Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery

Background Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. Objective This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Methods Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Results Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p < 0.001), age (standardized OR 1.10, 95%CI 1.03-1.17, p = 0.007), low body mass index (standardized OR 0.89, 95%CI 0.82-0.98, p = 0.012), operation year (standardized OR 0.91, 95%CI 0.85-0.97, p = 0.003), waist circumference (standardized OR 1.09, 95%CI 1.00-1.19, p = 0.059), and dyspepsia/GERD (standardized OR 1.08, 95%CI 1.02-1.15, p = 0.007) were all associated with risk for severe postoperative complication and were included in the risk prediction model. Despite high specificity, the sensitivity of the model was low. Conclusion Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.