A Vascular Quality Initiative frailty assessment predicts postdischarge mortality in patients undergoing arterial reconstruction.

BACKGROUND:Frailty assessment adds important prognostic information during preoperative decision-making but can be cumbersome to implement into routine clinical care. We developed and tested an abbreviated method of frailty assessment using variables routinely collected by the Vascular Quality Initiative (VQI) registry. METHODS:An abbreviated frailty score (the simple Vascular Quality Initiative-Frailty Score [VQI-FS]) was developed using 11 or fewer VQI variables (hypertension, congestive heart failure, coronary artery disease, peripheral vascular disease, diabetes, chronic obstructive pulmonary disease, renal impairment, anemia, underweight, nonhome residence, and nonambulatory status) that map to recognized frailty domains in the Comprehensive Geriatric Assessment and the literature. Nonemergent cases registered in the VQI from 2010 to 2017 (n = 265,632) in seven registries (carotid endarterectomy, n = 77,111; carotid artery stenting, n = 13,215; endovascular abdominal aortic aneurysm repair, n = 29,607; open abdominal aortic aneurysm repair, n = 7442; infrainguinal bypass, n = 33,128; suprainguinal bypass, n = 10,661; and peripheral vascular intervention, n = 94,468) were analyzed using logistic regression models to determine the predictive power of the VQI-FS for perioperative and longer term (9-month) mortality. Nomograms were created using weighted regression coefficients to assist in individualized frailty assessment and estimation of 9-month mortality. RESULTS:The VQI-FS, using equal weighting of these 11 VQI variables, effectively predicted 9-month mortality with an area under the curve of 0.724 by receiver operating characteristic curve analysis. However, differential weighting of the variables allowed simplification of the model to only seven variables (congestive heart failure, renal impairment, chronic obstructive pulmonary disease, not living at home, not ambulatory, anemia, and underweight status); hypertension, coronary artery disease, peripheral vascular disease, and diabetes had relatively low predictive power. Adding procedure-specific risk further improved performance of the model with a final area under the curve on receiver operating characteristic curve analysis of 0.758. Model calibration was excellent with predicted/observed regression line slope of 0.991 and intercept of 5.449e-04. CONCLUSIONS:A differentially weighted abbreviated VQI-FS using seven variables in addition to procedure-specific risk has strong correlation with 9-month mortality. Nomograms incorporating patient- and procedure-adjusted risk can effectively predict 9-month mortality. Reliable estimates of longer term mortality should assist in preoperative decision-making for vascular procedures that often carry substantial risk of mortality.