ArticleObesity surgery2021
Is It Possible to Predict Weight Loss After Bariatric Surgery?-External Validation of Predictive Models.
Article in Obesity surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 34 citations in OpenAlex.
- Long-Term Weight Loss Outcomes Following Sleeve Gastrectomy and Their Association with Diet Quality, Postoperative Complications, and Sociodemographic Factors: A Retrospective Cohort Study in Jeddah, Saudi Arabia.Journal of clinical medicine · 2026Article
- Machine and Deep Learning Models for Preoperative Prediction of Suboptimal Clinical Response One Year after Metabolic Bariatric Surgery: Findings from the Tehran Obesity Treatment Study.Obesity surgery · 2026Article
- Endoscopic sleeve gastroplasty video assessment: do technical features influence ESG integrity and weight loss at 6 and 12 months follow-up?Surgical endoscopy · 2025Article
- Actual weight loss trajectories after bariatric surgery compared with the SOPHIA prediction tool: An observational comparison study.Diabetes, obesity & metabolism · 2025Observational
- Exploring the prevalence and symptom presentation of food addiction among Norwegian bariatric surgery patients: associations with depression, dysregulated eating, and postoperative weight loss.Journal of eating disorders · 2024Article
- Pre-Surgery Cortisol Levels as Biomarker of Evolution after Bariatric Surgery: Weight Loss and Weight Regain.Journal of clinical medicine · 2024Article
- Prediction Model for Chronological Weight Loss After Bariatric Surgery in Korean Patients.Journal of metabolic and bariatric surgery · 2024Article
- Developing a Decision Aid for Clinical Obesity Services in the Real World: the DACOS Nationwide Pilot Study.Obesity surgery · 2024Article
- MBSAQIP Calculator Correlates Well with Weight Loss After Sleeve Gastrectomy in a Real World Setting.Obesity surgery · 2024Article
- Machine learning models to predict success of endoscopic sleeve gastroplasty using total and excess weight loss percent achievement: a multicentre study.Surgical endoscopy · 2024Article
- Comparative Analysis of Various Weight Loss Success Criteria Models After Bariatric Metabolic Surgery in Korean Morbid Obese Patients.Journal of metabolic and bariatric surgery · 2023Article
- Novel Insights into the Physiology of Nutrient Sensing and Gut-Brain Communication in Surgical and Experimental Obesity Therapy.Obesity surgery · 2023Review
- How Good is Stratification and Prediction Model Analysis Between Primary and Revisional Roux-en-Y Gastric Bypass Surgery? A Multi-center Study and Narrative Review.Obesity surgery · 2023Review
- Weight Regain in the Second Year after Sleeve Gastrectomy Could Be a Predictor of Long-Term Outcomes?Medicina (Kaunas, Lithuania) · 2023Article
- Weight Loss Prediction after Metabolic and Bariatric Surgery.Journal of obesity & metabolic syndrome · 2023Review
- Development and validation of a scoring system for pre-surgical and early post-surgical prediction of bariatric surgery unsuccess at 2 years.Scientific reports · 2021Observational
- Microstructural changes in human ingestive behavior after Roux-en-Y gastric bypass during liquid meals.JCI insight · 2021 · on this mapObservational
Corrections and comments
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Authors and funding
6 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBariatric surgery is the most effective obesity treatment. Weight loss varies among patients, and not everyone achieves desired outcome. Identification of predictive factors for weight loss after bariatric surgery resulted in several prediction tools proposed. We aimed to validate the performance of available prediction models for weight reduction 1 year after surgical treatment. MATERIALS AND
methodsThe retrospective analysis included patients after Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) who completed 1-year follow-up. Postoperative body mass index (BMI) predicted by 12 models was calculated for each patient. The correlation between predicted and observed BMI was assessed using linear regression. Accuracy was evaluated by squared Pearson's correlation coefficient (R
resultsOut of 760 patients enrolled, 509 (67.00%) were women with median age 42 years. Of patients, 65.92% underwent SG and 34.08% had RYGB. Median BMI decreased from 45.19 to 32.53kg/m
conclusionAlthough predicted BMI had reasonable correlation with observed values, none of evaluated models presented acceptable accuracy. All models tend to overestimate the outcome. Accurate tool for weight loss prediction should be developed to enhance patient's assessment.
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