Kingston Bariatric Centre of Excellence, Hotel Dieu Hospital, Kingston, Canada.
Department of Public Health Sciences, Queen's University, Kingston, Canada.
JPEN J Parenter Enteral Nutr. 2018 Mar;42(3):573-580. doi: 10.1177/0148607117697934. Epub 2017 Dec 12.
Diabetes remission is defined as the return of glycemic control in the absence of medication or insulin use after bariatric surgery. We sought to identify and assess the clinical utility of a predictive model for remission of type 2 diabetes mellitus in a population seeking bariatric surgery.
A retrospective cohort design was applied to presurgical data on patients referred for Roux-en-Y gastric bypass (RYGB) or vertical sleeve gastrectomy (VSG). The model developed from logistic regression was compared with a published model through receiver operating characteristic analyses.
At 12 months postoperatively, 59.7% of the cohort was remitted, with no differences between RYGB and VSG. Logistic regression analyses yielded a model in which 4 preoperative variables reliably predicted remission. A Hosmer-Lemeshow goodness-of-fit test result of 0.204 indicated good fit of the developed prediction model to our outcome data. The predictive accuracy of this prediction model was compared with a published model, and an associated variation with diabetes years was substituted for age in our patient population. Our model was the most accurate.
Using these predictors, healthcare providers may be able to better counsel patients who are living with diabetes and considering bariatric surgery on the likelihood of achieving remission from the intervention. This refined prediction model requires further testing in a larger sample to evaluate its external validity.
糖尿病缓解是指在没有药物或胰岛素使用的情况下，通过减重手术恢复血糖控制。我们旨在确定和评估一种用于预测接受减重手术的 2 型糖尿病缓解的临床实用模型。
采用回顾性队列设计，对接受 Roux-en-Y 胃旁路术（RYGB）或垂直袖状胃切除术（VSG）的患者术前数据进行分析。通过接受者操作特征分析，比较从逻辑回归中得出的模型与已发表的模型。
术后 12 个月，队列中有 59.7%的患者缓解，RYGB 和 VSG 之间没有差异。逻辑回归分析得出了一个模型，其中 4 个术前变量可靠地预测了缓解。Hosmer-Lemeshow 拟合优度检验结果为 0.204，表明开发的预测模型与我们的结果数据拟合良好。与已发表的模型相比，该预测模型的预测准确性，并在我们的患者群体中用糖尿病年数替代年龄进行了相关变化。我们的模型是最准确的。
使用这些预测因素，医疗保健提供者可能能够更好地为患有糖尿病并考虑接受减重手术的患者提供咨询，告知他们该干预措施缓解的可能性。这个经过改进的预测模型需要在更大的样本中进一步测试，以评估其外部有效性。
