Shipra Arya1,2, Patrick Varley3, Ada Youk4,5, Jeffrey D Borrebach6, Sebastian Perez7, Nader N Massarweh8, Jason M Johanning9, Daniel E Hall3,4,5. 1. Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA. 2. Center for Innovation to Implementation, VA Palo Alto Healthcare System, Palo Alto, CA. 3. Department of Surgery, University of Pittsburgh, Pittsburgh, PA. 4. Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA. 5. Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA. 6. Wolff Center at UPMC, University of Pittsburgh Medical Center, Pittsburgh, PA. 7. Department of Surgery, Emory University, Atlanta, GA. 8. Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey VA Medical Center; Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX. 9. Department of Surgery, University of Nebraska Medical Center and Nebraska Western Iowa VA. Health System, Omaha, NE.
Abstract
OBJECTIVE AND BACKGROUND: The Risk Analysis Index (RAI) predicts 30-, 180-, and 365-day mortality based on variables constitutive of frailty. Initially validated, in a single-center Veteran hospital, we sought to improve model performance by recalibrating the RAI in a large, veteran surgical registry, and to externally validate it in both a national surgical registry and a cohort of surgical patients for whom RAI was measured prospectively before surgery. METHODS: The RAI was recalibrated among development and confirmation samples within the Veterans Affairs Surgical Quality Improvement Program (VASQIP; 2010-2014; N = 480,731) including major, elective noncardiac surgery patients to create the revised RAI (RAI-rev), comparing discrimination and calibration. The model was tested externally in the American College of Surgeons National Surgical Quality Improvement Program dataset (NSQIP; 2005-2014; N = 1,391,785), and in a prospectively collected cohort from the Nebraska Western Iowa Health Care System VA (NWIHCS; N = 6,856). RESULTS: Recalibrating the RAI significantly improved discrimination for 30-day [c = 0.84-0.86], 180-day [c = 0.81-0.84], and 365-day mortality [c = 0.78-0.82] (P < 0.001 for all) in VASQIP. The RAI-rev also had markedly better calibration (median absolute difference between observed and predicted 180-day mortality: decreased from 8.45% to 1.23%). RAI-rev was highly predictive of 30-day mortality (c = 0.87) in external validation with excellent calibration (median absolute difference between observed and predicted 30-day mortality: 0.6%). The discrimination was highly robust in men (c = 0.85) and women (c = 0.89). Discrimination also improved in the prospectively measured cohort from NWIHCS for 180-day mortality [c = 0.77 to 0.80] (P < 0.001). CONCLUSIONS: The RAI-rev has improved discrimination and calibration as a frailty-screening tool in surgical patients. It has robust external validity in men and women across a wide range of surgical settings and available for immediate implementation for risk assessment and counseling in preoperative patients.
OBJECTIVE AND BACKGROUND: The Risk Analysis Index (RAI) predicts 30-, 180-, and 365-day mortality based on variables constitutive of frailty. Initially validated, in a single-center Veteran hospital, we sought to improve model performance by recalibrating the RAI in a large, veteran surgical registry, and to externally validate it in both a national surgical registry and a cohort of surgical patients for whom RAI was measured prospectively before surgery. METHODS: The RAI was recalibrated among development and confirmation samples within the Veterans Affairs Surgical Quality Improvement Program (VASQIP; 2010-2014; N = 480,731) including major, elective noncardiac surgery patients to create the revised RAI (RAI-rev), comparing discrimination and calibration. The model was tested externally in the American College of Surgeons National Surgical Quality Improvement Program dataset (NSQIP; 2005-2014; N = 1,391,785), and in a prospectively collected cohort from the Nebraska Western Iowa Health Care System VA (NWIHCS; N = 6,856). RESULTS: Recalibrating the RAI significantly improved discrimination for 30-day [c = 0.84-0.86], 180-day [c = 0.81-0.84], and 365-day mortality [c = 0.78-0.82] (P < 0.001 for all) in VASQIP. The RAI-rev also had markedly better calibration (median absolute difference between observed and predicted 180-day mortality: decreased from 8.45% to 1.23%). RAI-rev was highly predictive of 30-day mortality (c = 0.87) in external validation with excellent calibration (median absolute difference between observed and predicted 30-day mortality: 0.6%). The discrimination was highly robust in men (c = 0.85) and women (c = 0.89). Discrimination also improved in the prospectively measured cohort from NWIHCS for 180-day mortality [c = 0.77 to 0.80] (P < 0.001). CONCLUSIONS: The RAI-rev has improved discrimination and calibration as a frailty-screening tool in surgical patients. It has robust external validity in men and women across a wide range of surgical settings and available for immediate implementation for risk assessment and counseling in preoperative patients.
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