Overview of rehabilitation interventions for ESPEN/EASO-defined sarcopenic obesity: a scoping review
Bibliographic record
Abstract
PURPOSE: Sarcopenic obesity (SO) is a global concern characterized by the co-existence of sarcopenia and obesity. Although various interventions are recommended for SO, inconsistent definitions represent a barrier to clinical practice. This scoping review aimed to provide an overview of rehabilitation interventions for SO based on the definitions provided by the European Society for Clinical Nutrition and Metabolism and the European Association for the Study of Obesity. METHODS: A systematic search was conducted across nine databases, with a final search conducted on February 27, 2024. The eligible studies included randomized controlled trials, prospective and retrospective cohort studies, and case-control studies without restrictions on language, country, sex, or publication date. The risk-of-bias assessment focused on muscle strength, physical function, and body composition. The risk of bias was assessed using the Risk of Bias 2 tool for randomized trials and the Newcastle-Ottawa scale for non-randomized studies. RESULTS: Four randomized controlled trials involving 246 participants were included, all of which were conducted in communities. In addition, three studies comprised exclusively female participants, and all four studies employed resistance exercises. One study used a combination of resistance exercises and nutritional interventions. The overall risk of bias was high for all outcomes. CONCLUSION: The reported studies emphasized the limited number of studies covering diverse populations and settings. Further studies with improved methodological rigor are essential to identify effective rehabilitation strategies for SO. REGISTRATION: The study protocol was registered in the Open Science Framework ( https://osf.io/wak9n/ ) on January 31, 2024.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.023 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".