RESUMO
AIMS: For type 2 diabetes persons, we assessed the association between renal function decline and heart failure hospitalisation (HFH) and validated dynamic HFH predictions (DynHFH) based on repeated estimated Glomerular Filtration Rate (eGFR) values. METHODS: We studied 1413 patients from the SURDIAGENE cohort. From a joint model for longitudinal CKD-EPI measures and HFH risk, we calculated the probability of being HFH-free in the next five years. RESULTS: The mean eGFR decline was estimated at 1.48 ml/min/1.73 m2 per year (95 % CI from 1.23 to 1.74). We observed that eGFR decline was significantly associated with the HFH risk (adjHR = 1.15 for an increase in yearly decline of 1 ml/min/1.73 m2, 95 % CI from 1.03 to 1.26) independently of 7 baseline variables (from clinical, biological and ECG domains). Discrimination was good along the prediction times: AUC at 0.87 (95 %CI from 0.84 to 0.91) at patient inclusion and 0.77 (95 %CI from 0.67 to 0.87) at seven years' follow-up. CONCLUSIONS: Renal function decline was significantly associated with the HFH risk. In the era of computer-assisted medical decisions, the DynHFH, a tool that dynamically predicts HFH in type 2 diabetes persons (https://shiny.idbc.fr/DynHFH), might be helpful for precision medicine and the implementation of stratified medical decision-making.