Pre-existing medical conditions as predictors of adverse events in day-case surgery

Abstract

We have developed mathematical models to estimate the risk of perioperative adverse events in patients with pre-existing conditions undergoing day-case surgery. We studied 17,638 consecutive day-case surgical patients in a prospective study. Preoperative, intraoperative and postoperative data were collected. Risk modelling was performed with backward stepwise multiple logistic regression and validated on a separate subset of our patients. Eighteen pre-existing conditions were entered into the model. We adjusted for age, sex, and duration and type of surgery. Seven associations between pre-existing medical conditions and perioperative adverse events were statistically significant. Hypertension predicted the occurrence of any intraoperative event and intraoperative cardiovascular events. Obesity predicted intraoperative and postoperative respiratory events, and smoking and asthma predicted postoperative respiratory events. Gastro-oesophageal reflux predicted intubation-related events. The presented models of risk estimation were validated internally and provided a useful tool for accurate risk estimation.