The Diabetes Remission Index (DRI) and Weight Loss-Adjusted Diabetes Remission Index (W-DRI) models – used to assess type 2 diabetes (T2D) remission following bariatric and metabolic surgery (BMS) - accurately predict T2D remission post-BMS, enabling personalised patient care and informed decision-making. The findings were reported in the paper, 'The Diabetes Remission Index (DRI): A Novel Prognostic Calculator Model Predicting Diabetes Remission Before and After Metabolic Procedures', published in the Annals in Surgery.
“The aim of the study was to develop and validate two predictive models for assessing or “quantifying” diabetes remission after metabolic surgery thus allowing for an individualized approach for bariatric surgery selection for patients with diabetes,” explained Dr Omar M Ghanem, Associate Professor of Surgery and Chair, Division of Metabolic and Abdominal Wall Reconstructive Surgery at the Mayo Clinic, Rochester, MN, and lead author of the paper. “Additionally, incorporating weight loss as a variable will hopefully incentivize patients to achieve more weight loss and thus higher diabetes remission chances post operatively.”
This multi-centre, retrospective cohort study included patients with T2D and overweight/obesity (BMI ≥27 kg/m²) who underwent Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) between 2008 and 2018. Mayo Clinic (I-1) data (n=503) was used to develop and internally validate both models, while Fresno Heart and Surgical Hospital (I-2) data (n=409) was used for external validation.
The DRI model incorporated preoperative variables using patient baseline characteristics from a training dataset to create a classification algorithm that predicts T2D remission based on the type of BMS performed. In comparison, the W-DRI model incorporates post-procedure weight loss, one of the most determinant and influential factors affecting diabetes remission, into the baseline characteristics, thereby improving the predictive accuracy for diabetes remission.
Briefly, data collection included demographic details, baseline metabolic parameters including body-mass index (BMI), and diabetes-related indicators such as disease duration, glycosylated haemoglobin (HbA1c) levels, number of T2D medications and the presence of microvascular and macrovascular complications. Moreover, the presence of diabetic retinopathy, nephropathy and neuropathy was aggregated to create a microvascular complication score. The presence of coronary artery disease (CAD), peripheral arterial disease (PAD), and cerebrovascular accidents (CVA) were aggregated to form a macrovascular complication score. The researchers then combined both scores to generate a comprehensive composite vascular complication score. In addition, postoperative weight loss at different time intervals was recorded to assess its impact on T2D outcomes following BMS.
“These models are designed to refine clinical decision-making by illustrating the complex interplay between patient profiles, surgical outcomes, and remission probabilities,” he added.
Outcomes
In I-1, there was a final sample size of 503 patients – of whom 225 (44.7%) achieved T2D remission (mean age was 53.5 years (SD 10.5), mean post-surgical follow-up was 7.0 years (SD 3.6), 68% were female, 92% were White, and mean BMI was 46.2 kg/m2 (SD 8.7). Microvascular complications were present in 222 patients (44%), while macrovascular complications were reported in 169 patients (34%). In this cohort, 393 (78%) had a RYGB while 110 (22%) had SG.
In I-2, from 409 patients, 215 (52.6%) achieved remission (mean age was 51.8 years (SD 11.4), mean postsurgical follow-up was 3.8 years (SD 2.7), 69% were female, 90% were White, and mean BMI was 45.0 kg/m2). Microvascular complications were found in 48 patients (12%) and macrovascular complications in 50 patients (12%). The majority of the cohort, 258 patients (63%), had a RYGB, while the remaining 151 (37%) had a SG.
Compared to I-1, patients from I-2 were more likely to be Hispanic or Latino (38% vs. 5%) and to have undergone SG (37% vs. 21%), and were less likely to have T2D retinopathy (1% vs. 16%), nephropathy (5% vs. 23%) neuropathy (9% vs. 40%), CAD (10% vs. 31%), CVA (2% vs. 6%), and PAD (2% vs. 8%, p<0.01 for each), revealing lesser disease severity in I-2. I-2 patients also had lower baseline fasting glucose measures (31% <120 mg/dL vs. 23%, p=0.006), but higher baseline HbA1c levels (19% ≥ 9% vs. 12%, p=0.03), vs. I-1 patients.
Preoperative Score: Diabetes Remission Index (DRI)
Pre and post patient demographics, disease state and outcomes were significantly associated with remission (p<0.10) in at least four of the five model building sets from I-1 and, in addition to number of vascular complications, form the basis of the DRI score: number of T2D medications, HbA1c at preop, procedure, baseline fasting glucose levels, baseline use of insulin and T2D duration.
The greater number of vascular complications and prescribed T2D medications, procedure type SG, higher HbA1c and fasting glucose levels, longer T2D duration, and baseline insulin use were associated with lower remission probabilities.
Postoperative Score: Weight Loss Adjusted-Diabetes Remission Index (W-DRI)
W-DRI parameter estimates from the five I-1 model building sets after adding TBWL revealed that compared to patients with <15% TBWL, odds ratio of achieving remission ranged from 2.57 to 4.37 for TBWL 15-24%, and from 3.25 to 6.15 for TBWL 25+%. I-1 AUCs ranged from 0.78 to 0.89, with a mean of 0.82.
“Based on our findings, we developed a user-friendly calculator that quickly and accurately predicts T2D remission for patients undergoing BMS. The application accepts input for the eight characteristics that make up the DRI and W-DRI models and then calculates the predicted probabilities of remission,” explained Dr. Ghanem. “The probabilities are generated for both models and presented as a range, based on the original predictions from I-1 (lower bound) and the recalibrated predictions from I-2 (upper bound).”
The researchers believe this is the first model to include the type of procedure in the scoring calculation, allowing for greater precision in forecasting outcomes, and uniquely includes both microvascular and macrovascular complications, which have been shown to be associated with diabetes remission.
The authors write that the development of a user-friendly calculator based on these models marks a significant technological advancement in the clinical management of T2D patients considering BMS. Not only will this aid clinicians in predicting diabetes remission probabilities but also enhances patient-clinician interactions by providing tangible, personalised data to inform decision-making processes.
“While these models provide higher level of accuracy in predicting diabetes remission post BMS, validation across diverse populations is warranted. Molecular variables, including C-peptide, might be an additive variable for future research,” concluded Dr Ghanem. “Moreover, and as the bariatric surgery practices are evolving, incorporating other surgical and endoscopic procedures will further aid providers and patients in the decision making process.”
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