Risk of Cardiovascular Disease in Patients With Osteoarthritis: A Prospective Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: To determine the risk of cardiovascular disease (CVD) among osteoarthritis (OA) patients using population-based administrative data from British Columbia, Canada. METHODS: The medical history of a random sample of 600,000 individuals from 1991-2009 was analyzed. A total of 12,745 OA cases and up to 3 non-OA individuals matched by age, sex, and year of diagnosis were followed for CVD events. Cox proportional hazards and Poisson regression models were used to estimate the relative risks (RRs) of CVD, myocardial infarction, ischemic heart disease (IHD), congestive heart failure (CHF), and stroke after adjusting for available sociodemographic and medical factors. RESULTS: OA was an independent predictor of CVD. The adjusted RRs were 1.15 (95% confidence interval [95% CI] 1.04-1.27), 1.26 (95% CI 1.13-1.42), and 1.17 (95% CI 1.07-1.26) among older men, younger women, and older women, respectively. Analyses were stratified by age and sex due to statistically significant interactions between OA and age and sex. RRs among older men, younger women, and older women were 1.33 (95% CI 1.11-1.62), 1.66 (95% CI 1.37-2.01), and 1.45 (95% CI 1.22-1.72) for IHD, respectively, and 1.25 (95% CI 1.02-1.54), 1.29 (95% CI 1.00-1.68), and 1.20 (95% CI 1.03-1.39) for CHF, respectively. Compared to non-OA individuals, OA cases who underwent total joint replacements had a 26% increased risk of CVD. CONCLUSION: This prospective longitudinal study suggests that OA is associated with an increased risk of CVD. Older men and adult women with OA had a higher risk of CVD, particularly IHD and CHF. Further studies are needed to confirm these results and to elucidate the potential biologic mechanisms.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".