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Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study

Background: Most studies evaluate active case findings (ACF) for bacteriologically confirmed TB. Adapted diagnostic approaches are needed to identify cases with lower bacillary loads. Objectives: To assess the likelihood of diagnosing all forms of TB, including clinically diagnosed pulmonary and ext...

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Autores principales: Choun, Kimcheng, Decroo, Tom, Mao, Tan Eang, Lorent, Natalie, Gerstel, Lisanne, Creswell, Jacob, Codlin, Andrew J., Lynen, Lutgarde, Thai, Sopheak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735356/
https://www.ncbi.nlm.nih.gov/pubmed/31500551
http://dx.doi.org/10.1080/16549716.2019.1646024
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author Choun, Kimcheng
Decroo, Tom
Mao, Tan Eang
Lorent, Natalie
Gerstel, Lisanne
Creswell, Jacob
Codlin, Andrew J.
Lynen, Lutgarde
Thai, Sopheak
author_facet Choun, Kimcheng
Decroo, Tom
Mao, Tan Eang
Lorent, Natalie
Gerstel, Lisanne
Creswell, Jacob
Codlin, Andrew J.
Lynen, Lutgarde
Thai, Sopheak
author_sort Choun, Kimcheng
collection PubMed
description Background: Most studies evaluate active case findings (ACF) for bacteriologically confirmed TB. Adapted diagnostic approaches are needed to identify cases with lower bacillary loads. Objectives: To assess the likelihood of diagnosing all forms of TB, including clinically diagnosed pulmonary and extra-pulmonary TB, using different ACF algorithms in Cambodia. Methods: Clients were stratified into ‘high-risk’ (presumptive TB plus TB contact, or history of TB, or presumptive HIV infection; n = 12,337) and ‘moderate-risk’ groups (presumptive TB; n = 28,804). Sputum samples were examined by sputum smear microscopy (SSM) or Xpert MTB/RIF (Xpert). Initially, chest X-ray using a mobile radiography unit was a follow-up test after a negative sputum examination [algorithms A (Xpert/X-ray) and B (SSM/X-ray)]. Subsequently, all clients received an X-ray [algorithms C (X-ray+Xpert) and D (Xray+SSM/Xpert)]. X-rays were interpreted on the spot. Results: Between 25 August 2014 and 31 March 2016, 2217 (5.4%) cases with all forms of TB cases were diagnosed among 41,141 adults. The majority of TB cases (1488; 67.1%) were diagnosed using X-ray. When X-rays were taken and interpreted the same day the sputum was collected, same-day diagnosis more than doubled. Overall, the number needed to test (NNT) to diagnose one case was 18.6 (95%CI:17.9–19.2). In the high-risk group the NNT was lower [algorithm D: NNT = 17.3(15.9–18.9)] compared with the ‘moderate-risk group’ [algorithm D: NNT = 20.8(19.6–22.2)]. In the high-risk group the NNT was lower when using Xpert as an initial test [algorithm A: NNT = 12.2(10.8–13.9) or algorithm C: NNT = 11.2(9.6–13.0)] compared with Xpert as a follow-up test [algorithm D: NNT = 17.3(15.9–18.9)]. Conclusion: To diagnose all TB forms, X-ray should be part of the diagnostic algorithm. The combination of X-ray and Xpert testing for high-risk clients was the most effective ACF approach in this setting.
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spelling pubmed-67353562019-09-16 Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study Choun, Kimcheng Decroo, Tom Mao, Tan Eang Lorent, Natalie Gerstel, Lisanne Creswell, Jacob Codlin, Andrew J. Lynen, Lutgarde Thai, Sopheak Glob Health Action Original Article Background: Most studies evaluate active case findings (ACF) for bacteriologically confirmed TB. Adapted diagnostic approaches are needed to identify cases with lower bacillary loads. Objectives: To assess the likelihood of diagnosing all forms of TB, including clinically diagnosed pulmonary and extra-pulmonary TB, using different ACF algorithms in Cambodia. Methods: Clients were stratified into ‘high-risk’ (presumptive TB plus TB contact, or history of TB, or presumptive HIV infection; n = 12,337) and ‘moderate-risk’ groups (presumptive TB; n = 28,804). Sputum samples were examined by sputum smear microscopy (SSM) or Xpert MTB/RIF (Xpert). Initially, chest X-ray using a mobile radiography unit was a follow-up test after a negative sputum examination [algorithms A (Xpert/X-ray) and B (SSM/X-ray)]. Subsequently, all clients received an X-ray [algorithms C (X-ray+Xpert) and D (Xray+SSM/Xpert)]. X-rays were interpreted on the spot. Results: Between 25 August 2014 and 31 March 2016, 2217 (5.4%) cases with all forms of TB cases were diagnosed among 41,141 adults. The majority of TB cases (1488; 67.1%) were diagnosed using X-ray. When X-rays were taken and interpreted the same day the sputum was collected, same-day diagnosis more than doubled. Overall, the number needed to test (NNT) to diagnose one case was 18.6 (95%CI:17.9–19.2). In the high-risk group the NNT was lower [algorithm D: NNT = 17.3(15.9–18.9)] compared with the ‘moderate-risk group’ [algorithm D: NNT = 20.8(19.6–22.2)]. In the high-risk group the NNT was lower when using Xpert as an initial test [algorithm A: NNT = 12.2(10.8–13.9) or algorithm C: NNT = 11.2(9.6–13.0)] compared with Xpert as a follow-up test [algorithm D: NNT = 17.3(15.9–18.9)]. Conclusion: To diagnose all TB forms, X-ray should be part of the diagnostic algorithm. The combination of X-ray and Xpert testing for high-risk clients was the most effective ACF approach in this setting. Taylor & Francis 2019-09-05 /pmc/articles/PMC6735356/ /pubmed/31500551 http://dx.doi.org/10.1080/16549716.2019.1646024 Text en © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Choun, Kimcheng
Decroo, Tom
Mao, Tan Eang
Lorent, Natalie
Gerstel, Lisanne
Creswell, Jacob
Codlin, Andrew J.
Lynen, Lutgarde
Thai, Sopheak
Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study
title Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study
title_full Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study
title_fullStr Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study
title_full_unstemmed Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study
title_short Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia: a cross-sectional study
title_sort performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in cambodia: a cross-sectional study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735356/
https://www.ncbi.nlm.nih.gov/pubmed/31500551
http://dx.doi.org/10.1080/16549716.2019.1646024
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