Abstract:Objective To constructe a mortality risk predictive model for community elderly population based on routine physical examination blood test indicators and frailty index using a community-based geriatric frailty follow-up cohort in Dalang Town, Dongguan City. Methods A frailty risk score model was constructed using Cox regression analysis with baseline frailty assessment results and blood laboratory test results as predictor variables and survival status during the followup period as an outcome variable. Kaplan-Meier survival curves, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the model, and generate an online risk score calculation tool. Results The results of multifactorial Cox analysis showed significant intergroup differences (P<0.05) between the surviving and dying groups for the 12 baseline blood test results for leucocyte, haemoglobin, platelet distribution width, neutrophil percentage, standard deviation of erythrocyte distribution width, lymphocyte percentage, total bilirubin, ghrelin, glucose, creatinine, triglyceride, and azelaic acid aminotransferase levels. In the test set, the 6-year mean AUC of the FI-lab constructed from these 12 blood test results was 0.826, the 6-year mean AUC of the FI-self-report based on self-report of the Frailty Index scale was 0.809, and the 6-year mean AUC of the FI-combined combining the two was 0.834. Conclusion The frailty risk prediction model constructed on the routine physical examination blood test results and frailty index can effectively predict the risk of mortality in the elderly, and an online risk score calculation tool facilitates clinical implementation.