A Newly Characterized <i>SCN5A</i> Mutation Underlying Brugada Syndrome Unmasked by Hyperthermia
Bibliographic record
Abstract
Febrile illness has been rarely reported to modulate ST segment elevation in right precordial leads on ECG or even precipitate ventricular fibrillation in patients with Brugada syndrome. We report the case of a patient whose Brugada ECG pattern was unmasked by hyperthermia secondary to acute cholangitis. Serial ECGs showed progressive attenuation of ST segment elevation as body temperature gradually returned to normal. Structural heart disease was ruled out. Intravenous flecainide injection reproduced a less remarkable ST segment elevation. Genetic screening demonstrated a single amino acid substitution (H681P) in the SCN5A gene, thus confirming the diagnosis of Brugada syndrome. In vitro expression of this newly characterized genetic defect revealed novel biophysical abnormalities consisting of a shift in both steady-state activation and inactivation, resulting in a 60% reduction of sodium window current. Thus, SCN5A-H681P mutation induces a significant loss of transmembrane current and is clinically associated with a pathologic phenotype that is elicited by hyperthermia. Overall the observed clinical features are in agreement with previous observations and strongly suggest that fever may be an environmental modifier among Brugada syndrome patients with a detrimental (and possibly arrhythmogenic) effect on cardiac repolarization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".