Immediate and past cumulative effects of oral glucocorticoids on the risk of acute myocardial infarction in rheumatoid arthritis: a population-based study
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To determine the effect of glucocorticoids (GCs) on acute myocardial infarction (MI) risk in patients with RA. METHODS: Using administrative health data, we conducted a population-based cohort study of 8384 incident RA cases (1997-2006). Primary exposure was incident GC use. MI events were ascertained using hospitalization and vital statistics data. We used Cox proportional-hazards models and modelled GC use as four alternative time-dependent variables (current use, current dose, cumulative dose and cumulative duration), adjusting for demographics, comorbidities, cardiovascular drug use, propensity score and RA characteristics. Sensitivity analyses explored potential effects of unmeasured confounding. RESULTS: Within 50 238 person-years in 8384 RA cases, we identified 298 incident MI events. Multivariable models showed that current GC use was associated with 68% increased risk of MI [Hazard ratio (HR) = 1.68, 95% CI 1.14, 2.47]. Similarly, separate multivariable models showed that current daily dose (HR = 1.14, 95% CI 1.05, 1.24 per each 5 mg/day increase), cumulative duration of use (HR = 1.14, 95% CI 1.00, 1.29 per year of GC use) and total cumulative dose (HR = 1.06, 95% CI 1.02, 1.10 per gram accumulated in the past) were also associated with increased risk of MI. Furthermore, in the same multivariable model, current dose and cumulative use were independently associated with an increased risk of MI (10% per additional year on GCs and 13% per 5 mg/day increase). CONCLUSION: GCs are associated with an increased risk of MI in RA. Our results suggest a dual effect of GCs on MI risk, an immediate effect mediated through current dosage and a long-term effect of cumulative exposure.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it