External validation of the Codman score in colorectal surgery: a pragmatic tool to drive quality improvement

Abstract

Aim The simple six‐variable Codman score is a tool designed to reduce the complexity of contemporary risk‐adjusted postoperative mortality rate predictions. We sought to externally validate the Codman score in colorectal surgery. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) participant user file and colectomy targeted dataset of 2020 were merged. A Codman score (composed of six variables: age, American Society of Anesthesiologists score, emergency status, degree of sepsis, functional status and preoperative blood transfusion) was assigned to every patient. The primary outcome was in‐hospital mortality and secondary outcome was morbidity at 30 days. Logistic regression analyses were performed using the Codman score and the ACS NSQIP mortality and morbidity algorithms as independent variables for the primary and secondary outcomes. The predictive performance of discrimination area under receiver operating curve (AUC) and calibration of the Codman score and these algorithms were compared. Results A total of 40 589 patients were included and a Codman score was generated for 40 557 (99.02%) patients. The median Codman score was 3 (interquartile range 1–4). To predict mortality, the Codman score had an AUC of 0.92 (95% CI 0.91–0.93) compared to the NSQIP mortality score 0.93 (95% CI 0.92–0.94). To predict morbidity, the Codman score had an AUC of 0.68 (95% CI 0.66–0.68) compared to the NSQIP morbidity score 0.72 (95% CI 0.71–0.73). When body mass index and surgical approach was added to the Codman score, the performance was no different to the NSQIP morbidity score. The calibration of observed versus expected predictions was almost perfect for both the morbidity and mortality NSQIP predictions, and only well fitted for Codman scores of less than 4 and greater than 7. Conclusion We propose that the six‐variable Codman score is an efficient and actionable method for generating validated risk‐adjusted outcome predictions and comparative benchmarks to drive quality improvement in colorectal surgery.