A study of the correlation between sarcopenia and cognitive impairment in older individuals over 60 years: cross-sectional and longitudinal validation
Bibliographic record
Abstract
Objective To validate the correlation between sarcopenia and cognition, and explore cognitive subdomains affected by sarcopenia. Methods A case–control study was designed to recruit 90 individuals aged 60 and above from June to October 2023 in the same community, all individuals meeting the inclusion criteria were categorized according to the 2019 Asian criteria for sarcopenia and divided into the sarcopenia group and non-sarcopenia group at baseline. After a 12-week follow-up recording, individuals were classified into the aggravation group and alleviation group based on the change of sarcopenia severity. Sarcopenia tests including muscle mass, calf circumference, grip strength and physical function assessment, using Montreal Cognitive Assessment (MoCA) of nine dimensions for cognitive assessment. Results (1) There was a significant positive correlation between cognitive function and grip strength in males (r = 0.42, p < 0.05). (2) There was a moderate correlation between sarcopenia grading and MoCA score (r = −0.4, p < 0.001). (3) Individuals with sarcopenia had significantly lower MoCA total scores and sub-scores in executive function, fluency, calculation and delayed recall compared to non-sarcopenia group (p < 0.05). (4) After 12 weeks, the mean value of the change in fluency in the alleviation group increased by 0.33 points, while the aggravation group decreased by 0.2 points (W = 128, p < 0.05). Conclusion There is a correlation between sarcopenia and cognitive function, individuals with sarcopenia performing poorly in overall cognition as well as refined dimensions. The degree of cognition like fluency degenerates over time with increasing severity of sarcopenia.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".