Objective The objective of this study was to evaluate the ability of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) surgical risk calculator to predict complications in gynecologic oncology patients undergoing laparotomy. Methods A chart review of patients who underwent laparotomy on the gynecologic oncology service at a single academic hospital from January 2009 to December 2013 was performed. Preoperative variables were abstracted and NSQIP surgical risk scores were calculated. The risk of any complication, serious complication, death, urinary tract infection, venous thromboembolism, cardiac event, renal complication, pneumonia and surgical site infection were correlated with actual patient outcomes using logistic regression. The c-statistic and Brier score were used to calculate the prediction capability of the risk calculator. Results Of the 1,094 patients reviewed, the majority were <65 years old (70.9%), independent (95.2%), ASA class 1-2 (67.3%), and overweight or obese (76.1%). Higher calculated risk scores were associated with an increased risk of the actual complication occurring for all events (p<0.05). The calculator performed best for predicting death (c-statistic=0.851, Brier=0.008) and cardiac complications (c-statistic=0.708, Brier=0.011). The calculator did not accurately predict most complications. Conclusions The NSQIP surgical risk calculator adequately predicts specific serious complications, such as postoperative death and cardiac complications. However, the overall performance of the calculator was worse for gynecologic oncology patients than reported in general surgery patients. A tailored prediction model may be needed for this patient population.
Objectives: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator calculates risk of postoperative complications utilizing clinically apparent preoperative variables. If validated for patients with gynecologic , this can be an effective tool in to use for shared decision-making, especially in the older (70+ years of age) patient population for whom surgical risks and potential loss of independence is increased. The primary objective of this study was to evaluate the ability of the ACS NSQIP surgical risk calculator to predict discharge to a post-acute care among older (age 70+ years) gynecologic oncology patients undergoing laparotomy. The secondary objectives were to assess its ability to predict postoperative complications and death. Methods: This was a retrospective cohort study of gynecologic oncology patients 70+ years of age undergoing laparotomy. Surgical procedures, 21 preoperative variables, postoperative complications, and patient disposition were abstracted from the medical record. Risk scores for seven postoperative complications and discharge to post-acute care were calculated. The association between risk scores and outcomes were assessed using logistic regression and predictive ability was evaluated using the c-statistic and Brier score. Results: 204 surgeries were performed on 200 patients between January 1, 2009 and December 31, 2013. The mean age was 76.3±5.1 years; 87% were independent at baseline. A total of 79 (41%) were discharged to post-acute care. The calculator's ability to predict discharge to post-* Corresponding author at: Mayo Mail Code 395, 420 Delaware St SE, Minneapolis, MN 55417. AUTHOR CONTRIBUTIONS SS contributed to the data acquisition, quality control of data and algorithms, data analysis and interpretation, manuscript preparation, editing, and review. CR contributed to the study concepts and study design, manuscript editing, and manuscript review. RN contributed to the data acquisition, manuscript editing, and manuscript review. RIV contributed to the data analysis and interpretation, statistical analysis, manuscript preparation, editing, and review. DT contributed to the study design and concepts, quality control of data and algorithms, data analysis and interpretation, manuscript preparation, editing, and review.
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