Related Experiment Video
Updated: Feb 20, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Predictive validity of the ACS-NSQIP surgical risk calculator in geriatric patients undergoing lumbar surgery
Xiao Wang1, Yanting Hu, Binjiang Zhao
1Beijing Shijitan Hospital Anesthesiology, Capital Medical University, Beijing, China.
Abstract:
The risk calculator of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) has been shown to be useful in predicting postoperative complications. In this study, we aimed to evaluate the predictive value of the ACS-NSQIP calculator in geriatric patients undergoing lumbar surgery.A total of 242 geriatric patients who underwent lumbar surgery between January 2014 and December 2016 were included. Preoperative clinical information was retrospectively reviewed and entered into the ACS-NSQIP calculator. The predictive value of the ACS-NSQIP model was assessed using the Hosmer-Lemeshow test, Brier score (B), and receiver operating characteristics (ROC, also referred C-statistic) curve analysis. Additional risk factors were calculated as surgeon-adjusted risk including previous cardiac event and cerebrovascular disease.Preoperative risk factors including age (P = .004), functional independence (P = 0), American Society of Anesthesiologists class (ASA class, P = 0), dyspnea (P = 0), dialysis (P = .049), previous cardiac event (P = .001), and history of cerebrovascular disease (P = 0) were significantly associated with a greater incidence of postoperative complications. Observed and predicted incidence of postoperative complications was 43.8% and 13.7% (±5.9%) (P < .01), respectively. The Hosmer-Lemeshow test demonstrated adequate predictive accuracy of the ACS-NSQIP model for all complications. However, Brier score showed that the ACS-NSQIP model could not accurately predict risk of all (B = 0.321) or serious (B = 0.241) complications, although it accurately predicted the risk of death (B = 0.0072); this was supported by ROC curve analysis. The ROC curve also showed that the model had high sensitivity and specificity for predicting renal failure and readmission.The ACS-NSQIP surgical risk calculator is not an accurate tool for the prediction of postoperative complications in geriatric Chinese patients undergoing lumbar surgery.
More Related Videos
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025