Objective To compare the prognostic value of the Fried frailty phenotype and the frailty index based on the Comprehensive Geriatric Assessment(CGA-FI)in predicting 5-year all-cause mortality among elderly pa-tients with cardiovascular disease,as well as to explore methods for optimizing predictive models.Methods A prospec-tive cohort study design was employed,involving elderly patients with cardiovascular disease admitted to the cardiology department of Beijing Hospital from September 2018 to February 2019,with follow-up to record major adverse events.Frailty assessments were conducted using the Fried frailty phenotype and CGA-FI.Receiver operating characteristic(ROC)curves were utilized to evaluate the predictive performance of different assessment methods.Predictive factors were selected using LASSO regression,and logistic regression was subsequently employed to construct predictive models.Applying Bootstrap method for internal validation.Results A total of 420 patients were included in the study,with a median age of 73.8(68.9,79.1)years,of which 223(53.0％)were male.The median follow-up duration was 1 879(1 833,1 931)days,during which 73 patients(17.4％)died.Of these,107(25.5％)and 113(26.9％)patients were identified as frail according to the Fried frailty phenotype and CGA-FI,respectively.Frail patients identified by both methods had significantly higher 5-year all-cause mortality rates compared to non-frail patients(Log-rankP＜0.001).The area under the curve(AUC)for predicting mortality was 0.735(95％CI:0.667-0.804)for the Fried frailty phe-notype and 0.777(95％CI:0.713-0.840)for CGA-FI.A predictive model constructed using LASSO regression with 6 selected factors achieved an AUC of 0.882(95％CI:O.835-0.929).The average AUC validated by Bootstrap method is 0.871(95％CI:O.866-0.877).Conclusions Frailty is an independent predictor of all-cause mortality in elderly patients with cardiovascular disease.Both the Fried frailty phenotype and CGA-FI all have predictive value,and the new-ly constructed predictive model provides more accurate prediction of 5-year all-cause mortality risk.
维普
万方数据
