Assessment of the Risk Analysis Index for Prediction of Mortality, Major Complications, and Length of Stay in Patients who Underwent Vascular Surgery

• Type of Material: Article
• Authors: Kara A. Rothenberg, Stanford University; Elizabeth L. George, Stanford University; Amber W. Trickey, Stanford University; Nicolas B. Barreto, Stanford University; Theodore Johnson II, Emory University; Daniel E. Hall, University of Pittsburgh; Jason M. Johanning, University of Nebraska; Shipra Arya, Emory University
• Language: English
• Date: 2020-07-01
• Publisher: Elsevier Science Inc.
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2020 Elsevier Inc.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.avsg.2020.01.015
• Title of Journal or Parent Work: Annals of Vascular Surgery
• Volume: 66
• Start Page: 442
• End Page: 453
• Grant/Funding Information: U.S. Department of Health and Human Services (R03-AG050930-02)
• Keywords: Science & Technology; Frailty increases; Repair; Peripheral Vascular Disease; Validation; Life Sciences & Biomedicine; Cardiovascular System & Cardiology; Models; Surgery; Calibration; Possum; Morbidity; Sarcopenia; Survival; Outcomes
• Research Categories: Health Sciences, Medicine and Surgery; Health Sciences, Rehabilitation and Therapy

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 patients who underwent vascular surgery 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 database to identify 6 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). Although 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. Although 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.