Development and Validation of a Clinical Risk Score for Intensive Care Resource Utilization After Colon Cancer Surgery: a Practical Guide to the Selection of Patients During COVID-19

Background The purpose of this study was to develop and validate a prediction model and clinical risk score for Intensive Care Resource Utilization after colon cancer surgery. Methods Adult (≥ 18 years old) patients from the 2012 to 2018 ACS-NSQIP colectomy-targeted database who underwent elective colon cancer surgery were identified. A prediction model for 30-day postoperative Intensive Care Resource Utilization was developed and transformed into a clinical risk score based on the regression coefficients. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow goodness-of-fit test. The model was validated in a separate test set of similar patients. Results In total, 54,893 patients underwent an elective colon cancer resection, of which 1224 (2.2%) required postoperative Intensive Care Resource Utilization. The final prediction model retained six variables: age (≥ 70; OR 1.90, 95% CI 1.68–2.14), sex (male; OR 1.73, 95% CI 1.54–1.95), American Society of Anesthesiologists score (III/IV; OR 2.52, 95% CI 2.15–2.95), cardiorespiratory disease (yes; OR 2.22, 95% CI 1.94–2.53), functional status (dependent; OR 2.81, 95% CI 2.22–3.56), and operative approach (open surgery; OR 1.70, 95% CI 1.51–1.93). The model demonstrated good discrimination (AUC = 0.73). A clinical risk score was developed, and the risk of requiring postoperative Intensive Care Resource Utilization ranged from 0.03 (0 points) to 19.0% (8 points). The model performed well on test set validation (AUC = 0.73). Conclusion A prediction model and clinical risk score for postoperative Intensive Care Resource Utilization after colon cancer surgery was developed and validated.