Serum branched‐chain amino acid levels are associated with fracture risk in Japanese women
Bibliographic record
Abstract
AIM: Branched-chain amino acids (BCAAs) have been shown to exert beneficial effects on muscle and bone metabolism; however, no studies to date have investigated whether BCAAs have beneficial effects on bone fractures. Herein, we aim to prospectively investigate the relationship between serum BCAA concentrations and the occurrence of vertebral fractures (VFs) in Japanese women. METHODS: During the observation period (7.5 ± 6.1 years), 188 of 983 participants experienced VF. Kaplan-Meier analyses were conducted to examine time-dependent variations in the vertebral compression fracture occurrence rate. Patients were stratified into quartiles based on serum BCAA concentration for this analysis. RESULTS: The analysis results indicated that the group with the lowest BCAA level developed VFs significantly earlier and with a higher frequency than the other groups (P < 0.001). A Cox proportional hazards model showed that BCAA concentration was a significant risk factor for incident fracture, even after adjusting for possible confounding factors. A series of multiple regression analyses were performed to identify factors related to serum BCAA concentration, with the results identifying levels of glycated hemoglobin (P < 0.001), adiponectin (P < 0.001), and NOx (P = 0.011) as significant factors associated with serum BCAA. CONCLUSIONS: Overall, the present study revealed that a lower serum BCAA level was an independent risk factor for incident VF in postmenopausal women. Geriatr Gerontol Int 2024; 24: 603-608.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".