Abstract
Background
Chronic kidney disease (CKD) poses significant health risks due to its asymptomatic nature in early stages and its association with increased cardiovascular and kidney events. Early detection and management are critical for improving outcomes.
Objective
This study aimed to develop and validate a prediction model for major adverse cardiovascular events (MACE) and major adverse kidney events (MAKE) in Japanese individuals with mild CKD using readily available health check and prescription data.
Methods
A retrospective cohort study was conducted using data from 850,000 individuals in the PREVENT Inc. database, collected between April 2013 and April 2023. Cox proportional hazard regression models were utilized to derive and validate risk scores for MACE and MAKE, incorporating traditional risk factors and CKD-specific variables. Model performance was assessed using the concordance index (c-index) and 5-fold cross-validation.
Results
A total of 40,351 individuals were included. Key predictors included age, sex, diabetes, hypertension, and lipid levels for MACE and MAKE. Age significantly increased the risk score for both MACE and MAKE. The baseline 5-year survival rates are 0.99 for MACE and MAKE. The developed risk models demonstrated predictive ability, with mean c-indexes of 0.75 for MACE and 0.69 for MAKE.
Conclusions
This prediction model offers a practical tool for early identification of Japanese individuals with mild CKD at risk for MACE and MAKE, facilitating timely interventions to improve patient outcomes and reduce healthcare costs. The models stratified patients into risk categories, enabling identification of those at higher risk for adverse outcomes. Further clinical validation is required.