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05:10
Multidisciplinary Approach to Obesity Management: A Case Report
Published on: May 30, 2025
Analysis of weight loss after bariatric surgery using mixed-effects linear modeling
Ramsey M Dallal1, Brian B Quebbemann, Lacy H Hunt
1Department of Surgery, Albert Einstein Healthcare Network, Philadelphia, PA 19141, USA. dallalr@einstein.edu
Obesity Surgery
|March 12, 2009
Summary
Multivariable mixed models offer a more accurate way to analyze bariatric surgery weight loss outcomes than traditional methods. This approach provides better insights into patient weight changes over time.
Area of Science:
- Bariatric surgery outcomes
- Longitudinal data analysis
- Statistical modeling
Background:
- Traditional t-tests for bariatric surgery weight outcomes can be misleading.
- Uncontrolled comparisons limit research scope.
- A need exists for a more valid longitudinal analysis method.
Purpose of the Study:
- To develop and validate a multivariable mixed-effects model for analyzing weight loss after bariatric surgery.
- To compare the accuracy of mixed models with traditional uncontrolled analyses (%EWL).
Main Methods:
- Developed a mixed-effects model for weight after gastric bypass.
- Controlled for independent variables: gender, anastomotic technique, age, race, initial weight, height, and institution.
- Contrasted with traditional uncontrolled analyses using percent excess weight loss (%EWL).
Main Results:
- Initial weight and gender were the only independent predictors of weight loss (p<0.001).
- Weight as an outcome variable was more accurate than %EWL in multivariable models.
- Multivariable mixed models revealed women had lower average weight loss, contrary to uncontrolled analyses.
Conclusions:
- Multivariable mixed models offer superior accuracy for analyzing weight loss surgery outcomes.
- These models are recommended for studies involving repeated measurements of weight loss.
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