Influence of Sarcopenia on the Development of Physical Disability: The Cardiovascular Health Study
Bibliographic record
Abstract
OBJECTIVES: To examine the temporal relationship between sarcopenia and disability in elderly men and women. DESIGN: Cardiovascular Health Study, a longitudinal study of cardiovascular disease and its risk factors in older people. SETTING: Four U.S. communities. PARTICIPANTS: Five thousand thirty-six men and women aged 65 and older. MEASUREMENTS: Whole-body skeletal muscle mass was measured at baseline, and subjects were classified as having normal muscle mass, moderate sarcopenia, or severe sarcopenia based on previously established thresholds. Disability was measured via questionnaire at baseline in up to eight annual follow-up examinations. The cross-sectional relationship between sarcopenia and prevalent disability at baseline was examined using logistic regression models. The longitudinal relation between sarcopenia and incident disability over 8 years of follow-up was examined using Cox proportional hazards models. RESULTS: At baseline, the likelihood of disability was 79% greater in those with severe sarcopenia (P<.001) but was not significantly greater in those with moderate sarcopenia (P=.38) than in those with normal muscle mass. During the 8-year follow-up, the risk of developing disability was 27% greater in those with severe sarcopenia (P=.006) but was not statistically greater in those with moderate sarcopenia (P=.23) than in those with normal muscle mass. CONCLUSION: Severe sarcopenia was a modest independent risk factor for the development of physical disability. The effect of sarcopenia on disability was considerably smaller in the longitudinal analysis than in the cross-sectional analysis.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".