Sarcopenia and impairment in cognitive and physical performance
Bibliographic record
Abstract
BACKGROUND: Whether older adults with sarcopenia who underperform controls on tests of physical performance and cognition also have a higher likelihood of combined cognitive-physical impairment is not clear. We assessed the impact of sarcopenia on impairment in both aspects of functionality and the relative contribution of its components, muscle mass and strength. METHODS: Two hundred and twenty-three community-dwelling adults aged 40 years and older (mean age =68.1±10.6 years; 65% female) were recruited and underwent physical functionality, anthropometry, and cognitive testing. Participants with low muscle mass were categorized as pre-sarcopenic; those with low muscle mass and muscle strength as sarcopenic; those with higher muscle mass and low muscle strength only were categorized as non-sarcopenic and were compared on risk of cognitive impairment (Montreal Cognitive Assessment <26; Ascertaining Dementia 8 ≥2), physical impairment (Mini Physical Performance Test <12), both, or neither by ordinal logistic regression. RESULTS: Compared to controls, those with sarcopenia were six times more likely to have combined cognitive impairment/physical impairment with a fully adjusted model showing a three-fold increased odds ratio. The results were consistent across different measures of global cognition (odds ratio =3.46, 95% confidence interval =1.07-11.45 for the Montreal Cognitive Assessment; odds ratio =3.61, 95% confidence interval =1.11-11.72 for Ascertaining Dementia 8). Pre-sarcopenic participants were not different from controls. The effect of sarcopenia on cognition is related to low muscle strength rather than low muscle mass. CONCLUSION: Individuals with sarcopenia are not only more likely to have single but also to have dual impairment in cognitive and physical function. Interventions designed to prevent sarcopenia and improve muscle strength may help reduce the burden of cognitive and physical impairments of functionality in community-dwelling seniors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".