Development and Validation of a Risk Calculator for Renal Complications after Colorectal Surgery Using the National Surgical Quality Improvement Program Participant Use Files. Issue 12 (December 2016)

• Record Type: Journal Article
• Authors: Ramonell, Kimberly M.; Fang, Shuyang; Perez, Sebastian D.; Srinivasan, Jahnavi K.; Sullivan, Patrick S.; Galloway, John R.; Staley, Charles A.; Lin, Edward; Sharma, Jyotirmay; Sweeney, John F.; Shaffer, Virginia O.
• Is Part Of: American surgeon. Volume 82:Issue 12(2016)
• Page Start: 1244
• Page End: 1249
• Publication Date: 2016-12
• Subjects: Surgery -- Periodicals; Surgery -- United States -- Periodicals; 617.0973
• DOI: 10.1177/000313481608201234
• Languages: English
• ISSNs: 0003-1348

Abstract

Postoperative acute renal failure is a major cause of morbidity and mortality in colon and rectal surgery. Our objective was to identify preoperative risk factors that predispose patients to postoperative renal failure and renal insufficiency, and subsequently develop a risk calculator. Using the National Surgical Quality Improvement Program Participant Use Files database, all patients who underwent colorectal surgery in 2009 were selected (n = 21, 720). We identified renal complications during the 30-day period after surgery. Using multivariate logistic regression analysis, a predictive model was developed. The overall incidence of renal complications among colorectal surgery patients was 1.6 per cent. Significant predictors include male gender (adjusted odds ratio [OR]: 1.8), dependent functional status (OR: 1.5), preoperative dyspnea (OR: 1.5), hypertension (OR: 1.6), preoperative acute renal failure (OR: 2.0), American Society of Anesthesiologists class ≥3 (OR: 2.2), preoperative creatinine >1.2 mg/dL (OR: 2.8), albumin <3.5 g/dL (OR: 1.8), and emergency operation (OR: 1.5). This final model has an area under the curve (AUC) of 0.79 and was validated with similar excellent discrimination (area under the curve: 0.76). Using this model, a risk calculator was developed with excellent predictive ability for postoperative renal complications in colorectal patients and can be used to aid clinical decision-making, patient counseling, and further research on measures to improve patient care.