Multicenter validation of a simple clinical risk score for early prediction of severe dengue among adults in Thailand

Dengue remains a major public health challenge in Thailand. Although only a minority of patients progress to severe dengue, the condition is potentially life-threatening and requires early recognition. Simple clinical prediction tools may support early risk stratification in routine care, particularly in resource-limited settings. This study aimed to externally validate a simple clinical risk score for predicting severe dengue among adult patients using multicenter hospital data in Thailand. A retrospective multicenter validation study was conducted using clinical data from six hospitals in Thailand (2019–2022). Model discrimination was assessed using the area under the receiver operating characteristic curve (AuROC). Patients were categorized into three predefined risk groups. Likelihood ratios were calculated to evaluate clinical utility across risk strata. Calibration was assessed using calibration plots, slope, and intercept. The model demonstrated good discriminative performance, with an AuROC of 0.83 (95% CI 0.77–0.90) in the validation cohort, compared with 0.88 in the development cohort (p-value = 0.249). Likelihood ratios indicated strong rule-in ability in the high-risk group (LR + = 52.02), while the low-risk group was associated with reduced probability of severe disease. Calibration was acceptable overall, although systematic underestimation was observed in higher-risk patients. This simple clinical risk score demonstrated good and stable performance across diverse hospital settings. The model may support early in-hospital risk stratification and clinical monitoring decisions among adult dengue patients. Further prospective validation and recalibration studies are warranted. Not applicable.