Predicting cardiac electrical response to sodium-channel blockade and Brugada syndrome using polygenic risk scores
Bibliographic record
Abstract
AIMS: Sodium-channel blockers (SCBs) are associated with arrhythmia, but variability of cardiac electrical response remains unexplained. We sought to identify predictors of ajmaline-induced PR and QRS changes and Type I Brugada syndrome (BrS) electrocardiogram (ECG). METHODS AND RESULTS: In 1368 patients that underwent ajmaline infusion for suspected BrS, we performed measurements of 26 721 ECGs, dose-response mixed modelling and genotyping. We calculated polygenic risk scores (PRS) for PR interval (PRSPR), QRS duration (PRSQRS), and Brugada syndrome (PRSBrS) derived from published genome-wide association studies and used regression analysis to identify predictors of ajmaline dose related PR change (slope) and QRS slope. We derived and validated using bootstrapping a predictive model for ajmaline-induced Type I BrS ECG. Higher PRSPR, baseline PR, and female sex are associated with more pronounced PR slope, while PRSQRS and age are positively associated with QRS slope (P < 0.01 for all). PRSBrS, baseline QRS duration, presence of Type II or III BrS ECG at baseline, and family history of BrS are independently associated with the occurrence of a Type I BrS ECG, with good predictive accuracy (optimism-corrected C-statistic 0.74). CONCLUSION: We show for the first time that genetic factors underlie the variability of cardiac electrical response to SCB. PRSBrS, family history, and a baseline ECG can predict the development of a diagnostic drug-induced Type I BrS ECG with clinically relevant accuracy. These findings could lead to the use of PRS in the diagnosis of BrS and, if confirmed in population studies, to identify patients at risk for toxicity when given SCB.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".