Association of inflammatory markers with cognitive, pain and functionality assessment measures in long term care older adults
Bibliographic record
Abstract
Chronic inflammation may promote the development of age related conditions such as dementia, osteoporosis, pain and frailty especially in long term care (LTC) residing older adults. Aim of the study was to determine associations between inflammation and measures of functionality, cognition and pain in LTC residing older adults in Saskatoon, SK Canada. Those 60–80 y residents in LTCs, able to satisfactorily comply with protocol requirements were enrolled. Blood draws (inflammatory cytokines, hs‐CRP, 25(OH)‐vitamin D, cholesterol and prealbumin), vital signs, chart review and functional assessments (cognition, physical functioning, and pain) were done at baseline. Correlational analysis was used to study the relationship of inflammatory markers with the cognitive, functional and pain indices. Adults (n=26; 8 F, 18 M) (mean age 70.7 y) were enrolled. IL‐6 was significantly inversely correlated to all physical functioning measures. hs‐CRP was inversely correlated to cognitive tests (r = −0.54, p < 0.05) and activities of daily living (r = −41, p < 0.05). 25(OH)D was positively correlated to grip strength (r = 0.43, p < 0.05). Pain measures showed no significant correlations. Our results indicate an association of inflammatory markers with functionality tests, particularly grip strength, cognition, and activities of daily living in the LTC residing older adults. SHRF grant to Dr.T. Hadjistavropoulos QOL Team.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".