Departments of Metabolic and Bariatric Surgery.
Guangdong-Hong Kong-Macao Joint University Laboratory of Metabolic and Molecular Medicine, The University of Hong Kong and Jinan University, Guangzhou, Guangdong Province, China.
Int J Surg. 2023 Apr 1;109(4):850-860. doi: 10.1097/JS9.0000000000000330.
The purpose of this research was to determine the index that contributes the most to assessing the effectiveness of weight loss 1 year following bariatric surgery and to implement it as the clinical outcome to develop and confirm a nomogram to predict whether bariatric surgery would be effective.
Patient information was extracted from the Chinese Obesity and Metabolic Surgery Database for this retrospective study. The most contributing weight loss effectiveness evaluation index was created using canonical correlation analysis (CCA), and the predictors were screened using logistic regression analysis. A nomogram for estimating the likelihood of effectiveness of weight loss was constructed, and its performance was further verified.
Information was obtained for 540 patients, including 30 variables. According to the CCA, ≥25 percentage total weight loss was found to be the most correlated with patient information and contribute the most as a weight loss effectiveness evaluation index. Logistic regression analysis and nomogram scores identified age, surgical strategy, abdominal circumference, weight loss history, and hyperlipidemia as predictors of effectiveness in weight loss. The prediction model's discrimination, accuracy, and clinical benefit were demonstrated by the consistency index, calibration curve, and decision curve analysis.
The authors determined a 25 percentage total weight loss as an index for weight loss effectiveness assessment by CCA and next established and validated a nomogram, which demonstrated promising performance in predicting the probability of effectiveness of weight loss in bariatric surgery. The nomogram might be a valuable tool in clinical practice.
本研究旨在确定对评估减重手术后 1 年减肥效果最有贡献的指标,并将其作为临床结局来开发和验证一个列线图以预测减重手术是否有效。
本回顾性研究从中国肥胖与代谢外科数据库中提取患者信息。使用典型相关分析(CCA)创建最有贡献的减肥效果评估指标,并使用逻辑回归分析筛选预测因子。构建了一个用于估计减肥效果可能性的列线图,并进一步验证了其性能。
共获取 540 例患者的信息,包括 30 个变量。根据 CCA,≥25%的总体重减轻被发现与患者信息最相关,是评估减肥效果的最有效指标。逻辑回归分析和列线图评分确定年龄、手术策略、腹围、减肥史和高脂血症是减肥效果的预测因子。一致性指数、校准曲线和决策曲线分析显示了预测模型的判别力、准确性和临床获益。
作者通过 CCA 确定了 25%的总体重减轻作为减肥效果评估的指标,并建立和验证了一个列线图,该列线图在预测减重手术减肥效果的概率方面表现出良好的性能。该列线图可能是临床实践中的一种有价值的工具。