Review, Performance Comparison, and Validation of Models Predicting Type 2 Diabetes Remission After Bariatric Surgery in a Western European Population

Preoperative predictors of type 2 diabetes remission after bilio-pancreatic diversion with duodenal switch

BACKGROUND

Many patients achieve short-term type 2 diabetes (T2D) remission after bariatric surgery, but relapses are common. Diabetes outcomes after bariatric surgery vary across procedures and populations. T2D remission scores are simple clinical tools developed to predict remission after bariatric surgery. However, they have never been tested after Biliopancreatic diversion with duodenal switch (BPD-DS).

OBJECTIVES

The aim of this study was to compare the predictive value of T2D remission scores and preoperative diabetes characteristics in predicting T2D remission after BPD-DS.

SETTING

Quebec Heart and Lung Institute - Laval University.

METHODS

We retrospectively identified 918 patients with preoperative T2D who had undergone BPD-DS. Retrospective chart review was performed and variables used to calculate predictive scores were captured. T2D status was assessed annually for up to 10 years postop. Predictive values for each score (DiarRem, Ad Diarem, and Diabetter) and single preoperative diabetes characteristics used to construct these algorithms were evaluated by area under receiver operating characteristic curves (AUC).

RESULTS

Diabetter showed greater performance for prediction of durable diabetes remission than other algorithms with acceptable discriminative ability (AUC between .69 and .79), but was not superior to T2D duration as a single predictor (P = .24 and P = .18). At 10 years, T2D duration had a better discriminative ability for the prediction of T2D remission than all 3 predictive models (AUC = .85, P < .05).

CONCLUSIONS

Better chances for T2D remission following BPD-DS are associated with a shorter duration or T2D before surgery. Duration of T2D alone offers an excellent predictive ability and is a convenient alternative to diabetes remission scores to estimate chances of long-term diabetes remission after BPD-DS.

Comparison of the ABCD Score's Accuracy in Predicting Remission of Type 2 Diabetes Mellitus One Year After Sleeve Gastrectomy, One Anastomosis Gastric Bypass, and Sleeve Gastrectomy with Transit Bipartition

PURPOSE

ABCD score is one of the scoring systems that predicts the probability of T2DM remission after bariatric surgery. Its success in determining T2DM remission after sleeve gastrectomy with transit bipartition (TB) has not yet been validated. The aim of this study was to evaluate the predictive value of ABCD score in TB.

MATERIALS AND METHODS

Of 438 patients with T2DM, 191 underwent sleeve gastrectomy (SG), 136 underwent one anastomosis gastric bypass (OAGB), and 111 underwent TB. Retrospective analysis of ABCD scores, 1-year postoperative remission rates, and the predictive accuracy of ABCD scores for these were conducted.

RESULTS

In the SG, OAGB, and TB groups, respectively, median ABCD scores were 7, 6, and 4, while complete remission rates were 95.3%, 84.6%, and 76.6% (p < 0.001). The area under curves (AUCs) for SG, OAGB, and TB were 0.829 (95% CI = 0.768 to 0.879, p < 0.0001), 0.801 (95% CI = 0.724 to 0.865, p < 0.0001), and 0.840 (95% CI = 0.758 to 0.902, p < 0.0001), respectively. There was no statistically significant difference between AUCs.

CONCLUSION

ABCD score predicts the probability of remission at 1-year follow-up in T2DM patients undergoing TB as accurately as in patients receiving SG or OAGB.

Examining spousal and family support as predictors of long-term weight loss and remission of type 2 diabetes following bariatric surgery in Singapore: a retrospective cohort study

OBJECTIVES

Postoperative outcomes vary considerably across bariatric patients and may be related to psychosocial factors. In this study, we examined whether a patient's family support predicts postsurgical weight loss and the remission of type 2 diabetes mellitus (T2DM).

DESIGN

Retrospective cohort study in Singapore.

SETTING

Participants were recruited from a public hospital in Singapore.

PARTICIPANTS

Between 2008 and 2018, 359 patients completed a presurgical questionnaire before undergoing gastric bypass or sleeve gastrectomy.

OUTCOME MEASURES

As part of the questionnaire, patients described their family support in terms of structure (marital status, number of family members in the household) and function (marriage satisfaction, family emotional support, family practical support). Linear mixed-effects and Cox proportional-hazard models were used to examine whether these family support variables predicted percent total weight loss or T2DM remission up to 5 years postsurgery. T2DM remission was defined as glycated haemoglobin (HbA1c) <6.0% without medications.

RESULTS

Participants had a mean preoperative body mass index of 42.6±7.7 kg/m² and HbA1c (%) of 6.82±1.67. Marital satisfaction was found to be a significant predictor of postsurgical weight trajectories. Namely, patients who reported higher marital satisfaction were more likely to sustain weight loss than patients who reported lower marital satisfaction (β=0.92, SE=0.37, p=0.02). Family support did not significantly predict T2DM remission.

CONCLUSIONS

Given the link between marital support and long-term weight outcomes, providers could consider asking patients about their spousal relationships during presurgical counselling.

TRIAL REGISTRATION NUMBER

NCT04303611.

How Good is Stratification and Prediction Model Analysis Between Primary and Revisional Roux-en-Y Gastric Bypass Surgery? A Multi-center Study and Narrative Review

INTRODUCTIONS

Revision surgery because of weight recurrence is performed in 2.5-33% of primary vertical banded gastroplasty (VBG), laparoscopic sleeve gastrectomy (LSG), and gastric band (GB) cases. These cases qualify for revisional Roux-en-Y gastric bypass (RRYGB).

METHODS

This retrospective cohort study analyzed data from 2008 to 2019. A stratification analysis and multivariate logistic regression for prediction modeling compared the possibility of sufficient % excess weight loss (%EWL) ≥ 50 or insufficient %EWL < 50 between three different RRYGB procedures, with primary Roux-en-Y gastric bypass (PRYGB) as the control during 2 years of follow-up. A narrative review was conducted to test the presence of prediction models in the literature and their internal and external validity.

RESULTS

A total of 558 patients underwent PRYGB, and 338 underwent RRYGB after VBG, LSG, and GB, and completed 2 years of follow-up. Overall, 32.2% of patients after RRYGB had a sufficient %EWL ≥ 50 after 2 years, compared to 71.3% after PRYGB (p ≤ 0.001). The total %EWL after the revision surgeries for VBG, LSG, and GB was 68.5%, 74.2%, and 64.1%, respectively (p ≤ 0.001). After correcting for confounding factors, the baseline odds ratio (OR) or sufficient %EWL ≥ 50 after PRYGB, LSG, VBG, and GB was 2.4, 1.45, 0.29, and 0.32, respectively (p ≤ 0.001). Age was the only significant variable in the prediction model (p = 0.0016). It was impossible to develop a validated model after revision surgery because of the differences between stratification and the prediction model. The narrative review showed only 10.2% presence of validation in the prediction models, and 52.5% had external validation.

CONCLUSION

Overall, 32.2% of all patients after revisional surgery had a sufficient %EWL ≥ 50 after 2 years, compared to PRYGB. LSG had the best outcome in the revisional surgery group in the sufficient %EWL group and the best outcome in the insufficient %EWL group. The skewness between the prediction model and stratification resulted in a partially non-functional prediction model.

Validation of the Individual Metabolic Surgery Score for Bariatric Procedure Selection in the Merged Data of Two Randomized Clinical Trials (SLEEVEPASS and SM-BOSS)

BACKGROUND

LSG and LRYGB are globally the most common bariatric procedures. IMS score categorizes T2D severity (mild, moderate, and severe) based on 4 independent preoperative predictors of long-term remission as follows: T2D duration, number of diabetes medications, insulin use, and glycemic control. IMS score has not been validated in a randomized patient cohort.

OBJECTIVES

To assess the feasibility of individualized metabolic surgery (IMS) score in facilitating procedure selection between laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB) for patients with severe obesity and type 2 diabetes (T2D).

SETTING

Merged individual patient-level 5-year data of 2 large randomized clinical trials (SLEEVEPASS and SM-BOSS [Swiss Multicenter Bypass or Sleeve Study]).

METHODS

IMS score was calculated for study patients and its performance was analyzed.

RESULTS

One hundred thirty-nine out of 155 patients with T2D had available preoperative data to calculate IMS score as follows: mild stage (n = 41/139), moderate stage (n = 77/139), severe stage (n = 21/139). At 5 years, 135 (87.1%, 67 LSG/68 LRYGB) were available for follow-up and 121 patients had both pre- and postoperative data. Diabetes remission rates according to preoperative IMS score were as follows: mild stage 87.5% (n = 14/16) after LSG and 85.7% (n = 18/21) after LRYGB (P = .999), moderate stage 42.9% (n = 15/35) and 45.2% (n = 14/31) (P = .999), and severe stage 18.2% (n = 2/11) and 0% (n = 0/7) (P = .497), respectively. The T2D remission rate varied significantly between the stages as follows: mild versus moderate odds ratio (OR) 8.3 (95% CI, 2.8-24.0; P < .001), mild versus severe OR 52.2 (95% CI 9.0-302.3; P < .001), and moderate versus severe OR 6.3 (95% CI, 1.3-29.8; P = .020).

CONCLUSIONS

In our study, remission rates of T2D were not statistically different after LSG and LRYGB among all patients and among patients with mild, moderate, and severe diabetes stratified by the IMS score. However, the study may be underpowered to detect differences due to small number of patients in each subgroup. IMS score seemed to be useful in predicting long-term T2D remission after bariatric surgery.

Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

Predictors of diabetes relapse after metabolic surgery in Asia

BACKGROUND

Limited studies have focused on diabetes relapse after metabolic surgery, especially among Asians.

OBJECTIVES

To identify the predictors of diabetes relapse following initial postoperative remission in Asia.

SETTING

Four tertiary hospitals METHODS: We assessed 342 patients (age, 41.0 ± 10.8 yr; body mass index [BMI], 39.6 ± 7.3 kg/m²) with complete diabetes data before and 1 and 3 years after metabolic surgery. A total of 290 (84.8%) and 277 (81.0%) patients had diabetes remission at 1 and 3 years after surgery. Logistic regressions were performed to identify the independent predictors of diabetes relapse. Two published predictive models for diabetes remission were also tested for relapse.

RESULTS

Of the 290 patients with 1-year diabetes remission, 29 (10%) experienced a relapse at 3 years after surgery. The area under the receiver operating characteristic curve of the ABCD score in predicting 1-year remission, 3-year remission, and 3-year relapse were .814, .793, and .795, while those of the DiaRem2 score were .823, .774, and .701, respectively. The baseline age, BMI, and insulin use were independent predictors for relapse. The most powerful predictive model for relapse was composed of preoperative insulin use, 1-year A1C, and a change in BMI between the first and third year (C-statistic: .919).

CONCLUSION

The ABCD score predicted both mid-term postoperative diabetes remission and relapse in Asians. Initial older age, lower BMI, insulin use, higher 1-year A1C, and weight regain were independent predictors of relapse. Personalized strategies should be proposed for those at risk of relapse to optimize diabetes outcomes after surgery.

Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

A Scoping Review of Artificial Intelligence and Machine Learning in Bariatric and Metabolic Surgery: Current Status and Future Perspectives

Artificial intelligence (AI) is a revolution in data analysis with emerging roles in various specialties and with various applications. The objective of this scoping review was to retrieve current literature on the fields of AI that have been applied to metabolic bariatric surgery (MBS) and to investigate potential applications of AI as a decision-making tool of the bariatric surgeon. Initial search yielded 3260 studies published from January 2000 until March 2021. After screening, 49 unique articles were included in the final analysis. Studies were grouped into categories, and the frequency of appearing algorithms, dataset types, and metrics were documented. The heterogeneity of current studies showed that meticulous validation, strict reporting systems, and reliable benchmarking are mandatory for ensuring the clinical validity of future research.