Variants of Brugada Syndrome and Early Repolarization Syndrome: An Expanded Concept of J‐Wave Syndrome
Bibliographic record
Abstract
BACKGROUND: The role of J-waves in the pathogenesis of ventricular fibrillation (VF) occurring in structurally normal hearts is important. METHODS: We evaluated 127 patients who received an implantable cardioverter-defibrillator (ICD) for Brugada syndrome (BS, n = 53), early repolarization syndrome (ERS, n = 24), and patients with unknown or deferred diagnosis (n = 50). Electrocardiography (ECG), clinical characteristics, and ICD data were analyzed. RESULTS: J-waves were found in 27/50 patients with VF of unknown/deferred diagnosis. The J-waves were reminiscent of those seen in BS or ERS, and this subgroup of patients was termed variants of ERS and BS (VEB). In 12 VEB patients, the J/ST/T-wave morphology was coved, although amplitudes were <0.2 mV. In 15 patients, noncoved-type J/ST/T-waves were present in the right precordial leads. In the remaining 23 patients, no J-waves were identified. VEB patients exhibited clinical characteristics similar to those of BS and ERS patients. Phenotypic transition and overlap were observed among patients with BS, ERS, and VEB. Twelve patients with BS had background inferolateral ER, while five ERS patients showed prominent right precordial J-waves. Patients with this transient phenotype overlap showed a significantly lower shock-free survival than the rest of the study patients. CONCLUSIONS: VEB patients demonstrate ECG phenotype similar to but distinct from those of BS and ERS. The spectral nature of J-wave morphology/distribution and phenotypic transition/overlap suggest a common pathophysiologic background in patients with VEB, BS, and ERS. Prognostic implication of these ECG variations requires further investigation.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".