Development and external validation of a nomogram incorporating the TyG index and prognostic nutritional index for predicting cardiovascular events in patients with heart failure with preserved ejection fraction and chronic kidney disease

Background Heart failure with preserved ejection fraction (HFpEF) frequently coexists with chronic kidney disease (CKD), representing a high-risk cardiorenal phenotype within the cardiovascular–kidney–metabolic (CKM) syndrome. Despite the high burden of adverse cardiovascular events in this population, dedicated risk prediction tools remain limited. We aimed to develop and validate a prediction model for major adverse cardiovascular events (MACE), defined in this study as the composite of all-cause death and first hospitalization for worsening heart failure, in patients with HFpEF and CKD by integrating biomarkers reflecting metabolic and nutritional-inflammatory status. Methods This retrospective cohort study included a development cohort of 2,363 consecutive patients with HFpEF and CKD between January 2012 and December 2023. The development cohort was randomly divided into a training cohort (70%) and an internal validation cohort (30%). An independent cohort of 713 patients from Wenzhou TCM Hospital of Zhejiang Chinese Medical University was used for external validation. Predictor selection was performed using Cox proportional hazards regression, and a nomogram was constructed based on the final multivariable model. Model performance was evaluated using time-dependent receiver operating characteristic curves, calibration plots, decision curve analysis, and Shapley additive explanations (SHAP). Results During a median follow-up of 1.41 years, 1,085 patients (45.9%) experienced MACE. The final multivariable model retained age, atrial fibrillation, ACEI/ARB/ARNI therapy, serum creatinine, mean E/e’, pulmonary arterial systolic pressure, triglyceride–glucose (TyG) index, and prognostic nutritional index (PNI). The nomogram showed good discrimination in the training cohort (AUC 0.764, 0.825, and 0.813 for predicting 1-, 3-, and 5-year MACE, respectively) and in the internal validation cohort (AUC 0.724, 0.757, and 0.868). Calibration analysis demonstrated good agreement between predicted and observed outcomes, and decision curve analysis indicated favorable clinical utility. The SHAP analysis highlighted key predictors. Benchmark comparison with the MAGGIC score showed higher time-dependent AUCs for the proposed model in the internal validation cohort. In the independent external validation cohort, the 1-, 3-, and 5-year AUC values were 0.800, 0.804, and 0.831, respectively. Calibration and decision curve analyses demonstrated generally acceptable agreement and clinically relevant net benefit. Conclusion A nomogram incorporating the TyG index and prognostic nutritional index demonstrated promising predictive performance for MACE in patients with HFpEF and CKD. These markers may provide complementary prognostic information beyond conventional clinical predictors. Further prospective, multicenter, and geographically diverse validation is required before clinical implementation.