Development and validation of a novel critical risk stratification scale for HFRS patients with Hantaan virus infection

Background. This study aims to develop and validate a critical risk prediction model for hemorrhagic fever with renal syndrome (HFRS) caused by Hantaan virus across Eurasia. Methods. Clinical data of 570 HFRS patients from Xi'an Eighth Hospital from 2022 to 2023 were collected and randomly divided into a training group (n=344) and a validation group (n=226). The proposed model integrated patient clinical characteristics with multi-dimensional laboratory test results. 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, age distribution, thrombin-antithrombin complex, total calcium, and neutrophils counts were identified as independent predictors of critical risk. Based on these five 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 (AUROC > 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% to 80%. Conclusion. The first prediction model for critically-illed HFRS patients was developed and validated, which will aid clinicians in clinical decision-making.