Predicting Postoperative Complications after Acute Care Surgery: How Accurate is the ACS NSQIP Surgical Risk Calculator?

Le résumé fourni par la source

The ACS NSQIP Surgical Risk Calculator (SRC) is an evidence-based clinical tool commonly used for evaluating postoperative risk. The goal of this study was to validate SRC-predicted complications by comparing them with observed outcomes in the acute care surgical setting. In this study, pre- and postoperative data from 1693 acute care surgeries (hernia repair, enterolysis, intestinal incision/excision and enterectomy, gastrectomy, debridement, colectomy, appendectomy, cholecystectomy, gastrorrhaphy, and incision and drainage of soft tissue, breast abscesses, and removal of foreign bodies) performed at a Level I trauma center over a five-year time period were abstracted. Predictions for any and serious complications were based on SRC were compared with observed outcomes using various measures of diagnostic. When evaluated as one group, the SRC had good discriminative power for predicting any and serious complications after acute care surgeries (Area Under the Curve (AUC) 0.79, 0.81). In addition, the SRC met Brier score requirements for an informative model overall. However, the predictive accuracy of the SRC varied for various procedures within the acute care patient population. For serious complications, the diagnostic measures ranged from an AUC of 0.61 and negative likelihood ratio of 0.716 for incision & drainage soft tissue to AUC of 0.91 and negative likelihood ratio of 0.064 for gastrorrhaphy. Length of stay was significantly underestimated by the SRC overall (8.56 days, P < 0.01) and for individual procedures. The SRC performs well at predicting complications after acute care surgeries overall; however, there is great variability in performance between procedure types. Further refinements in risk stratification may improve SRC predictions.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.