Cardiac arrest in seronegative idiopathic inflammatory myopathy: a case report
Bibliographic record
Abstract
Background: Idiopathic inflammatory myopathies (IIMs) are autoimmune diseases that are characterized by muscle injury. These disorders can cause cardiomyopathy and heart failure, myocarditis, and arrhythmias. However, only a few cases of cardiac arrest as a result of IIMs have been previously reported. Case summary: A 46-year-old male presented with an out-of-hospital ventricular fibrillation cardiac arrest. A diagnosis of IIM had been made through a muscle biopsy performed 2 years before presentation. The patient had a positive anti-nuclear antibody but negative myositis-specific antibodies. His initial symptoms of IIM were mild and consisted of myalgias. His only cardiac symptoms were minor palpitations that occurred 3 years prior to the cardiac arrest, with a negative Holter monitor test result at that time. His cardiac catheterization was normal. He was suspected to have myocarditis, and a rheumatologist was consulted, following which the patient was initiated on intravenous immunoglobulin (IVIG). Cardiac magnetic resonance imaging demonstrated evidence of chronic myocarditis and an ejection fraction of 44%. He was initiated on goal-directed medical therapy for heart failure. A VVI implantable cardioverter defibrillator was implanted for secondary prevention. He was discharged and prescribed additional immunosuppression including further IVIG infusions, prednisone taper and rituximab infusions. Discussion: Our case demonstrates that cardiac arrest in IIM is not only plausible, but can be the first major cardiac manifestation of the disease. When a diagnosis of IIM is made, patients require a thorough assessment of cardiac symptomatology and a low threshold for additional cardiac investigations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".