Is the ACS-NSQIP Risk Calculator Accurate in Predicting Adverse Postoperative Outcomes in the Emergency Setting? An Italian Single-center Preliminary Study

World J Surg. 2020 Nov;44(11):3710-3719. doi: 10.1007/s00268-020-05705-w. Epub 2020 Jul 24.

Abstract

Background: The ACS-NSQIP surgical risk calculator (SRC) is an open-access online tool that estimates the chance for adverse postoperative outcomes. The risk is estimated based on 21 patient-related variables and customized for specific surgical procedures. The purpose of this monocentric retrospective study is to validate its predictive value in an Italian emergency setting.

Methods: From January to December 2018, 317 patients underwent surgical procedures for acute cholecystitis (n = 103), appendicitis (n = 83), gastrointestinal perforation (n = 45), and intestinal obstruction (n = 86). Patients' personal risk was obtained and divided by the average risk to calculate a personal risk ratio (RR). Areas under the ROC curves (AUC) and Brier score were measured to assess both the discrimination and calibration of the predictive model.

Results: The AUC was 0.772 (95%CI 0.722-0.817, p < 0.0001; Brier 0.161) for serious complications, 0.887 (95%CI 0.847-0.919, p < 0.0001; Brier 0.072) for death, and 0.887 (95%CI 0.847-0.919, p < 0.0001; Brier 0.106) for discharge to nursing or rehab facility. Pneumonia, cardiac complications, and surgical site infection presented an AUC of 0.794 (95%CI 0.746-0.838, p < 0.001; Brier 0.103), 0.836 (95%CI 0.790-0.875, p < 0.0001; Brier 0.081), and 0.729 (95%CI 0.676-0.777, p < 0.0001; Brier 0.131), respectively. A RR > 1.24, RR > 1.52, and RR > 2.63 predicted the onset of serious complications (sensitivity = 60.47%, specificity = 64.07%; NPV = 81%), death (sensitivity = 82.76%, specificity = 62.85%; NPV = 97%), and discharge to nursing or rehab facility (sensitivity = 80.00%, specificity = 69.12%; NPV = 95%), respectively.

Conclusions: The calculator appears to be accurate in predicting adverse postoperative outcomes in our emergency setting. A RR cutoff provides a much more practical method to forecast the onset of a specific type of complication in a single patient.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Area Under Curve
  • Female
  • Humans
  • Italy / epidemiology
  • Male
  • Middle Aged
  • Postoperative Complications* / epidemiology
  • Retrospective Studies
  • Risk Assessment / methods*