C-Reactive Protein and Frailty in the Elderly: A Literature Review
Bibliographic record
Abstract
Chronic inflammation is a well-established background process in many age-related diseases. Many recent studies investigate the use of various inflammatory biomarkers such as C-reactive protein (CRP), interleukin-6, and interleukin-1 as predictors of physical and cognitive performance among elders. The phenotype of frailty has also been associated with underlying inflammatory mechanisms. The aim of this article was to review the literature referring to the correlation of CRP serum levels and frailty in older individuals. We tried to identify all relevant publications regarding the relation of CRP as an index of frailty in the elderly and its potential use. Although many studies in the recent medical literature positively associate serum CRP levels and frailty in older individuals, some do not, and some raise some interesting questions and set the basis for future studies. The association of CRP and frailty in elder patients should be considered when clinicians interpret inflammatory biomarkers in various clinical settings in such patients. Well-designed, prospective clinical trials are warranted to better assess the role and pathophysiology of frailty in the elderly and its mechanisms as also the exact role of CRP as an inflammatory marker and as a prognostic index in this syndrome.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".