减肥手术后的体重减轻量表日历:呼吁进行标准化预测

Mohamed A.M. Amin El Masry, Mostafa A.M. El Fiky
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引用次数: 0

摘要

背景:减肥手术的候选者需要在术后制定切实可行的减重目标,而外科医生则需要确保患者能够成功减重。本研究旨在提供一个体重减轻日历,估算手术后每周体重指数的平均下降幅度,并介绍一个简单的公式,帮助对减肥手术后的体重减轻结果进行简单可靠的预测。患者和方法:这是一项回顾性研究,研究对象包括连续接受减肥手术的患者。在术后随访期间,对患者的体重减轻数据进行了记录和分析。研究队列随机分为训练组(用于推导回归模型)和验证组(用于验证获得的模型)。研究结果术前平均体重指数(BMI)为 47.8 ± 8.3 kg/m 2 。随访 12 个月时,平均体重指数(BMI)为 30.04 ± 5.3 kg/m 2,平均超重百分比(EWL %)为 80.9 ± 18.7,平均总重百分比为 36.9 ± 5.8。回归方程如下1 年 EWL % = 139.71 + (- 0.291 × 年龄) + (- 0.981 × 基线体重指数) + (0.95 × 2 周 EWL %) + (- 17.151 × 以前的减肥手术)。回归公式为:1 年 BMI = (- 3.61) + (- 0.079 × 年龄) + (0.539× 基线 BMI) + (4.977 × 既往减肥手术)。结论患者的年龄、基线体重指数和既往减肥手术史是预测 1 年体重指数的重要因素。同样的变量与术后早期 EWL 百分比相结合,可显著预测 1 年 EWL 百分比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weight loss scale calendar postbariatric surgery: call for standardized prediction
Background: Candidates for bariatric surgery need realistic targets for weight loss after surgery and the surgeons need to ensure that the patients are on the way to successful weight loss. This study aimed to present a weight loss calendar estimating the average loss in BMI per week after the surgery and to introduce a simple formula to help make an easy and reliable prediction of the weight loss outcome after bariatric surgery. Patients and Methods: This is a retrospective study that included patients who were consecutively recruited for bariatric surgery. During the postoperative follow-up visits, the patients’ weight loss data were recorded and analyzed. The study cohort was randomly split into a training group (to derive the regression models) and a validation group (to validate the obtained model). Results: The mean preoperative BMI was 47.8 ± 8.3 kg/m 2 . At the 12-month follow-up, the mean BMI was 30.04 ± 5.3 kg/m 2 , the mean percentage of excess weight loss (EWL %) was 80.9 ± 18.7 and the mean percentage of total weight loss % was 36.9 ± 5.8. The regression equation was formulated as follows: 1-year EWL % = 139.71 + (- 0.291 × age) + (- 0.981 × baseline BMI) + (0.95 × 2-week EWL %) + (- 17.151 × previous bariatric procedure). The regression formula was: 1-year BMI = (- 3.61) + (- 0.079 × age) + (0.539×baseline BMI) + (4.977 × previous bariatric procedure). Conclusion: The patient’s age, baseline BMI and history of previous bariatric procedures were significant predictors of the 1-year BMI. The same variables, combined with the early postoperative EWL %, significantly predicted the 1-year EWL %.
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