Giant cell arteritis and cardiovascular disease in older adults
Bibliographic record
Abstract
OBJECTIVE: To explore the association between giant cell arteritis (GCA) and subsequent cardiovascular disease in older adults. DESIGN: Population based retrospective cohort study. SETTING: The entire province of Ontario, Canada. PARTICIPANTS: Patients aged 66 years and older with newly diagnosed GCA (n = 1141), osteoarthritis (n = 172,953), or neither (n = 200,000). Patients with neither were randomly selected from the general population and formed the control group. MAIN OUTCOME MEASURES: The primary composite outcome was based on a subsequent diagnosis or surgical treatment for coronary artery disease, stroke, peripheral arterial disease, or aneurysm or dissection of the aorta. RESULTS: The composite end point was more common in seniors with GCA (12.1/1000 person-years) than in patients with osteoarthritis (7.3/1000 person-years) or neither condition (5.3/1000 person-years). The adjusted hazard ratio for cardiovascular disease was 1.6 (95% confidence interval (CI) 1.1 to 2.2) in patients with GCA versus patients with osteoarthritis, and 2.1 (95% CI 1.5 to 3.0) in patients with GCA versus unaffected controls. CONCLUSIONS: Older adults with GCA appear to be at increased risk for developing cardiovascular disease. Whether an aggressive approach to cardiovascular risk factor modification is particularly beneficial in these patients remains to be determined.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".