The effect of rheumatoid arthritis–associated autoantibodies on the incidence of cardiovascular events in a large inception cohort of early inflammatory arthritis
Bibliographic record
Abstract
Objective: . RA is associated with an increased risk of cardiovascular events (CVEs). The objective was to estimate independent effects of RA autoantibodies on the incident CVEs in patients with early RA. Methods: Patients were enrolled in the Canadian Early Inflammatory Arthritis Cohort, a prospective multicentre inception cohort. Incident CVEs, including acute coronary syndromes and cerebrovascular events, were self-reported by the patient and partially validated by medical chart review. Seropositive status was defined as either RF or ACPA positive. Multivariable Cox proportional hazards survival analysis was used to estimate the effects of seropositive status on incident CVEs, controlling for RA clinical variables and traditional cardiovascular risk factors. Results: . A total of 2626 patients were included: the mean symptom duration at diagnosis was 6.3 months ( s . d . 4.6), the mean age was 53 years ( s . d . 15), 72% were female and 86% met classification criteria for RA. Forty-six incident CVEs occurred over 6483 person-years [incidence rate 7.1/1000 person-years (95% confidence interval 5.3, 9.4)]. The CVE rate did not differ in seropositive vs seronegative subjects and seropositivity was not associated with incident CVEs in multivariable Cox regression models. Baseline covariates independently associated with incident CVEs were older age, a history of hypertension and a longer duration of RA symptoms prior to diagnosis. Conclusion: The rate of CVEs early in the course of inflammatory arthritis was low; however, delays in the diagnosis of arthritis increased the rate of CVEs. Hypertension was the strongest independent risk factor for CVEs. Results support early aggressive management of RA disease activity and co-morbidities to prevent severe complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".