Diagnostic accuracy of automation and non-automation techniques for identifying Burkholderia pseudomallei: A systematic review and meta-analysis

Jirarat Songsri; Moragot Chatatikun; Sueptrakool Wisessombat; Wanida Mala; Preeda Phothaworn; Wilaiwan Senghoi; Wilawan Palachum; Wetpisit Chanmol; Nuchpicha Intakhan; Sirithip Chuaijit; Pakpoom Wongyikul; Phichayut Phinyo; Kenshi Yamasaki; Anchalee Chittamma; Wiyada Kwanhian Klangbud

Journal of Infection and Public Health (Jul 2024)

Diagnostic accuracy of automation and non-automation techniques for identifying Burkholderia pseudomallei: A systematic review and meta-analysis

Jirarat Songsri,
Moragot Chatatikun,
Sueptrakool Wisessombat,
Wanida Mala,
Preeda Phothaworn,
Wilaiwan Senghoi,
Wilawan Palachum,
Wetpisit Chanmol,
Nuchpicha Intakhan,
Sirithip Chuaijit,
Pakpoom Wongyikul,
Phichayut Phinyo,
Kenshi Yamasaki,
Anchalee Chittamma,
Wiyada Kwanhian Klangbud

Affiliations

Jirarat Songsri: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Moragot Chatatikun: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Sueptrakool Wisessombat: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Wanida Mala: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Preeda Phothaworn: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Wilaiwan Senghoi: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Wilawan Palachum: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Wetpisit Chanmol: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Nuchpicha Intakhan: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; Medical Technology Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
Sirithip Chuaijit: Center of Excellence Research for Melioidosis and Microorganisms (CERMM), Walailak University, Nakhon Si Thammarat, Thailand; School of Medicine, Walailak University, Nakhon Si Thammarat, Thailand
Pakpoom Wongyikul: Center for Clinical Epidemiology and Clinical Statistics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand; Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
Phichayut Phinyo: Center for Clinical Epidemiology and Clinical Statistics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand; Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
Kenshi Yamasaki: Department of Dermatology, Graduate School of Medicine, Tohoku University, Sendai, Japan
Anchalee Chittamma: Division of Clinical Chemistry, Department of Pathology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
Wiyada Kwanhian Klangbud: Medical Technology program, Faculty of Science, Nakhon Phanom University, Nakhon Phanom, Thailand; Corresponding author.

Journal volume & issue: Vol. 17, no. 7
p. 102438

Abstract

Read online

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. 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 I2 statistics. 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%). 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.

Published in Journal of Infection and Public Health

ISSN: 1876-0341 (Print); 1876-035X (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Medicine: Internal medicine: Infectious and parasitic diseases; Medicine: Public aspects of medicine
Website: https://www.journals.elsevier.com/journal-of-infection-and-public-health

About the journal

Abstract

Keywords