The Diabetes Remission Index: A Novel Prognostic Calculator Model Predicting Diabetes Remission Before and After Metabolic Procedures.

Objective: To develop and validate 2 predictive models, the Diabetes Remission Index (DRI) and the Weight loss-adjusted DRI (W-DRI), for assessing type 2 diabetes (T2D) remission following metabolic and bariatric surgery (MBS).

Background: MBS, including Roux-en-Y gastric bypass and sleeve gastrectomy, is highly effective in achieving T2D remission, but outcomes vary across populations. Predicting remission remains critical for individualized patient care and optimizing surgical outcomes. Existing tools focus on general outcomes, and a specific model incorporating weight loss data has been lacking.

Methods: This multicenter, retrospective cohort study included patients with T2D and overweight/obesity (body mass index: ≥27 kg/m 2 ) who underwent Roux-en-Y gastric bypass or sleeve gastrectomy between 2008 and 2018. Institution 1 (I-1) data (n = 503) were used to develop and internally validate the models, whereas Institution 2 (I-2) data (n = 409) were used for external validation. The DRI model incorporated preoperative variables, and the W-DRI model, in addition, included postsurgical weight loss. Predictive accuracy was assessed using area under the Receiver Operating Characteristic curve [area under the curve (AUC)], calibration plots, and stratified analyses.

Results: In I-1, 44.7% of patients achieved T2D remission, with a DRI model AUC of 0.80. In I-2, 52.6% achieved remission, with a model AUC of 0.78. Incorporating weight loss improved W-DRI predictive accuracy (AUC: 0.82 in I-1, 0.79 in I-2). Calibration plots demonstrated strong agreement between predicted and observed remission rates. An online DRI and W-DRI calculator is available through the Mayo Clinic webpage ( https://newsnetwork.mayoclinic.org/dri-calculator/ ).

Conclusions: The DRI and W-DRI models accurately predict T2D remission post-MBS, enabling personalized patient care and informed decision-making. Further validation across diverse populations is warranted.