Cardiovascular Disease Prevention in Rheumatoid Arthritis: Compliance with Diabetes Screening Guidelines
Bibliographic record
Abstract
OBJECTIVE: To evaluate compliance with diabetes screening guidelines for cardiovascular disease (CVD) prevention in rheumatoid arthritis (RA) compared to the general population. METHODS: We conducted the first longitudinal study of a population-based RA cohort including all prevalent RA cases in British Columbia between 1996 and 2006 and followed until 2010, with matched general population comparators. Using administrative data, we measured compliance with general population guidelines [i.e., testing plasma glucose (PG) at least once every 3 years after age 45] after excluding individuals with previous diabetes. Followup was divided into 3-year eligibility periods. Compliance was measured as the proportion of periods with ≥ 1 PG test performed. OR (95% CI) of compliance in RA (vs general population) was calculated using generalized estimating equation models, adjusting for age and sex. Mean compliance rate per patient was also calculated and compared using the Mann-Whitney U test. RESULTS: Analysis included 22,624 individuals with RA, contributing 48,724 three-year eligibility periods; and 22,579 people in a general population group, contributing 51,081 three-year eligibility periods. PG was measured in 72.3% (SD 37%) of the eligible time periods in the RA sample and in 70.4% (SD 38%) for the general population (OR 1.05, 95% CI 1.02-1.09, p < 0.0001). RA individuals met recommended screening guidelines in 71.4% of their eligible periods, compared to 70.6% (p < 0.001). Screening improved over time in RA relative to the general population. Family physicians ordered nearly all the PG tests. CONCLUSION: Compliance with general population guidelines for diabetes screening in RA was suboptimal, with little difference relative to the general population, despite a higher risk of CVD and diabetes.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".