The epidemiology of osteoarthritis and its association with cardiovascular disease and diabetes
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is a highly prevalent chronic condition and the most common form of rheumatic disease. The relationship between OA and cardiovascular disease (CVD) and diabetes has not been observed prospectively and the data on descriptive epidemiology of administratively defined OA are limited. Objectives: 1) to determine whether OA increases the risk of CVD (myocardial infarction, ischemic heart disease, congestive heart failure, and stroke) and diabetes; 2) to examine the association between OA and prevalent CVD; 4) to estimate the prevalence, incidence, and trends of OA; and 5) to validate the administrative diagnosis of OA. Methods: Using a random sample (n = 640,000) from the British Columbia administrative database during the period 1991-2009, the crude and age-standardized incidence rates and the prevalence of OA were calculated. Administrative OA Definition 1 required at least one physician diagnosis or hospital admission, and Definition 2 required, at least two physician diagnoses in two years or one hospital admission. The relative risks (RR) of CVD and diabetes in persons with OA, compared to age-sex matched non-OA individuals, were estimated using Cox proportional hazards models. Based on the Canadian Community Health Survey (CCHS) data, odds ratio (OR) between OA and heart disease was obtained. The validity of the two administrative definitions was determined using four clinical reference standards. Results: The overall prevalence of OA on March 2009, was 19.7%, and the incidence rate in the year 2008/09 was 14.6/1000 person-years under Definition 1. The adjusted RRs (95% CI) for CVD were 1.26 (1.13-1.42), 1.17 (1.07-1.26), 1.08 (0.97-1.19), and 1.15 (1.04-1.27), among younger women, older women, younger men, and older men, respectively. For diabetes, adjusted RRs (95% CI) were 1.27 (1.18-1.38), 1.23 (1.12-1.34), 1.19 (1.09-1.29), and 0.94 (0.82-1.09) for younger women, older women, younger men, and older men, respectively. In the CCHS sample, ORs (95% CI) for heart disease were 1.35 (1.21-1.50) among men and 1.51 (1.39-1.64) among women. Conclusions: These novel findings update current knowledge of OA epidemiology and highlight the risks of CVD and diabetes among persons with OA. These data are useful in formulating public health policies around OA treatment and prevention.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".