New electrocardiographic criteria to differentiate the Type-2 Brugada pattern from electrocardiogram of healthy athletes with r'-wave in leads V1/V2
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Bibliographic record
Abstract
AIMS: Diagnosis of Type-2 Brugada pattern remains challenging and it could be confused with other electrocardiogram (ECG) patterns presenting an r'-wave in leads V1-V2 like in healthy athletes. This could impact their ability to perform competitive sports. The aim of the study was to evaluate, as a proof of concept, the new ECG criteria to differentiate the Type-2 Brugada pattern from the ECG pattern of healthy athletes depicting an r'-wave in leads V1-V2. METHODS AND RESULTS: Surface ECGs from 50 patients with Brugada syndrome and type-2 Brugada pattern and 58 healthy athletes with an r'-wave in leads V1-V2 were analysed. Different criteria based on the characteristics of the triangle formed by the ascendant and descendant arms of the r'-wave in leads V1-V2 were compared. The duration of the base of the triangle at 0.5 mV (5 mm) from high take-off ≥160 ms (4 mm) has a specificity (SP) of 95.6%, sensitivity (SE) 85%, positive predictive value (PPV) 94.4%, and negative predictive value (NPV) 87.9%. The duration of the base of the triangle at the isoelectric line ≥60 ms (1.5 mm) in leads V1-V2 has an SP of 78%, SE 94.8%, PPV 79.3%, and NPV 93.5%. The ratio of the base at isoelectric line/height from the baseline to peak of r'-wave in leads V1-V2 has an SP of 92.1%, SE 82%, PPV 90.1%, and NPV 83.3%. CONCLUSIONS: The three new ECG criteria were accurate to distinguish the Type-2 Brugada pattern from the ECG pattern with an r'-wave in healthy athletes. The duration of the base of the triangle at 0.5 mV from the high take-off is the easiest to measure and may be used in clinical practice.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it