Development and validation of a novel critical risk stratification scale for hemorrhagic fever with renal syndrome patients with Hantaan virus infection.

OBJECTIVES

To develop and validate a critical risk prediction model for hemorrhagic fever with renal syndrome caused by Hantaan virus.

METHODS

Patients were randomly divided into a training group (n = 344) and a validation group (n = 226). Clinical data were gathered and analyzed. Logistic regression analysis was employed to construct a nomogram-based prediction model, which was subsequently simplified into a novel scoring scale. The calibration curve, receiver operating characteristic curve, and decision curve analysis were used to assess the model's calibration, discrimination, accuracy, and clinical applicability in both the training and validation cohorts.

RESULTS

Hypotensive shock, myoglobin, and neutrophils counts were identified as independent predictors of critical risk. Based on these three predictors, a nomogram prediction model was developed and subsequently simplified into a scoring scale. The model demonstrated predictive performance in both the training cohort and the validation cohort (area under the receiver operating characteristic curve >0.8). Furthermore, the calibration of the scoring scale and the nomogram was satisfactory (P >0.05). Decision curve analysis revealed that the model provided significant net clinical benefit within the risk threshold range of 0-90%.

CONCLUSIONS

We developed and validated the first prediction model for critically ill hemorrhagic fever with renal syndrome patients, which will aid clinicians in clinical decision-making.