Risk factors for prevalent and incident hypertension in rheumatoid arthritis: data from the Canadian Early Arthritis Cohort
Bibliographic record
Abstract
Objective: Hypertension (HTN) is a common comorbidity in RA. This study aimed to explore the prevalence and incidence of HTN and baseline factors associated with incident HTN in early RA (ERA). Methods: Data were from the Canadian Early Arthritis Cohort (CATCH), an inception cohort of ERA patients having <1 year of disease duration. HTN was determined by patient- or physician-reported diagnosis, the use of anti-hypertensives and/or blood pressure. Multivariable logistic regression was performed to determine baseline factors associated with prevalent and incident HTN in this population. Results: The study sample included 2052 ERA patients [mean age 55 years (s.d. 14), 71% female). The prevalence of HTN at study enrolment was 26% (23% in females and 34% in males). In both sexes, prevalent HTN was associated with older age, diabetes and hyperlipidaemia. HTN was associated with being overweight or high alcohol consumption in females. Of the RA patients who did not have HTN at enrolment, 24% (364/1518) developed HTN during the median follow-up period of 5 years (range 1-8). Baseline factors significantly associated with incident HTN were older age, being overweight, excess alcohol consumption and having hyperlipidaemia. Incident HTN was associated with high alcohol consumption in males and with hyperlipidaemia in females. RA-associated disease factors and treatments were not significantly associated with prevalent or incident HTN. Conclusions: Early RA patients had a high incidence of hypertension with the highest risk in older patients with traditional cardiovascular risk factors.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".