SCN5A mutation type and topology are associated with the risk of ventricular arrhythmia by sodium channel blockers
Bibliographic record
Abstract
Background Ventricular fibrillation in patients with Brugada syndrome (BrS) is often initiated by premature ventricular contractions (PVCs). Presence of SCN5A mutation increases the risk of PVCs upon exposure to sodium channel blockers (SCB) in patients with baseline type-1 ECG. In patients without baseline type-1 ECG, however, the effect of SCN5A mutation on the risk of SCB-induced arrhythmia is unknown. We aimed to establish whether presence/absence, type, and topology of SCN5A mutation correlates with PVC occurrence during ajmaline infusion. Methods and results We investigated 416 patients without baseline type-1 ECG who underwent ajmaline testing and SCN5A mutation analysis. A SCN5A mutation was identified in 88 patients ( S + ). Ajmaline-induced PVCs occurred more often in patients with non-missense mutations ( S non-missense ) or missense mutations in transmembrane or pore regions of SCN5A -encoded channel protein ( S missense-TP ) than patients with missense mutations in intra-/extracellular channel regions ( S missense-IE ) and patients without SCN5A mutation ( S − ) (29%, 24%, 9%, and 3%, respectively; P <0.001). The proportion of patients with ajmaline-induced BrS was similar in different mutation groups but lower in S − (71% S non-missense , 63% S missense-TP , 70% S missense-IE , and 34% S − ; P <0.001). Logistic regression indicated S non-missense and S missense-TP as predictors of ajmaline-induced PVCs. Conclusions SCN5A mutation is associated with an increased risk of drug-induced ventricular arrhythmia in patients without baseline type-1 ECG. In particular, S non-missense and S missense-TP are at high risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".