PSEN1 as an Adjunct for Diagnosis of Human Myocarditis
Bibliographic record
Abstract
Background Myocarditis, defined as inflammation of the heart muscle, is a spectrum of conditions causing considerable morbidity and mortality, resulting from various etiologies, including infection, autoimmunity, or chemical exposure. As such, diagnosing myocarditis can be quite difficult and determining etiology even more so. The gold standard of diagnosis is endomyocardial biopsy showing inflammation with or without myocyte damage in the absence of an ischemic event. However, due to the spatial and structural heterogeneity of myocarditis, diagnostic sensitivity is estimated as low as 30%. To improve upon this, we examined several markers implicated in the pathogenesis of viral myocarditis in animal models as possible diagnostic adjuncts. PSEN1 (the gene encoding presenilin 1) emerged as a promising candidate. This study aims to formally evaluate PSEN1 as a diagnostic adjunct. Design Fifty (50) cases were examined for PSEN1 staining (20 lymphocytic active or healing myocarditis, 4 eosinophilic myocarditis, 4 idiopathic dilated cardiomyopathy, 4 hypertrophic cardiomyopathy, 4 sarcoidosis, 4 coronary artery disease, 3 transplant rejection, 1 Lyme disease, 1 toxoplasmosis, and 5 normal controls). All cases were obtained from the Cardiovascular Tissue Registry in the Centre for Heart Lung Innovation, under approved human ethics protocols. Levels of PSEN1 were evaluated using colour segmentation and scoring conducted by three individual subspecialty cardiac pathologists blinded to diagnosis. Statistical analysis was performed using Mann Whitney U test and receiver operating characteristics (ROC) curves. Results Colour segmentation and pathologist scoring correlated with each other well (Spearman's rho correlation coefficient 0.71 or better in all comparisons). PSEN1 is expressed at significantly higher levels in lymphocytic myocarditis cases as compared to normals and to all other pathologies (all pvalues less than 0.005). The ROC curves for diagnosing myocarditis as compared to other pathologies using PSEN1 staining have areas under the curve (AUCs, or cstatistics) ranging from 0.78 to 0.88. Of note, several “false positive” cases were those with idiopathic dilated cardiomyopathy, such cardiomyopathy reflects the end stage of a prior lymphocytic myocarditis. Case subset analyses and validation on biopsy specimens are under way. Conclusion PSEN1 immunohistochemistry appears to be a helpful diagnostic adjunct for identifying myocarditis, even in minimally inflamed specimens and in tissue obtained long after the initial insult. Support or Funding Information Funding and support from St. Paul's Foundation
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".