Use of Lipid-lowering Agents in Rheumatoid Arthritis: A Population-based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Rheumatoid arthritis (RA) is associated with an increased risk of cardiovascular disease and mortality. Lipid-lowering therapy is reportedly underused in patients with RA. Longitudinal cohort studies comparing use of lipid-lowering medications in patients with RA versus the general population are lacking. METHODS: Cardiovascular risk factors, lipid measures, and use of lipid-lowering agents were assessed in a population-based inception cohort of patients with RA and a cohort of non-RA subjects followed from January 1, 1988, to December 31, 2008. The National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATPIII) guidelines were assessed at the time of each lipid measure throughout followup. Time from meeting guidelines to initiation of lipid-lowering agents was assessed using Kaplan-Meier methods. RESULTS: The study population included 412 RA and 438 non-RA patients with ≥ 1 lipid measure during followup and no prior use of lipid-lowering agents. Rates of lipid testing were lower among patients with RA compared to non-RA subjects. Among patients who met NCEP ATPIII criteria for lipid-lowering therapy (n = 106 RA; n = 120 non-RA), only 27% of RA and 26% of non-RA subjects initiated lipid-lowering agents within 2 years of meeting the guidelines for initiation. CONCLUSION: There was substantial undertreatment in both the RA and the non-RA cohorts who met NCEP ATPIII criteria for initiation of lipid-lowering agents. Patients with RA did not have as frequent lipid testing as individuals in the general population.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".