Inflammation mediates approximately one quarter of excess relative all-cause mortality in persons with rheumatoid arthritis: the Trøndelag Health Study
Bibliographic record
Abstract
Inflammation may contribute to excess mortality in rheumatoid arthritis (RA) patients. We investigated associations to all-cause mortality of the inflammation markers high-sensitivity C-reactive protein (CRP), lactoferrin (neutrophil activation marker), and neopterin (monocyte activation marker). From the population-based Trøndelag Health Study (3rd wave 2006-2008), 316 RA patients and 43,579 controls were included. Lactoferrin and neopterin were quantified in a nested cohort (n = 283 RA patients, n = 3698 controls). Follow-up was until death found by linkage to the Norwegian Cause of Death Registry or 31.12.2018. All-cause mortality was analyzed using Cox regression and Cox regression-based mediation analysis. Having RA (hazard ratio (HR): 1.25, 95%CI: 1.00, 1.56, p = 0.048), and CRP ≥ 3 mg/L (HR: 1.50, 95%CI: 1.41, 1.60, p < 0.001) were associated with all-cause mortality. The overall excess relative mortality risk of having RA was 38%. CRP ≥ 3 mg/L mediated approximately 1/4 of this risk (p < 0.001). In the nested cohort, CRP ≥ 3 mg/L (HR: 1.51, 95%CI: 1.26, 1.80, p < 0.001) and neopterin (HR: 1.17, 95%CI: 1.01, 1.36, p = 0.031) were associated with all-cause mortality. In conclusion, CRP levels ≥ 3 mg/L mediated approximately a quarter of the 38% excess relative all-cause mortality risk associated with RA. Using definitions of RA remission with emphasis both on joint status and the level of general inflammation may help guide the most efficient treatment regimens.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".