ArticleSurgery in practice and science2024
A meta-analysis of the American college of surgeons risk calculator's predictive accuracy among different surgical sub-specialties.
Article in Surgery in practice and science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- The Predictive Value of Clinical and Systemic Inflammatory Biomarkers in Emergency Colic Cancer Surgery: A Retrospective Study.Journal of clinical medicine · 2026Article
- Preoperative malnutrition is associated with increased postoperative complications following lumbar fusion: a propensity-matched analysis.Journal of spine surgery (Hong Kong) · 2026Article
- Review
- Predictive value of the American college of surgeons "surgical risk calculator" (ACS-NSQIP SRC) for plastic and reconstructive surgery: a validation study from an academic tertiary referral center in Germany.Patient safety in surgery · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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[A 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, 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.
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