An approach to endomyocardial biopsy interpretation
Bibliographic record
Abstract
The endomyocardial biopsy (EMB) remains the gold standard mode of investigation for diagnosing many primary and secondary cardiac conditions. Through a percutaneous and transvenous route, tissue fragments are generally procured from the right ventricular septum, with very few complications. Widespread use of EMB followed the development of heart transplantation as a means to follow allograft rejection. It has since been useful in helping to diagnose conditions affecting the heart, including cardiomyopathies, myocarditis, infiltrative lesions, arrhythmias, and drug toxicities. The procedure has also been used as a research tool to investigate the natural history of disease and the cardiotoxicity of new medications. This review presents an approach to the evaluation of the EMB, which is particularly directed towards those who may be asked to interpret such biopsies, but are not dedicated cardiovascular pathologists. Through a systematic evaluation of the endocardium, myocardium, interstitium, and intramural vessels, in the context of a complete clinical history, enough information can be deduced to diagnose or exclude specific conditions of clinical value.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".