Predicting postoperative mortality after colorectal surgery: a novel clinical model

Abstract

Aim: The aim of this study was to develop and externally validate a clinically, practical and discriminative prediction model designed to estimate in-hospital mortality of patients undergoing colorectal surgery.

Method: All consecutive patients who underwent elective or emergency colorectal surgery from 1990 to 2005, at the Zaandam Medical Centre, The Netherlands, were included in this study. Multivariate logistic regression analysis was performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) linking the explanatory variables to the outcome variable in-hospital mortality, and a simplified Identification of Risk in Colorectal Surgery (IRCS) score was constructed. The model was validated in a population of patients who underwent colorectal surgery from 2005 to 2011 in Barcelona, Spain. Predictive performance was estimated by calculating the area under the receiver operating characteristic curve.

Results: The strongest predictors of in-hospital mortality were emergency surgery (OR = 6.7, 95% CI 4.7-9.5), tumour stage (OR = 3.2, 95% CI 2.8-4.6), age (OR = 13.1, 95% CI 6.6-26.0), pulmonary failure (OR = 4.9, 95% CI 3.3-7.1) and cardiac failure (OR = 3.7, 95% CI 2.6-5.3). These parameters were included in the prediction model and simplified scoring system. The IRCS model predicted in-hospital mortality and demonstrated a predictive performance of 0.83 (95% CI 0.79-0.87) in the validation population. In this population the predictive performance of the CR-POSSUM score was 0.76 (95% CI 0.71-0.81).

Conclusions: The results of this study have shown that the IRCS score is a good predictor of in-hospital mortality after colorectal surgery despite the relatively low number of model parameters.

Keywords: Colorectal surgery; clinical prediction rule; colorectal cancer; hospital mortality.