Applying the National Surgical Quality Improvement Program risk calculator to patients undergoing colorectal surgery: theory vs reality

2017 ◽  
Vol 213 (1) ◽  
pp. 30-35 ◽  
Author(s):  
Titilayo O. Adegboyega ◽  
Andrew J. Borgert ◽  
Pamela J. Lambert ◽  
Benjamin T. Jarman
Keyword(s):  
Quality Improvement ◽  
Colorectal Surgery ◽  
Quality Improvement Program ◽  
Risk Calculator ◽  
Improvement Program ◽  
Surgical Quality ◽  
Surgery Theory

Assessing the Veterans Affairs Surgical Quality Improvement Program Risk Calculator in Cholecystectomy

2018 ◽  
Vol 84 (6) ◽  
pp. 1039-1042 ◽  
Author(s):  
Jonathan B. Imran ◽  
Oswaldo Renteria ◽  
Maria Ruiz ◽  
Thai H. Pham ◽  
Ali A. Mokdad ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Predictive Accuracy ◽  
Weighted Least Squares ◽  
Veterans Affairs ◽  
Quality Improvement Program ◽  
Least Squares Regression ◽  
Risk Calculator ◽  
Improvement Program ◽  
Surgical Quality ◽  
C Statistic

The Veterans Affairs Surgical Quality Improvement Program (VASQIP) risk calculator has been validated for several operations but has not been assessed specifically for cholecystectomy. Our aim was to externally validate the VASQIP calculator's accuracy in predicting 30-day morbidity and mortality (M&M) for patients undergoing cholecystectomy. A retrospective review of patients undergoing cholecystectomy at the North Texas Veterans Affairs hospital was performed. The VASQIP risk calculator was used to determine predicted 30-day M&M, which was compared with actual M&M. The predictive accuracy of the Veterans Affairs risk calculator was assessed using the C-statistic and a graphical assessment of a locally weighted least squares regression smoother. Overall, 848 patients were included in the study. Actual M&M were 6.3 and 0.94 per cent, respectively, whereas predicted M&M were 6.0 and 0.54 per cent. The C-statistic was 0.75 for morbidity and 0.78 for mortality. In our analysis, the VASQIP risk calculator reasonably predicted 30-day M&M.

Development and Validation of a Risk Calculator for Renal Complications after Colorectal Surgery Using the National Surgical Quality Improvement Program Participant Use Files

2016 ◽  
Vol 82 (12) ◽  
pp. 1244-1249 ◽  
Author(s):  
Kimberly M. Ramonell ◽  
Shuyang Fang ◽  
Sebastian D. Perez ◽  
Jahnavi K. Srinivasan ◽  
Patrick S. Sullivan ◽  
...  
Keyword(s):  
Renal Failure ◽  
Acute Renal Failure ◽  
Quality Improvement ◽  
Colorectal Surgery ◽  
Area Under The Curve ◽  
Risk Calculator ◽  
Improvement Program ◽  
Surgical Quality ◽  
Program Participant ◽  
Renal Complications

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.

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