Songhao Hu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Songhao Hu has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
Cunchuan Wang
Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
1 shared publication- Cunchuan Wang
First Affiliated Hospital of Jinan University, Guangzhou, China
1 shared publication - Guanhua Lu
Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of Jinan University
1 shared publication Huajiang Liu
Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
1 shared publicationLiqin Zhang
Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
1 shared publication- Min Hu
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Jinan University, Guangzhou 510630, Guangdong, China
1 shared publication
Latest Publications
- Open Access
- 28 March 2023
- Published by Wolters Kluwer Health in International Journal of Surgery
- Vol. 109 (4) , 850-860
Determination of weight loss effectiveness evaluation indexes and establishment of a nomogram for forecasting the probability of effectiveness of weight loss in bariatric surgery: a retrospective cohort
Background: 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. Methods: 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. Results: 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. Conclusions: 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.
- 28 March 2023
- Published by Wolters Kluwer Health in International Journal of Surgery
- Vol. 109 (4) , 850-860
Open AccessDetermination of weight loss effectiveness evaluation indexes and establishment of a nomogram for forecasting the probability of effectiveness of weight loss in bariatric surgery: a retrospective cohort
Background: 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. Methods: 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. Results: 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. Conclusions: 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.