity with last reported drink > 7 days prior). Among 211 participants (40.8% women), there were 44 (20.8%) lifetime abstainers, 32 (15.2%) former drinkers, and 135 (64.0%) current drinkers, including 106 (50.2%) with unhealthy drinking per AUDIT-C. Eighty-seven (41.2%) were uEtG-positive including 64 of 65 (98.5%) who drank ≤ 3 days prior and 17 of 134 (12.7%) underreported, all of whom admitted to recent drinking when results were discussed. uEtG was moderately concordant with AUDIT-C. Past drinking (versus lifetime abstinence) and longer time on antiretrovirals (≥ 12 months) were associated with underreporting. These data support further use of POC alcohol biomarkers in HIV and hepatitis research and clinical settings.