A prediction model for mortality risk in melioidosis patients based on clinical and laboratory indicators: A single-center retrospective study.

Melioidosis, caused by Burkholderia pseudomallei, carries a high mortality rate, particularly in acute severe cases. This study aimed to develop a practical prediction model for in-hospital mortality using routinely available clinical data. We retrospectively analyzed 283 melioidosis patients from Hainan General Hospital (2010-2024). Compared to survivors, non-survivors had significantly higher neutrophil percentage, C-reactive protein (CRP), and urea nitrogen levels, and lower platelet counts (PLT) (all P < 0.05) based on the last available measurements during hospitalization. Multivariate logistic regression identified these four variables as independent risk factors for mortality. A combined model integrating neutrophil percentage, PLT, CRP, and urea nitrogen demonstrated outstanding discriminative performance, with an area under the curve (AUC) of 0.957 (95% CI: 0.925-0.989), sensitivity of 94.9%, and specificity of 86.4%, significantly outperforming any single indicator. This high-accuracy model, based on inexpensive and universally available parameters, shows great potential for risk assessment during hospitalization of melioidosis patients in resource-limited endemic settings, facilitating timely intensive intervention.