Alfredo D Guerron1, Juan Esteban Perez2, Thomas Risoli3, Hui-Jie Lee4, Dana Portenier2, Leonor Corsino5. 1. Department of Surgery, Division of Metabolic and Weight Loss Surgery, Duke University, Durham, North Carolina. Electronic address: alfredo.guerron-cruz@duke.edu. 2. Department of Surgery, Division of Metabolic and Weight Loss Surgery, Duke University, Durham, North Carolina. 3. Duke Biostatistics, Epidemiology, Research and Design (BERD) Methods Core, Duke University, Durham, North Carolina. 4. Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina. 5. Department of Medicine, Division of Endocrinology, Metabolism and Nutrition, Duke University School of Medicine, Durham, North Carolina.
Abstract
BACKGROUND: The DiaRem score has proven to be a reliable predictor tool for diabetes remission in Roux-en-Y gastric bypass (RYGB), as well as laparoscopic adjustable gastric band (LAGB) and laparoscopic sleeve gastrectomy (LSG). To our knowledge there are no studies that analyze DiaRem in patients undergoing biliopancreatic diversion with duodenal switch (BPD/DS). OBJECTIVE: To test the validity of the DiaRem score as a predictor of type 2 diabetes remission at 1 year post surgery in patients who underwent LABG, LSG, RYGB, and BPD/DS, as well as to develop and test a novel model that uses DiaRem to predict type 2 diabetes remission by procedure type (LABG, LSG, RYGB, and BPD/DS). SETTING: University Medical Center, United States. METHODS: A retrospective review of institutional records identified patients who underwent primary bariatric procedures (LAGB, LSG, RYGB, and BPD/DS) between January 1, 2000 to April 10, 2017, had a diagnosis of diabetes and had complete preoperative and 1-year postoperative follow-up information. A univariable logistic regression model was fit to assess the association between DiaRem score and diabetes remission. A multivariable logistic regression model was created, including procedure type and other preoperative characteristics. The area under the receiver operating curve (AUROC) was calculated to analyze the performance of both models for the entire cohort as well as a BPD/DS only subgroup. RESULTS: A total study cohort of 602 was obtained. The majority of patients underwent RYGB (456; 75.7%), followed by LSG (84; 14.0%), BPD/DS (35; 5.8%), and LAGB (27; 4.5%). The multivariable regression model with RYGB as the reference procedure, showed that BPD/DS results in higher odds of type 2 diabetes remission at 1 year post surgery (adjusted odds ratio [OR] 3.29, 95% confidence interval [CI] 1.27, 8.51), while LSG (adjusted OR .52, 95%CI .29, .93) and LAGB resulted in lower odds (adjusted OR.23, 95% CI.09,.60). The univariable DiaRem model and the novel model were determined to be moderately strong in classifying diabetes remission in the entire cohort (AUROC: .79, 95% CI: .75, .83 and .82, 95% CI: .79, .85, respectively) as well as in the BPD/DS sub-group (AUROC: .85, 95% CI: .70, .99 and .84, 95% CI .69, .99, respectively). CONCLUSION: Our study shows that the DiaRem score is a reliable tool to predict diabetes remission, amongst a wide variety of different procedures as well as specifically those receiving BPD/DS. Our novel model, which takes into account procedure type, not only shows that BPD/DS patients have the highest odds of diabetes remission than other procedures, but also that this model performs significantly better at predicting diabetes remission than DiaRem alone.
BACKGROUND: The DiaRem score has proven to be a reliable predictor tool for diabetes remission in Roux-en-Y gastric bypass (RYGB), as well as laparoscopic adjustable gastric band (LAGB) and laparoscopic sleeve gastrectomy (LSG). To our knowledge there are no studies that analyze DiaRem in patients undergoing biliopancreatic diversion with duodenal switch (BPD/DS). OBJECTIVE: To test the validity of the DiaRem score as a predictor of type 2 diabetes remission at 1 year post surgery in patients who underwent LABG, LSG, RYGB, and BPD/DS, as well as to develop and test a novel model that uses DiaRem to predict type 2 diabetes remission by procedure type (LABG, LSG, RYGB, and BPD/DS). SETTING: University Medical Center, United States. METHODS: A retrospective review of institutional records identified patients who underwent primary bariatric procedures (LAGB, LSG, RYGB, and BPD/DS) between January 1, 2000 to April 10, 2017, had a diagnosis of diabetes and had complete preoperative and 1-year postoperative follow-up information. A univariable logistic regression model was fit to assess the association between DiaRem score and diabetes remission. A multivariable logistic regression model was created, including procedure type and other preoperative characteristics. The area under the receiver operating curve (AUROC) was calculated to analyze the performance of both models for the entire cohort as well as a BPD/DS only subgroup. RESULTS: A total study cohort of 602 was obtained. The majority of patients underwent RYGB (456; 75.7%), followed by LSG (84; 14.0%), BPD/DS (35; 5.8%), and LAGB (27; 4.5%). The multivariable regression model with RYGB as the reference procedure, showed that BPD/DS results in higher odds of type 2 diabetes remission at 1 year post surgery (adjusted odds ratio [OR] 3.29, 95% confidence interval [CI] 1.27, 8.51), while LSG (adjusted OR .52, 95%CI .29, .93) and LAGB resulted in lower odds (adjusted OR.23, 95% CI.09,.60). The univariable DiaRem model and the novel model were determined to be moderately strong in classifying diabetes remission in the entire cohort (AUROC: .79, 95% CI: .75, .83 and .82, 95% CI: .79, .85, respectively) as well as in the BPD/DS sub-group (AUROC: .85, 95% CI: .70, .99 and .84, 95% CI .69, .99, respectively). CONCLUSION: Our study shows that the DiaRem score is a reliable tool to predict diabetes remission, amongst a wide variety of different procedures as well as specifically those receiving BPD/DS. Our novel model, which takes into account procedure type, not only shows that BPD/DSpatients have the highest odds of diabetes remission than other procedures, but also that this model performs significantly better at predicting diabetes remission than DiaRem alone.