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.
journal_name
Medicine (Baltimore)journal_title
Medicineauthors
Wang X,Hu Y,Zhao B,Su Ydoi
10.1097/MD.0000000000008416subject
Has Abstractpub_date
2017-10-01 00:00:00pages
e8416issue
43eissn
0025-7974issn
1536-5964pii
00005792-201710270-00067journal_volume
96pub_type
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