Development of a hematological risk stratification model for predicting mortality in dengue hemorrhagic fever patients

Abstract

Dengue Hemorrhagic Fever (DHF) continues to be a major global public health concern, particularly in tropical and subtropical regions, where it contributes to significant morbidity and mortality. Early identification of patients at risk of severe outcomes or death remains a clinical challenge in resource-limited settings. Hematological indicators, which are routinely assessed in dengue management, may provide valuable prognostic information. This study aimed to develop a hematological risk stratification model to predict mortality in DHF patients using simple and widely available clinical and laboratory parameters. A retrospective analysis was conducted using medical records of confirmed DHF patients (n = 120) treated at Labuang Baji Regional General Hospital (RSUD Labuang Baji), Makassar, South Sulawesi, Indonesia, between January and December 2023. Patients were classified into two outcome groups—recovered and deceased. Independent variables included age, leukocyte count, neutrophil count, lymphocyte count, monocyte level, and DHF clinical grade based on the World Health Organization (WHO) criteria. Descriptive statistics, bivariate comparisons, and multivariate logistic regression were performed to identify independent predictors of mortality and construct a hematological risk stratification model. The analysis revealed that non-survivors were generally older (mean 40 years) and exhibited significantly lower leukocyte (1.06 ×10³/µL) and neutrophil counts (0.42 ×10³/µL) compared to survivors (mean age 31 years, leukocyte 5.05 ×10³/µL, neutrophil 3.20 ×10³/µL). The mean DHF grade was higher among those who died (3.0) compared to those who recovered (1.4), indicating greater disease severity. Logistic regression identified leukocyte count, neutrophil count, and DHF clinical grade as independent predictors of mortality, and these variables were integrated into a predictive model with good discriminatory accuracy (AUC = 0.892). The proposed hematological risk stratification model offers a practical, evidence-based tool for early identification of high-risk DHF patients using basic laboratory indicators. Its application may enhance clinical decision-making, support timely interventions, and improve survival outcomes in dengue-endemic healthcare settings.

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