Utility of microvolt T-wave alternans to predict sudden cardiac death in patients with cardiomyopathy
Bibliographic record
Abstract
PURPOSE OF REVIEW: Sudden cardiac death remains a major cause of mortality among patients with cardiomyopathy and implantable cardioverter-defibrillator therapy has been shown to improve survival in these patients. Effective use of prophylactic implantable cardioverter-defibrillator therapy requires accurate risk stratification beyond assessment of ejection fraction, however. Repolarization alternans is a harbinger of ventricular arrhythmias and its measurement from body-surface recordings, also known as microvolt T-wave alternans, is emerging as an effective prognostic tool in these patients based on recent clinical trials. RECENT FINDINGS: We review the pathogenesis and determinants of repolarization alternans. The current techniques for measuring T-wave alternans from the body surface are compared, including the spectral and modified moving average methods. Recent clinical trials evaluating the prognostic utility of T-wave alternans in patients with ischemic and nonischemic cardiomyopathy and no prior arrhythmic events are summarized. The findings of these studies are discussed in the context of implantable cardioverter-defibrillator prophylaxis. Body-surface T-wave alternans is an evolving technique and its limitations are presented along with approaches to improve its predictive accuracy. SUMMARY: Risk stratification with T-wave alternans has the potential to guide prophylactic implantable cardioverter-defibrillator therapy in a growing population of patients with cardiomyopathy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".