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Predictive validity of the ACS-NSQIP surgical risk calculator in geriatric patients undergoing lumbar surgery

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 undergoi...

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Detalles Bibliográficos
Autores principales: Wang, Xiao, Hu, Yanting, Zhao, Binjiang, Su, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5671873/
https://www.ncbi.nlm.nih.gov/pubmed/29069040
http://dx.doi.org/10.1097/MD.0000000000008416
Descripción
Sumario: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.