Performance of algorithms for tuberculosis active case finding in underserved high-prevalence settings in Cambodia
A cross-sectional study
Bibliographic Data
| ID | 19529552 |
|---|---|
| Authors | Kimcheng Choun (Sihanouk Hospital Center of HOPE, corresponding author), Tom Decroo (0000-0002-1205-1484, Research Foundation - Flanders), Tan Eang Mao (Cambodia National Malaria Center), Natalie Lorent (0000-0002-2653-5885, KU Leuven), Lisanne Gerstel (0000-0002-2137-3282, Royal Tropical Institute), Jacob Creswell (0000-0002-4885-940X, Stop TB Partnership, Geneva, Switzerland), Andrew James Codlin (0000-0003-1380-8300), Lutgarde Lynen (0000-0001-7183-4895, Instituut voor Tropische Geneeskunde), Sopheak Thai (Sihanouk Hospital Center of HOPE) |
| Year | 2019 |
| Volume | 12 |
| Issue | 1 |
| Pages | 1646024 |
| Publication date | 2019-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Global Health Action (JOURNAL) |
| Journal identifiers | ISSN: 1654-9716 • E-ISSN: 1654-9880 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/16549716.2019.1646024 |
| PMID | 31500551 |
| OpenAlex | W2971923365 |
| Language | EN |
| Citations received | 1 |
| References cited | 18 |
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
Algorithm · Case finding · Confidence interval · Cross-sectional study · Number needed to treat · Pathology · Pulmonary tuberculosis · Relative risk · Sputum · Tuberculosis · COVID-19 diagnosis using AI · Digital Imaging for Blood Diseases · Medicine · Tuberculosis Research and Epidemiology · Internal Medicine
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2021 - 2021 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |