Increased Risk of Myocardial Infarction in Inclusion Body Myositis: A Non‐Concurrent Cohort Study
Bibliographic record
Abstract
BACKGROUND: Idiopathic inflammatory myopathies, beyond inclusion body myositis (IBM), have demonstrated an increased risk of adverse cardiovascular outcomes, particularly myocardial infarction (MI). This study evaluated the risk of cardiovascular disease in IBM. METHODS: We conducted a non-concurrent cohort study utilizing the expanded Rochester Epidemiologic Project, including 50 patients with IBM, matched 1:6 to age-, sex-, and calendar year-matched referents without IBM. Baseline cardiovascular risk factors were recorded. Differences in baseline covariates were adjusted by the inverse probability of treatment weighting method. Participants were followed from the index date forward to determine relative risks (RR) and hazard ratios (HR) for the development of cardiovascular outcomes including MI, ischemic stroke, cardiomyopathy, congestive heart failure (CHF), and peripheral vascular disease (PVD). RESULTS: 50 patients with IBM and 294 matched population referents were included. Baseline cardiovascular risk factors were similar between groups. Aspirin use was more common (28% vs. 18%, p = 0.03) and statin use less common (26% vs. 38%, p = 0.04) in IBM versus referents. Patients with IBM had an increased hazard of MI compared to referents [HR: 5.79, 95% CI (2.51, 13.36)]. The risk of MI remained consistently elevated across all models, after accounting for potential confounders. For PVD, 16/50 IBM patients versus 16/287 referents were excluded due to pre-existing PVD at index (p < 0.001). Among remaining participants, RR for PVD was 2.38 (0.82, 6.9). IBM was not associated with an increased risk of ischemic stroke, cardiomyopathy, or CHF. CONCLUSIONS: IBM is associated with increased risk of MI compared to population referents. Heightened cardiovascular monitoring and prevention strategies are needed in IBM.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".