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Diagnostic accuracy of automation and non-automation techniques for identifying Burkholderia pseudomallei: A systematic review and meta-analysis.
- Source :
-
Journal of infection and public health [J Infect Public Health] 2024 Jul; Vol. 17 (7), pp. 102438. Date of Electronic Publication: 2024 Apr 26. - Publication Year :
- 2024
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Abstract
- Background: Burkholderia pseudomallei, a Gram-negative pathogen, causes melioidosis. Although various clinical laboratory identification methods exist, culture-based techniques lack comprehensive evaluation. Thus, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of culture-based automation and non-automation methods.<br />Methods: Data were collected via PubMed/MEDLINE, EMBASE, and Scopus using specific search strategies. Selected studies underwent bias assessment using QUADAS-2. Sensitivity and specificity were computed, generating pooled estimates. Heterogeneity was assessed using I <superscript>2</superscript> statistics.<br />Results: The review encompassed 20 studies with 2988 B. pseudomallei samples and 753 non-B. pseudomallei samples. Automation-based methods, particularly with updating databases, exhibited high pooled sensitivity (82.79%; 95% CI 64.44-95.85%) and specificity (99.94%; 95% CI 98.93-100.00%). Subgroup analysis highlighted superior sensitivity for updating-database automation (96.42%, 95% CI 90.01-99.87%) compared to non-updating (3.31%, 95% CI 0.00-10.28%), while specificity remained high at 99.94% (95% CI 98.93-100%). Non-automation methods displayed varying sensitivity and specificity. In-house latex agglutination demonstrated the highest sensitivity (100%; 95% CI 98.49-100%), followed by commercial latex agglutination (99.24%; 95% CI 96.64-100%). However, API 20E had the lowest sensitivity (19.42%; 95% CI 12.94-28.10%). Overall, non-automation tools showed sensitivity of 88.34% (95% CI 77.30-96.25%) and specificity of 90.76% (95% CI 78.45-98.57%).<br />Conclusion: The study underscores automation's crucial role in accurately identifying B. pseudomallei, supporting evidence-based melioidosis management decisions. Automation technologies, especially those with updating databases, provide reliable and efficient identification.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1876-035X
- Volume :
- 17
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Journal of infection and public health
- Publication Type :
- Academic Journal
- Accession number :
- 38820898
- Full Text :
- https://doi.org/10.1016/j.jiph.2024.04.022