A meta-analysis of the American college of surgeons risk calculator's predictive accuracy among different surgical sub-specialties

Background: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) provides risk estimates of postoperative complications. While several studies have examined the accuracy of the ACS -Surgical Risk Calculator (SRC) within a single specialty, the respective conclusions are limited by sample size. We sought to conduct a meta -analysis to determine the accuracy of the ACS -SRC among various surgical specialties. Study design: Clinical studies that utilized the ACS -SRC, predicted complication rates compared to actual rates, and analyzed at least one metric reported by ACS -SRC met the inclusion criteria. Data for each specialty were pooled using the DerSimonian and Laird random -effect models and analyzed with the binary random -effect model to produce risk difference (RD) and 95 % confidence intervals (CIs) using Open Meta[Analyst]. Results: The initial search yielded 281 studies and, after applying inclusion and exclusion criteria, a total of 53 studies remained with a total sample of 30,134 patients spanning 10 surgical specialties. When considering any complication and death, the ACS -SRC significantly underpredicted complications for: Orthopaedic Surgery (RD -0.067, p = 0.008), Spine (RD -0.027, p < 0.001), Urology (RD -0.03, p < 0.001), Surgical Oncology (RD -0.045, p < 0.001), and Gynecology (RD -0.098, p = 0.01). Conclusion: The ACS -SRC proved useful in General, Acute Care, Colorectal, Otolaryngology, and Cardiothoracic Surgery, but significantly underpredicted complication rates in Spine, Orthopaedics, Urology, Surgical Oncology, and Gynecology. These data indicate the ACS -SRC is a reliable predictor in some specialties, but its use should be cautioned in the remaining specialties evaluated here.