Mortality and Predictors of Mortality in Rheumatoid Arthritis — A Role for Mannose-binding Lectin?
Bibliographic record
Abstract
OBJECTIVE: Patients with rheumatoid arthritis (RA) have increased overall and cardiovascular mortality. Mannose-binding lectin (MBL) may play differentiated roles in the pathogenesis of RA. We had observed that high serum levels of MBL increased the risk of ischemic heart disease in patients with RA. In this followup study we describe the mortality in a cohort of 229 Danish patients with RA. We examine if previously reported factors and MBL influence the risk of overall death and death due to cardiovascular disease. METHODS: Known predictors of RA mortality were assessed. MBL extended genotypes (YA/YA, YA/XA, XA/XA, YA/YO, XA/YO, YO/YO) were determined; MBL serum concentrations were measured. The vital status and causes of death were assessed in a prospective study. RESULTS: The median followup was 10.3 years. The overall risk of death was 4% per year. Comparing mortality in the RA cohort with mortality in an age- and sex-matched cohort based on the general Danish population, we found significantly increased overall mortality [standardized mortality ratio (SMR) 1.5, 95% CI 1.2-1.9, and cardiovascular mortality (SMR 1.7, 95% CI 1.3-2.6)]. In multivariate analysis, significant predictors of overall death were extraarticular manifestations, positive rheumatoid factor, increased C-reactive protein (CRP), poor nutritional state, and serum MBL. Predictors of cardiovascular death were Health Assessment Questionnaire score, increased CRP, poor nutritional state, and the high-producing MBL genotype YA/YA. CONCLUSION: Both overall and cardiovascular mortality were increased in Danish patients with RA. In our cohort, states of high MBL production and several previously reported factors contributed significantly to this increased risk of overall death and cardiovascular death.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".