Nomogram for Predicting 5-Year Diabetes Remission After Roux-en-Y Gastric Bypass Surgery in Chinese Patients with Obesity

Pan, Yunhui; Han, Xiaodong; Kam, HoiMan; Tu, Ya; Han, Junfeng; Zhang, Pin; Bao, Yuqian; Yu, Haoyong

doi:10.1007/s11695-022-05952-x

Cited by 2 publications

(4 citation statements)

References 28 publications

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“…Our results revealed that HbA1c, TGs, diabetes duration, insulin‐requiring, and hypercholesterolaemia were identified as independent predictors of DR. To validate our findings further, we constructed the corresponding nomogram and assessed its stability and accuracy using the AUC and calibration curves in both the training and validation cohorts. We found that the AUC was higher than that of some previously established prediction models, indicating that our predictive model showed strong predictive capabilities 10,24 …”

Section: Discussionmentioning

confidence: 61%

“…We found that the AUC was higher than that of some previously established prediction models, indicating that our predictive model showed strong predictive capabilities. 10,24 Our study includes an analysis of two different surgeries, despite multiple publications suggesting that RYGB is more effective than SG in treating obesity combined with T2DM. 25,26 Because of the higher risk of postoperative infection in patients with diabetes, and the more common complications of RYGB compared with SG, we do not have a preference for the type of surgery in patients with obesity combined with diabetes.…”

Section: Discussionmentioning

confidence: 99%

“…Predictive models for the DR after BMS have been developed in numerous articles. However, the factors included in these models have varied across studies, primarily because of the heterogeneity of patients' preoperative characteristics and the duration of follow‐up 7–10 . According to the most recent criterion for DR, as stated by ADA in 2023, a minimum of 3 months of observation is required 11 .…”

Section: Introductionmentioning

confidence: 99%

“…However, the factors included in these models have varied across studies, primarily because of the heterogeneity of patients' preoperative characteristics and the duration of followup. [7][8][9][10] According to the most recent criterion for DR, as stated by ADA in 2023, a minimum of 3 months of observation is required. 11 However, a prediction model specifically designed for short-term DR after BMS in the Chinese population has not yet been developed.…”

Section: Introductionmentioning

confidence: 99%

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Construction and validation of a nomogram for predicting diabetes remission at 3 months after bariatric surgery in patients with obesity combined with type 2 diabetes mellitus

Yuan,

Wu,

Zeng

et al. 2023

Diabetes Obesity Metabolism

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AimBariatric metabolic surgery (BMS) is a proven treatment option for patients with both obesity and type 2 diabetes mellitus (T2DM). However, there is a lack of comprehensive reporting on the short‐term remission rates of diabetes, and the existing data are inadequate. Hence, this study aimed to investigate the factors that may contribute to diabetes remission (DR) in patients with obesity and T2DM, 3 months after undergoing BMS. Furthermore, our objective was to develop a risk‐predicting model using a nomogram.MethodsIn total, 389 patients with obesity and T2DM, who had complete preoperative information and underwent either laparoscopic sleeve gastrectomy or laparoscopic gastric bypass surgery between January 2014 and May 2023, were screened in the Chinese Obesity and Metabolic Surgery Database. The patients were randomly divided into a training set (n = 272) and a validation set (n = 117) in a 7:3 ratio. Potential factors for DR were analysed through univariate and multivariate logistic regression analyses and then modelled using a nomogram. The model's performance was evaluated using receiver operating characteristic curves and the area under the curve (AUC). Calibration plots were used to assess prediction accuracy and decision curve analyses were conducted to evaluate the clinical usefulness of the model.ResultsGlycated haemoglobin, triglycerides, duration of diabetes, insulin requirement and hypercholesterolaemia were identified as independent factors influencing DR. We have incorporated these five indicators into a nomogram, which has shown good efficacy in both the training cohort (AUC = 0.930) and validation cohort (AUC = 0.838). The calibration plots indicated that the model fits well in both the training and the validation cohorts, and decision curve analyses showed that the model had good clinical applicability.ConclusionThe prediction model developed in this study holds predictive value for short‐term DR following BMS in patients with obesity and T2DM.

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Section: Discussionmentioning

confidence: 61%