Systematic review of risk prediction models for diabetes after bariatric surgery

Abstract

Abstract Background Diabetes remission is an important outcome after bariatric surgery. The purpose of this study was to identify risk prediction models of diabetes remission after bariatric surgery. Methods A systematic literature review was performed in MEDLINE, MEDLINE-In-Process, Embase and the Cochrane Central Register of Controlled Trials databases in April 2015. All English-language full-text published derivation and validation studies for risk prediction models on diabetic outcomes after bariatric surgery were included. Data extraction included population, outcomes, variables, intervention, model discrimination and calibration. Results Of 2330 studies retrieved, eight met the inclusion criteria. Of these, six presented development of risk prediction models and two reported validation of existing models. All included models were developed to predict diabetes remission. Internal validation using tenfold validation was reported for one model. Two models (ABCD score and DiaRem score) had external validation using independent patient cohorts with diabetes remission assessed at 12 and 14 months respectively. Of the 11 cohorts included in the eight studies, calibration was not reported in any cohort, and discrimination was reported in two. Conclusion A variety of models are available for predicting risk of diabetes following bariatric surgery, but only two have undergone external validation.