ArticleBMC surgery2026
Nutritional status and its determinants in obese patients with type 2 diabetes mellitus following Roux-en-Y gastric bypass surgery.
Article in BMC surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveObese patients with type 2 diabetes mellitus (T2DM) face unique long-term nutritional risks following Roux-en-Y gastric bypass (RYGB) surgery. This study aims to evaluate postoperative nutritional status in this population, identify key preoperative predictive factors, and develop and validate a clinical scoring system for predicting the risk of postoperative malnutrition.
methodsThis single-center retrospective cohort study consecutively included obese T2DM patients (body mass index [BMI] ≥ 32.5 kg/m²) who underwent RYGB between January 2020 and January 2023. The primary outcome was a composite endpoint of malnutrition at 12 months postoperatively, defined as moderate anemia (hemoglobin < 100 g/L) or hypoalbuminemia (albumin < 30 g/L). Univariate and multivariate logistic regression analyses were performed to identify independent predictors. Discrimination of the nomogram-based predictive model was assessed by the area under the receiver operating characteristic curve (AUC). Calibration was evaluated using bootstrap calibration plots.
resultsA total of 195 patients were included in the final analysis, with a 12-month postoperative malnutrition incidence of 31.8% (62/195). Female gender (odds ratio [OR] = 2.702, 95% confidence interval [CI]: 1.034–7.058) and diabetes duration ≥ 5 years (OR = 4.890, 95% CI: 1.416–16.894) were independent risk factors for postoperative malnutrition, whereas higher preoperative levels of albumin, hemoglobin, ferritin, and 25-hydroxyvitamin D were protective factors. The joint predictive model incorporating these six factors demonstrated excellent discriminative ability for predicting postoperative malnutrition and good calibration.
conclusionThe preoperative clinical risk prediction model based on six readily available indicators shows robust predictive performance, guiding individualized nutritional management.
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