Osteosarcopenia, bone-muscle interactions, and frailty risk: A prospective cohort study of community-dwelling older adults
Bibliographic record
Abstract
BACKGROUND: Osteosarcopenia, defined as the co-existence of osteopenia/osteoporosis and sarcopenia, may influence frailty risk in older adults. However, the longitudinal association between osteosarcopenia or its components and frailty remain unclear. This study aimed to address this. METHODS: Data from a prospective cohort study of community-dwelling adults in Australia. Frailty was defined by the presence of ≥ 3 components based on Fried criteria: exhaustion, slow gait speed, low grip strength, unintentional weight loss, and low physical activity. Osteosarcopenia was defined by osteopenia/osteoporosis (WHO criteria) and sarcopenia (European Working Group on Sarcopenia in Older People [EWGSOP2] and Sarcopenia Definition and Outcome consortium [SDOC]). Multivariable logistic regression models evaluated the associations between osteosarcopenia, its components and frailty. RESULTS: Of 300 enrolled, 151 (mean age: 65.1years, 59.6%women) completed follow-up (median: 4.8 years). Among 143 non-frails at baseline, 13 (9.1%) transitioned to frailty. Osteosarcopenia (versus non-osteosarcopenia) was associated with frailty irrespective of the definition used: EWGSOP2: OR = 9.53, 95%CI 2.53-35.92; SDOC: OR = 9.19, 95%CI 2.19-38.56). Grip strength reduction by 1 kg (OR = 0.92, 95%CI 0.84-1.00) and gait speed reduction by 0.1 m/sec (OR = 0.67, 95%CI 0.53-0.85) were associated with 8% and 33% lower odds of frailty, respectively, whereas bone mineral density or lean mass was not. An interaction between bone-muscle function and frailty risk was observed (p < 0.011), whereby higher values of grip strength were associated with lower odds of frailty when bone density was lower. CONCLUSION: In this prospective cohort study, osteosarcopenia increased the risk of frailty. Our interaction analysis suggests therapies targeting bone density and grip strength may mitigate frailty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".