4.5 Article

Does the ACS NSQIP Surgical Risk Calculator Accurately Predict Complications Rates After Anterior Lumbar Interbody Fusion Procedures?

期刊

SPINE
卷 46, 期 12, 页码 E655-E662

出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/BRS.0000000000003893

关键词

ACS NSQIP surgical risk calculator; ALIF; complications; predictive tools; risk stratification

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The ACS NSQIP surgical risk calculator showed good predictive ability for some complications after ALIF, such as acute kidney injury and surgical site infection, but was not adequate for predicting other complication groups. Further identification of risk stratification models is necessary for patients undergoing ALIF.
Study Design. Clinical case series. Objective. The aim of this study was to determine the effectiveness of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator in the prediction of complications after anterior lumbar interbody fusion (ALIF). Summary of Background Data. Identifying at-risk patients may aid in the prevention of complications after spine procedures. The ACS NSQIP surgical risk calculator was developed to predict 30-day postoperative complications for a variety of operative procedures. Methods. Medical records of patients undergoing ALIF at our institution from 2009 to 2019 were retrospectively reviewed. Demographic and comorbidity variables were entered into the ACS NSQIP surgical risk calculator to generate percentage predictions for complication incidence within 30 days postoperatively. The observed incidences of these complications were also abstracted from the medical record. The predictive ability of the ACS NSQIP surgical risk calculator was assessed in comparison to the observed incidence of complications using area under the curve (AUC) analyses. Results. Two hundred fifty-three (253) patients were analyzed. The ACS NSQIP surgical risk calculator was a fair predictor of discharge to non-home facility (AUC 0.71) and surgical site infection (AUC 0.70). The ACS NSQIP surgical risk calculator was a good predictor of acute kidney injury/progressive renal insufficiency (AUC 0.81). The ACS NSQIP surgical risk calculator was not an adequate predictive tool for any other category, including: pneumonia, urinary tract infections, venous thromboembolism, readmission, reoperations, and aggregate complications (AUC < 0.70). Conclusion. The ACS NSQIP surgical risk calculator is an adequate predictive tool for a subset of complications after ALIF including acute kidney injury/progressive renal insufficiency, surgical site infections, and discharge to non-home facilities. However, it is a poor predictor for all other complication groups. The reliability of the ACS NSQIP surgical risk calculator is limited, and further identification of models for risk stratification is necessary for patients undergoing ALIF.

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