Predictors of in-hospital mortality by logistic regression analysis among melioidosis patients in Northern Malaysia: A retrospective study

Abstract

Objective: To identify the predictors of mortality among in-hospital melioidosis patients. Methods: A total of 453 patients in Hospital Sultanah Bahiyah, Kedah, and Hospital Tuanku Fauziah, Perlis with culture-confirmed melioidosis were retrospectively included in the study. Advanced multiple logistic regression was used to obtain the final model of predictors of mortality from melioidosis. The analysis was performed using STATA/SE 14.0. Results: A total of 50.11% (227/453) of the patients died at the hospital, and a majority (86.75%, 393/453) of cases were bacteremic. The logistic regression estimated that the bacteremic type of melioidosis, low platelet count, abnormal white blood cell counts, and increased urea value were predictors of mortality. The results showed that bacteremic melioidosis increased the risk of death by 4.39 times (OR 4.39, 95% CI 1.83-10.55, P=0.001) compared to non-bacteremic melioidosis. Based on laboratory test, the adjusted ORs from the final model showed that all three blood investigations were included as the associated factors of mortality for the disease [high white blood cell (>10×109/L): OR 2.43, 95% CI 1.41-4.17, P7 800 μmol/L): OR 5.53, 95% CI 2.50-12.30, P<0.001; and low level of urea (<2 500 μmol/L): OR 3.52, 95% CI 1.71-7.23, P=0.001). Conclusions: Routine blood investigations during a hospital admission can early identify predictors of mortality in melioidosis patients.

Keywords

• melioidosis; infectious disease; mortality; predictors; prognostic factors; logistic model