Circulating Interleukin-6 (but Not Other Immune Mediators) Associates with Criteria for Fried’s Frailty among Very Old Adults
Bibliographic record
Abstract
Background and Aim. Frailty is a geriatric condition resulting from physiological changes covering the musculoskeletal, immune, and neuroendocrine systems, leading to a greater inflammatory state. The present research aimed to investigate the association of components of Fried’s frailty (as well as of the phenotype as a whole) with total serum levels of a panel of inflammatory mediators. Methods. One hundred and sixty-one very old patients (aged ≥80 years) devoid of cognitive decline were eligible for analyses. Clinical and biochemical data along with physical and cognitive assessments encompassing dual-energy X-ray scans and hand dynamometry were adopted to investigate frailty criteria, while circulating immune mediators (IFNγ, IL-2, IL-4, IL-6, IL-10, and TNFα) were assessed using high-throughput flow cytometry. Results. Preliminarily, IL-6 correlated positively with waist-to-hip ratio and C-reactive protein and negatively with glycemia. In analyses controlled for these factors, serum levels of IL-6 were comparatively augmented among the very old participants with reduced grip strength (OR = 3.299; 95% CI 1.08–6.09; p=0.032 ) and among those with slow walk speed (OR = 2.460; 95% CI 1.16–7.05; p=0.022 ). Conclusions. Our study shows a strong negative correlation of IL-6 levels with Fried’s frailty components of grip strength and walk speed in very old adults, regardless of confounding factors.
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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 | 0.000 |
| 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".