Sudden Cardiac Death due to Giant Cell Inflammatory Processes*
Bibliographic record
Abstract
Granulomatous inflammation of the myocardium may occur in a number of systemic disease processes including those with infectious etiologies such as fungal, mycobacterial and parasitic infections, as well as hypersensitivity reactions, and rarely autoimmune disorders. In many of these disorders, giant cells are components of the inflammatory infiltrate. Systemic granulomatous processes of unknown pathogenesis, most notably sarcoidosis, may also be associated with involvement of the myocardium. Occasionally, these disorders are associated with sudden death due to pathologic involvement of the heart. In contrast, giant cell myocarditis, also known as idiopathic myocarditis, a rare, frequently fulminant and fatal disorder of unknown etiology, is isolated to the heart and lacks systemic involvement. This disorder is most commonly diagnosed at autopsy. We present two cases in which sudden death resulted from a giant cell inflammatory process affecting the myocardium. Both individuals lacked antemortem diagnoses and collapsed at their respective places of employment. These cases compare and contrast the clinical and pathologic issues involved in the differential diagnoses of the subgroup of sudden cardiac deaths resulting from giant cell inflammatory processes that affect the myocardium, as well as the value of histologic examination and immunohistochemical studies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".