HoiMan Kam1, Yinfang Tu1, Jiemin Pan1, Junfeng Han1, Pin Zhang2, Yuqian Bao3, Haoyong Yu4. 1. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, 200233, China. 2. Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China. 3. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, 200233, China. yqbao@sjtu.edu.cn. 4. Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, 200233, China. yuhaoyong111@163.com.
Abstract
BACKGROUND: Roux-en-Y gastric bypass (RYGB) is a major type of bariatric surgery. Various models have been established for facilitating clinical decision-making and predicting outcomes after RYGB; the ABCD, DiaRem, advanced-DiaRem (Ad-DiaRem), and DiaBetter scores are among the most commonly used risk prediction models. However, these models were primarily developed based on retrospective analyses of patients from Western countries at 1 year after RYGB. The present study was to assess the performance of these models and identify the optimal model, for predicting postoperative diabetes remission in diabetic Chinese patients. METHODS: The present study included a total of 253 RYGB patients; 214 completed a 1-year follow-up and 131 completed a 3-year follow-up. The assessments and comparisons of the predictive performance of the four models were based on both discrimination and calibration measures. Discrimination was assessed according to the area under the receiver operating characteristic curve (AUC), and calibration was evaluated by Hosmer-Lemeshow goodness-of-fit tests and predicted-to-observed ratios. RESULTS: One hundred thirteen (52.8%) in the 1-year follow-up group and 59 (45.0%) in the 3-year follow-up group achieved complete diabetes remission. Although all models showed similar discriminatory capacity and good calibration, the DiaBetter model exhibited the best predictive performance (1-year follow-up, AUC 0.760, 95% confidence interval [CI] 0.697-0.815, predicted-to-observed ratio 1.04; 3-year follow-up, AUC 0.804, 95% CI 0.726-0.868, predicted-to-observed ratio 0.95). CONCLUSIONS: The present results indicated that the DiaBetter model is the optimal model for predicting postoperative diabetes remission in diabetic Chinese individuals, due to its excellent predictive accuracy and ready availability for use in clinical practice.
BACKGROUND: Roux-en-Y gastric bypass (RYGB) is a major type of bariatric surgery. Various models have been established for facilitating clinical decision-making and predicting outcomes after RYGB; the ABCD, DiaRem, advanced-DiaRem (Ad-DiaRem), and DiaBetter scores are among the most commonly used risk prediction models. However, these models were primarily developed based on retrospective analyses of patients from Western countries at 1 year after RYGB. The present study was to assess the performance of these models and identify the optimal model, for predicting postoperative diabetes remission in diabetic Chinese patients. METHODS: The present study included a total of 253 RYGB patients; 214 completed a 1-year follow-up and 131 completed a 3-year follow-up. The assessments and comparisons of the predictive performance of the four models were based on both discrimination and calibration measures. Discrimination was assessed according to the area under the receiver operating characteristic curve (AUC), and calibration was evaluated by Hosmer-Lemeshow goodness-of-fit tests and predicted-to-observed ratios. RESULTS: One hundred thirteen (52.8%) in the 1-year follow-up group and 59 (45.0%) in the 3-year follow-up group achieved complete diabetes remission. Although all models showed similar discriminatory capacity and good calibration, the DiaBetter model exhibited the best predictive performance (1-year follow-up, AUC 0.760, 95% confidence interval [CI] 0.697-0.815, predicted-to-observed ratio 1.04; 3-year follow-up, AUC 0.804, 95% CI 0.726-0.868, predicted-to-observed ratio 0.95). CONCLUSIONS: The present results indicated that the DiaBetter model is the optimal model for predicting postoperative diabetes remission in diabetic Chinese individuals, due to its excellent predictive accuracy and ready availability for use in clinical practice.
Authors: Kajsa Sjöholm; Lena M S Carlsson; Magdalena Taube; Carel W le Roux; Per-Arne Svensson; Markku Peltonen Journal: Diabetes Care Date: 2020-09-01 Impact factor: 19.112
Authors: Izabela A Karpińska; Joanna Choma; Michał Wysocki; Alicja Dudek; Piotr Małczak; Magdalena Szopa; Michał Pędziwiatr; Piotr Major Journal: Langenbecks Arch Surg Date: 2021-07-13 Impact factor: 2.895