Longterm Blood Pressure Variability in Patients with Rheumatoid Arthritis and Its Effect on Cardiovascular Events and All-cause Mortality in RA: A Population-based Comparative Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To examine longterm visit-to-visit blood pressure (BP) variability in patients with rheumatoid arthritis (RA) versus non-RA subjects and to assess its effect on cardiovascular (CV) events and mortality in RA. METHODS: Clinic BP measures were collected in a population-based incident cohort of patients with RA (1987 American College of Rheumatology criteria met between January 1, 1995, and January 1, 2008) and non-RA subjects. BP variability was defined as within-subject SD in systolic and diastolic BP. RESULTS: The study included 442 patients with RA (mean age 55.5 yrs, 70% females) and 424 non-RA subjects (mean age 55.7 yrs, 69% females). Patients with RA had higher visit-to-visit variability in systolic BP (13.8 ± 4.7 mm Hg) than did non-RA subjects (13.0 ± 5.2 mm Hg, p = 0.004). Systolic BP variability declined after the index date in RA (p < 0.001) but not in the non-RA cohort (p = 0.73), adjusting for age, sex, and calendar year of RA. During the mean followup of 7.1 years, 33 CV events and 57 deaths occurred in the RA cohort. Visit-to-visit systolic BP variability was associated with increased risk of CV events (HR per 1 mm Hg increase in BP variability 1.12, 95% CI 1.01-1.25). Diastolic BP variability was associated with all-cause mortality in RA (HR 1.14, 95% CI 1.03-1.27), adjusting for systolic and diastolic BP, body mass index, smoking, diabetes, dyslipidemia, and use of antihypertensives. CONCLUSION: Patients with RA had higher visit-to-visit systolic BP variability than did non-RA subjects. There was a significant decline in systolic BP variability after RA incidence. Higher visit-to-visit BP variability was associated with adverse CV outcomes and all-cause mortality in RA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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".