Modulated dispersion of activation and repolarization by premature beats in patients with cardiomyopathy at risk of sudden death
Bibliographic record
Abstract
Premature beats can trigger ventricular arrhythmias in heart disease, but the mechanisms are not well defined. We studied the effect of premature beats on activation and repolarization dispersion in seven patients with cardiomyopathy (57 ± 10 yr, left ventricular ejection fraction 31 ± 7%). Activation time (AT), activation-recovery interval (ARI), and total repolarization time (TRT) were measured from 26 unipolar electrograms during right ventricle (RV) endocardial (early) to left ventricle epicardial (late) activation in response to RV apical extrastimulation (S1S2). Early TRT dispersion increased significantly with shorter S1S2 (1.0 ± 0.2 to 2.3 ± 0.4 ms/mm, P < 0.0001), with minimal change in late TRT dispersion (0.8 ± 0.1 to 1.0 ± 0.3 ms, P = 0.02). This was associated with an increase in early AT dispersion (1.0 ± 0.1 to 1.5 ± 0.2 ms/mm, P = 0.05) but no change in late AT dispersion (0.6 ± 0.1 to 0.7 ± 0.2 ms/mm, P = 0.4). Early and late ARI dispersion did not change with shorter S1S2. AT restitution slopes were similar between early and late sites, as was slope heterogeneity. ARI restitution slope was greater in early vs. late sites (1.3 ± 0.6 vs. 0.8 ± 0.6, P = 0.03), but slope heterogeneity was similar. With shorter S1S2, AT-ARI slopes became less negative (flattened) at both early (-0.4 ± 0.1 to +0.04 ± 0.2) and late (-1.5 ± 0.2 to +0.3 ± 0.2) sites, implying less activation-repolarization coupling. There was no difference in AT-ARI slopes between early and late sites at short S1S2. In conclusion, high-risk patients with cardiomyopathy have greater TRT dispersion at tightly coupled S1S2 due to greater AT dispersion and activation-repolarization uncoupling. Modulated dispersion is more pronounced at early vs. late activated sites, which may predispose to reentrant ventricular arrhythmias.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".