Construction of a risk prediction model for coagulation during continuous renal replacement therapy with nafamostat mesylate anticoagulation

To identify risk factors affecting the filter lifespan during CRRT (continuous renal replacement therapy) with nafamostat mesylate anticoagulation and to construct a Cox proportional hazards prediction model. A total of 105 patients undergoing 230 CRRT sessions in our hospital between December 2023 and February 2025 were retrospectively analyzed. Cox regression analysis was used to identify predictive variables, and a multivariate Cox proportional hazards model was developed. A nomogram was constructed, and the model’s discriminatory ability and predictive performance were evaluated using receiver operating characteristic (ROC) curves. In the univariable analysis, four variables were identified as significant predictors of filter clotting: activated partial thromboplastin time (APTT), hematocrit (HCT), type 2 diabetes mellitus (T2DM), and heparinized saline priming of the circuit. Other variables were not statistically significant (P > 0.05).Based on the variables included in the univariable analysis, together with one additional clinically relevant variable identified through literature review and expert consultation (subcutaneous injection of low-molecular-weight heparin, 4000 IU/day), a multivariable Cox proportional hazards model was constructed and analyzed. The results showed that three variables remained statistically significant in the multivariable analysis and were identified as independent predictors, while APTT was not statistically significant in the multivariable model.The constructed nomogram demonstrated good predictive performance, with areas under the curve (AUCs) of 0.791, 0.760, and 0.747 for predicting filter clotting risk at 24, 48, and 60 hours, respectively. A Cox proportional hazards prediction model was successfully developed for filter clotting during CRRT with NM anticoagulation. The model demonstrated good predictive performance and may help identify high-risk patients at an early stage, providing a valuable reference for preventing and managing filter clotting events.