Long QT Syndrome Complicating Atrioventricular Block
Bibliographic record
Abstract
BACKGROUND: The magnitude of QT prolongation in response to bradycardia, rather than the bradycardia per se, determines the risk for torsade de pointes during atrioventricular block (AVB). However, we do not know why some patients develop more QT prolongation than others, despite similar bradycardia. We hypothesized that in patients who develop significant QRS vector changes during AVB, the effects of cardiac memory lead to excessive QT prolongation. METHODS AND RESULTS: We studied 91 patients who presented with AVB and who also had an ECG predating the bradyarrhythmia for comparison. We correlated changes in QRS morphology and axis taking place during AVB with the bradycardia-induced QT prolongation. Patients with and without QRS morphology changes at the time of AVB were of similar age and sex. Moreover, despite similar R-R interval during AVB, cases with a QRS morphology change had significantly longer QT (648 ± 84 versus 561 ± 84; P<0.001) than those without. Patients who developed a change in QRS morphology at the time of AVB had a 7-fold higher risk of developing long QT. This risk nearly doubled when the change in QRS morphology was accompanied by a change in QRS axis. CONCLUSIONS: Cardiac memory resulting from a change in QRS morphology during AVB is independently associated with QT prolongation and may be arrhythmogenic during AVB.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| 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".