Nomogram to Predict Rapid Kidney Function Decline in Population at Risk of Cardiovascular Disease

Abstract Background To develop a simple model to predict risk of rapid kidney function decline (RKFD) in population at risk of cardiovascular disease. Methods 8455 subjects aged ≥ 65 years or complicated diabetes or hypertension undergoing community annual health examinations between January 2015 and December 2020 were included. All participants were randomly assigned to a development cohort and a validation cohort in a 2:1 ratio. Rapid kidney function decline was defined as the reduction of estimated glomerular filtration rate (eGFR)≥40% during follow-up period. Cox regression analysis and stepwise approach were used to identify the risk factors. A nomogram based on these predictors was then developed, and discrimination, calibration and decision curve analysis were assessed. Results During the median follow-up period of 3.72 years, the incidence of rapid kidney function decline was 11.96% (n = 1011), 11.98% (n = 676) and 11.92% (n = 335) in the entire cohort, development cohort and validation cohort, respectively. Age, eGFR, hemoglobin, systolic blood pressure, and diabetes were identified as predictors for RKFD. The nomogram demonstrated a good discriminative power with the 5-year AUCs of 0.763 and 0.740 in the development and the validation cohort, respectively. Calibration plots also demonstrated a good fitness between the observed and predicted risk in both cohorts. Conclusions Risk stratification for rapid kidney function decline is achievable using a risk prediction nomogram based on clinical factors that are readily accessible in primary care. The utility of this nomogram in identifying individuals at high risk of RKFD in the community needs further investigation.