Beyond Calcium and Vitamin D: Exploring Creatine, β-Hydroxy-β-methylbutyrate, Prebiotics and Probiotics in Osteosarcopenia
Bibliographic record
Abstract
Background/Objectives: Osteosarcopenia, the coexistence of osteoporosis and sarcopenia, in older adults, is an emerging geriatric syndrome linked to functional decline, increased frailty, and higher mortality. Evidence supports the benefits of interventions such as physical exercise and dietary supplementation with vitamin D, calcium, and protein in this population. Additionally, emerging supplements—such as creatine, β-hydroxy-β-methylbutyrate (HMB), probiotics, and prebiotics—are being investigated for their potential to enhance bone density, muscle mass, and physical function. This review aims to examine the current evidence on these novel nutritional strategies and provide a comprehensive synthesis of how these factors may synergistically influence both muscle and bone health. Methods: A comprehensive literature search was conducted across the PubMed/MEDLINE, Embase, Scopus, and Google Scholar databases. Relevant observational studies, clinical trials, systematic reviews, and meta-analyses published from January 2020 to June 2025 were included, and then a reverse search in the bibliography was used to expand on definitions and concepts. Conclusions: Nutritional interventions for osteosarcopenia play a pivotal role in not only improving bone and muscle composition but also enhancing functional outcomes in older adults. Emerging strategies involving creatine monohydrate, HMB, probiotics, and prebiotics show potential as part of a comprehensive patient-centered approach. However, further research is needed to determine the most effective strategies and to identify which patients are most likely to benefit from each supplement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".