Microvolt QRS Alternans Without Microvolt T‐Wave Alternans in Human Cardiomyopathy: A Novel Risk Marker of Late Ventricular Arrhythmias
Bibliographic record
Abstract
Background Action potential alternans can induce ventricular tachyarrhythmias and manifest on the surface ECG as T‐wave alternans (TWA) and QRS alternans (QRSA). We sought to evaluate microvolt QRSA in cardiomyopathy patients in relation to TWA and ventricular tachyarrhythmia outcomes. Methods and Results Prospectively enrolled cardiomyopathy patients (n=100) with prophylactic defibrillators had 12‐lead ECGs recorded during ventricular pacing from 100 to 120 beats/min. QRSA and TWA were quantified in moving 128‐beat segments using the spectral method. Segments were categorized as QRSA positive (QRSA+) and/or TWA positive (TWA+) based on ≥2 precordial leads having alternans magnitude >0 and signal:noise >3. Patients were similarly categorized based on having ≥3 consecutive segments with alternans. TWA+ and QRSA+ occurred together in 31% of patients and alone in 18% and 14% of patients, respectively. Although TWA magnitude (1.4±0.4 versus 4.7±1.0 µV, P <0.01) and proportion of TWA+ studies (16% versus 46%, P <0.01) increased with rate, QRSA did not change. QRS duration was longer in QRSA+ than QRSA‐negative patients (138±23 versus 113±26 ms, P <0.01). At 3.5 years follow‐up, appropriate defibrillator therapy or sustained ventricular tachyarrhythmia was greater in QRSA+ than QRSA‐negative patients (30% versus 8%, P =0.02) but similar in TWA+ and TWA‐negative patients. Among QRSA+ patients, the event rate was greater in those without TWA (62% versus 21%, P =0.02). Multivariable Cox analysis revealed QRSA+ (hazard ratio [HR], 4.6; 95% CI, 1.5–14; P =0.009) and QRS duration >120 ms (HR, 4.1; 95% CI, 1.3–12; P =0.014) to predict events. Conclusions Microvolt QRSA is novel phenomenon in cardiomyopathy patients that can exist without TWA and is associated with QRS prolongation. QRSA increases the risk of ventricular tachyarrhythmia 4‐fold, which merits further study as a risk stratifier.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".