%0 Journal Article
%T Diagnostic accuracy of automation and non-automation techniques for identifying Burkholderia pseudomallei: A systematic review and meta-analysis.
%A Songsri J
%A Chatatikun M
%A Wisessombat S
%A Mala W
%A Phothaworn P
%A Senghoi W
%A Palachum W
%A Chanmol W
%A Intakhan N
%A Chuaijit S
%A Wongyikul P
%A Phinyo P
%A Yamasaki K
%A Chittamma A
%A Klangbud WK
%J J Infect Public Health
%V 17
%N 7
%D 2024 Jul 26
%M 38820898
%F 7.537
%R 10.1016/j.jiph.2024.04.022
%X <B>BACKGROUND: </B>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><B>METHODS: </B>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 I2 statistics.<BR><B>RESULTS: </B>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><B>CONCLUSIONS: </B>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.