218. Development of a Simple Score for Diagnosis Melioidosis

BACKGROUND: Melioidosis is a common gram-negative bacterial infection in northeastern Thailand. Patients with melioidosis infections often experience severe conditions and high mortality rates. This study aims to develop a clinical prediction model to estimate the risk of melioidosis septicemia. METHODS: This retrospective case-control study included patients with positive hemoculture for Burkholderia pseudomallei (BP) and other gram-negative bacteria (Escherichia coli, and Klebsiella pneumoniae) admitted to Srinagarind Hospital between January 2015 and December 2020. Logistic regression analyses were used to determine the calculation of a score for diagnosing melioidosis infection. RESULTS: A total of 426 patients with positive hemoculture were included: 132 patients for BP and 294 patients for other gram-negative bacteria. The clinical prediction model for diagnosing melioidosis utilized seven variables: age ≥ 60 years (-2 points), male gender (3 points), duration of symptom onset to hospitalization ≥ 7 days (5 points), occupation as a farmer (3 points), presence of diabetes mellitus (2 points), presence of cancer (-5 points), and platelet count (x 10(9)/L) (200-399.9: 1 point, ≥400: 3 points). The model demonstrated good discrimination (area under the curve: 0.89; 95% CI: 0.86-0.93) and acceptable calibration (Hosmer and Lemeshow goodness of fit test: P-value of 0.252). A cut-off point of the melioidosis score ≥ 5 points (maximum score = 16 and minimum score = -7) resulted in an accuracy of 84.3% (95%CI 80.5-87.6), a sensitivity of 78.8%, and a specificity of 86.7%. [Figure: see text] [Figure: see text] [Figure: see text] CONCLUSION: The melioidosis score exhibited high performance and clinical utility in predicting melioidosis infection. DISCLOSURES: All Authors: No reported disclosures