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Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray
BACKGROUND: Cambodia has one of the highest tuberculosis (TB) prevalence rates in the world. People aged 55 years and over account for an estimated 50% of the country's TB burden, yet this group has a low notification rate owing to specific barriers in accessing health services. One-off active...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830163/ https://www.ncbi.nlm.nih.gov/pubmed/31720408 http://dx.doi.org/10.1016/j.jctube.2018.11.001 |
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author | Codlin, Andrew James Monyrath, Chry Ky, Mom Gerstel, Lisanne Creswell, Jacob Eang, Mao Tan |
author_facet | Codlin, Andrew James Monyrath, Chry Ky, Mom Gerstel, Lisanne Creswell, Jacob Eang, Mao Tan |
author_sort | Codlin, Andrew James |
collection | PubMed |
description | BACKGROUND: Cambodia has one of the highest tuberculosis (TB) prevalence rates in the world. People aged 55 years and over account for an estimated 50% of the country's TB burden, yet this group has a low notification rate owing to specific barriers in accessing health services. One-off active case finding (ACF) days with mobile GeneXpert and X-ray systems were organized at 75 government health facilities in four operational districts. Symptomatic community members with an abnormal chest X-ray were tested using the Xpert MTB/RIF assay. People with TB were then treated at health facilities after screening services moved onto the next site. METHODS: De-identified project data were analysed to produce descriptive statistics about the people tested on Xpert and those diagnosed with TB. A linear regression was fit through the 12 quarters of National TB Program (NTP) TB case notification data immediately prior to ACF. The regression was used to calculate trend-expected notifications during and after the ACF quarters. Notifications from the ACF quarters were then compared to actual notifications from the previous year and to the trend-expected notifications during the ACF quarter by age group and type of TB. Finally, NTP TB treatment outcomes for the patients started on treatment during the ACF quarter were compared to those from a year prior. RESULTS: 2068 individuals submitted sputum for Xpert MTB/RIF testing, resulting in the identification of 319 (15.4%) bacteriologically-positive TB patients and an additional 574 people who were clinically diagnosed with TB. In the ACF quarters, new bacteriologically-positive notifications increased +119.2% for all ages and +262.7% for people aged 55 and over compared with trend-expected notifications. Treatment initiation figures remained above trend-expected notifications for three full quarters after ACF. The treatment success rate across all operational districts was significantly higher for patients detected in the ACF quarters (88.8% vs 94.5%, p = 0.012). CONCLUSION: A series of roving, one-off ACF days at government health facilities were able to increase TB diagnosis, treatment initiation and treatment outcomes in a key population with high TB prevalence. Targeted ACF interventions such as this could be used to reduce a backlog of untreated, prevalent TB. |
format | Online Article Text |
id | pubmed-6830163 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68301632019-11-12 Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray Codlin, Andrew James Monyrath, Chry Ky, Mom Gerstel, Lisanne Creswell, Jacob Eang, Mao Tan J Clin Tuberc Other Mycobact Dis Article BACKGROUND: Cambodia has one of the highest tuberculosis (TB) prevalence rates in the world. People aged 55 years and over account for an estimated 50% of the country's TB burden, yet this group has a low notification rate owing to specific barriers in accessing health services. One-off active case finding (ACF) days with mobile GeneXpert and X-ray systems were organized at 75 government health facilities in four operational districts. Symptomatic community members with an abnormal chest X-ray were tested using the Xpert MTB/RIF assay. People with TB were then treated at health facilities after screening services moved onto the next site. METHODS: De-identified project data were analysed to produce descriptive statistics about the people tested on Xpert and those diagnosed with TB. A linear regression was fit through the 12 quarters of National TB Program (NTP) TB case notification data immediately prior to ACF. The regression was used to calculate trend-expected notifications during and after the ACF quarters. Notifications from the ACF quarters were then compared to actual notifications from the previous year and to the trend-expected notifications during the ACF quarter by age group and type of TB. Finally, NTP TB treatment outcomes for the patients started on treatment during the ACF quarter were compared to those from a year prior. RESULTS: 2068 individuals submitted sputum for Xpert MTB/RIF testing, resulting in the identification of 319 (15.4%) bacteriologically-positive TB patients and an additional 574 people who were clinically diagnosed with TB. In the ACF quarters, new bacteriologically-positive notifications increased +119.2% for all ages and +262.7% for people aged 55 and over compared with trend-expected notifications. Treatment initiation figures remained above trend-expected notifications for three full quarters after ACF. The treatment success rate across all operational districts was significantly higher for patients detected in the ACF quarters (88.8% vs 94.5%, p = 0.012). CONCLUSION: A series of roving, one-off ACF days at government health facilities were able to increase TB diagnosis, treatment initiation and treatment outcomes in a key population with high TB prevalence. Targeted ACF interventions such as this could be used to reduce a backlog of untreated, prevalent TB. Elsevier 2018-11-12 /pmc/articles/PMC6830163/ /pubmed/31720408 http://dx.doi.org/10.1016/j.jctube.2018.11.001 Text en © 2018 The Authors. Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Codlin, Andrew James Monyrath, Chry Ky, Mom Gerstel, Lisanne Creswell, Jacob Eang, Mao Tan Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray |
title | Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray |
title_full | Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray |
title_fullStr | Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray |
title_full_unstemmed | Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray |
title_short | Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray |
title_sort | results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the xpert mtb/rif assay and chest x-ray |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830163/ https://www.ncbi.nlm.nih.gov/pubmed/31720408 http://dx.doi.org/10.1016/j.jctube.2018.11.001 |
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