Hidden IgG4-Related Coronary Disease
Bibliographic record
Abstract
OBJECTIVES: We present a full autopsy with a focused radiology and pathologic review of the coronary arteries. We hope that the results described in this article will help create better diagnostic measures and prevent future coronary artery vasculitis misdiagnosis. METHODS: A full autopsy was performed on the body of Dr Myung Choong Yoon, with full consent from the family, within the department of pathology and laboratory medicine at Vancouver General Hospital. Tissue samples from the heart, brain, lungs, and spinal cord were submitted to specialist pathologists for histologic processing. RESULTS: Cardiac gated computed tomography coronary angiography suggested periarteritis. Coexistent calcified coronary atherosclerosis with linear calcifications was present along the luminal wall, along with coronary artery ectasia. Histologic assessment confirmed features of dense adventitial fibrosis around the coronary arteries, with an exuberant lymphoplasmacytic infiltrate and numerous plasma cells consistent with IgG4-related disease. The media of the coronary arteries was markedly attenuated or completely absent, which likely contributed to the coronary arterial ectasia noted microscopically. These findings confirmed IgG4-related coronary arteritis. CONCLUSIONS: Coronary periarteritis is an uncommon manifestation of IgG4-related disease established radiographically and later by autopsy.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".