Ischemic Brugada phenocopy during ablation of ventricular tachycardia
Bibliographic record
Abstract
We examined the report by Hori et al. with specific interest in their description of a Brugada ECG (electrocardiogram) pattern observed during ablation of ventricular tachycardia (VT) [1]. Their case provides an important contribution to an expanding database of ischemic Brugada phenocopies (BrP) [2], [3]. BrP are characterized by ECG patterns identical to those of Brugada syndrome (BrS), but are elicited under various circumstances [2], [3]. They are classified according to six etiological categories: (i) metabolic conditions; (ii) mechanical compression; (iii) myocardial ischemia & pulmonary embolism; (iv) myocardial & pericardial disease; (v) ECG modulations; and (vi) miscellaneous. See www.brugadaphenocopy.com. The authors [1] presented the case of a 63-year-old man undergoing catheter ablation of ischemic VT. The patient developed a Type-1 Brugada ECG pattern during the procedure, resolving upon observation within two minutes. During this time, the mapping catheter appeared to have been pushed against the left ventricular wall. The patient was subjected to provocative testing with pilsicainide, the results of which were negative. We believe that this patient developed BrP in the context of ischemia, resulting from direct compression of a coronary artery or vasospasm. Ischemic causes of BrP are not uncommon; however, this is the first confirmed case to observe a BrP during ablation of VT [4], [5]. This case has been included in our database as a Type-1A BrP, under the category of myocardial and pericardial disease. All authors declare no conflict of interest related to this study. None to disclose.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".