High Levels of Serum C‐Reactive Protein Are Associated with Greater Risk of All‐Cause Mortality, but Not Dementia, in the Oldest‐Old: Results from The 90+ Study
Bibliographic record
Abstract
OBJECTIVES: To evaluate whether high levels of C-reactive protein (CRP) in serum are associated with greater risk of all-cause dementia or mortality in the oldest-old. DESIGN: Prospective. SETTING: Research clinic and in-home visits. PARTICIPANTS: Population-based sample of adults (N=227; aged 93.9+/-2.8) from The 90+ Study, a longitudinal cohort study of people aged 90 and older. MEASUREMENTS: CRP levels were divided into three groups according to the assay detection limit: undetectable (<0.5 mg/dL), detectable (0.5-0.7 mg/dL), and elevated (> or =0.8 mg/dL). Neurological examination was used to determine dementia diagnosis (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria). Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using Cox regression, and results were stratified according to and apolipoprotein E4 (APOE4) genotype. RESULTS: Subjects with detectable CRP levels had significantly greater risk of mortality (HR=1.7, 95% CI=1.0-2.9), but not dementia (HR=1.2, 95% CI=0.6-2.1), 0.4 to 4.5 years later than subjects with undetectable CRP. The highest relative risk for dementia and mortality was in APOE4 carriers with detectable CRP (dementia HR=4.5, 95% CI=0.9-23.3; mortality HR=5.6, 95% CI=1.0-30.7). CONCLUSION: High levels of CRP are associated with greater risk of mortality in people aged 90 and older, particularly in APOE4 carriers. There was a trend toward greater risk of dementia in APOE4 carriers with high CRP levels, although this relationship did not reach significance. High levels of CRP in the oldest-old represent a risk factor for negative outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".