Notice: Users may be experiencing issues with displaying some pages on stanfordhealthcare.org. We are working closely with our technical teams to resolve the issue as quickly as possible. Thank you for your patience.
 

Learn about the flu shot, COVID-19 vaccine, and our masking policy »

Stanford Health Care

Assessment of Risk Analysis Index for Prediction of Mortality, Major Complications and Length of Stay in Vascular Surgery Patients. Annals of vascular surgery Rothenberg, K. A., George, E. L., Trickey, A. W., Barreto, N. B., Johnson, T. M., Hall, D. E., Johanning, J. M., Arya, S. 2020

Abstract

INTRODUCTION: Frailty is a risk factor for adverse postoperative outcomes. We aimed to test the performance of a prospectively-validated frailty measure, the Risk Analysis Index (RAI) in vascular surgery patients and delineate the additive impact of procedure complexity on surgical outcomes.METHODS: We queried the 2007-2013 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database to identify six major elective vascular procedure categories (carotid revascularization, abdominal aortic aneurysm [AAA] repair, suprainguinal revascularization, infrainguinal revascularization, thoracic aortic aneurysm [TAA] repair, and thoracoabdominal aortic aneurysm [TAAA] repair). We trained and tested logistic regression models for 30-day mortality, major complications and prolonged length of stay (LOS). The first model, "RAI", used the RAI alone; "RAI-Procedure (RAI-P)" included procedure category (e.g., AAA repair) and procedure approach (e.g., endovascular); "RAI-Procedure Complexity (RAI-PC)" added outpatient versus inpatient surgery, general anesthesia use, work relative value units (RVUs), and operative time.RESULTS: The RAI model was a good predictor of mortality for vascular procedures overall (C-statistic 0.72). The C-statistic increased with the RAI-P (0.78), which further improved minimally, with the RAI-PC (0.79). When stratified by procedure category, the RAI predicted mortality well for infrainguinal (0.79) and suprainguinal (0.74) procedures, moderately well for AAA repairs (0.69) and carotid revascularizations (0.70), and poorly for TAAs (0.62) and TAAAs (0.54). For carotid, infrainguinal, and suprainguinal procedures, procedure complexity (RAI-PC) had little impact on model discrimination for mortality, did improve discrimination for AAAs (0.84), TAAs (0.73), and TAAAs (0.80). While the RAI model was not a good predictor for major complications or LOS, discrimination improved for both with the RAI-PC model.CONCLUSIONS: Frailty as measured by the RAI was a good predictor of mortality overall after vascular surgery procedures. While the RAI was not a strong predictor of major complications or prolonged LOS, the models improved with the addition of procedure characteristics like procedure category and approach.

View details for DOI 10.1016/j.avsg.2020.01.015

View details for PubMedID 31935435