High Density Intramural Mapping of Post-Infarct Premature Ventricular Contractions.
Bibliographic record
Abstract
Background: Spontaneous ventricular premature contractions (PVCs) in the post infarct milieu is assumed to be due to automaticity. However, the mechanism has not been studied with appropriate mapping tools. Objective: To study the mechanism of spontaneous PVCs with high density intramural mapping in a canine model, to test the hypothesis that post-infarct PVCs are due to re-entry rather than automaticity. Methods: In 15 anesthetized dogs, using 768 intramural unipolar electrograms, simultaneous recordings were made. After 30 mins of stabilization, recordings were made during the first 10 minutes of ischemia, and activation maps were constructed of individual beats. Acute ischemia was produced by clamping the left anterior descending coronary artery proximal to the first diagonal branch. The analysis was limited to the activation pattern of spontaneous ventricular beats. Results: In all experiments ST-T alternans occurred. In 8 of 15 dogs spontaneous ventricular beats occurred. In all 8 of these experiment earliest, ectopic activity occurred in the endocardium, well within the ischemic zone. From there, activity spread rapidly along the subendocardium, with endo-to epicardial spread along the non ischemic myocardium. Epicardial breakthrough always occurred at the border of the ischemic myocardium. In 3 dogs, delayed potentials were observed, which were earliest at the ischemic epicardium and extended transmurally with increasing delay towards the endocardium, where they culminated in a premature beat. Conclusion: Graded responses that occur with each sinus beat intramurally, when able to propagate from epicardium to endocardium is the mechanism by which PVCs are generated in post-infarct myocardium.
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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 | 0.000 |
| 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".