Effect of global ischemia and reperfusion during ventricular fibrillation in myopathic human hearts
Bibliographic record
Abstract
The effect of lack of global coronary perfusion on myocardial activation rate, wavebreak, and its temporal progression during human ventricular fibrillation (VF) is not known. We tested the hypothesis that global myocardial ischemia decreases activation rate and spatiotemporal organization during VF in myopathic human hearts, while increasing wavebreak, and that a short duration of reperfusion can restore these spatiotemporal changes to baseline levels. The electrograms were acquired during VF in a human Langendorff model using global mapping consisting of two 112-electrode arrays placed on the epicardium and endocardium simultaneously. We found that global myocardial ischemia results in slowing of the global activation rate (combined endo and epi), from 4.89+/-0.04 Hz. to 3.60+/-0.04 Hz. during the 200 s of global ischemia (no coronary flow) (P<0.01) in eight myopathic hearts. Two minutes of reperfusion contributed to reversal of the slowing with activation rate value increasing close to VF onset (4.72+/-0.04 Hz). In addition, during the period of ischemia, an activation rate gradient between the endocardium (3.76+/-0.06 Hz) and epicardium (3.45+/-0.06 Hz) was observed (P<0.01). There was a concomitant difference in wavebreak index (that provides a normalized parameterization of phase singularities) between the epicardium (11.29+/-2.7) and endocardium (3.25+/-2.7) during the 200 s of ischemia (P=0.02). The activation rate, gradient, and wavebreak changes were reversed by short duration (2 min) of reperfusion. Global myocardial ischemia of 3 min leads to complex spatiotemporal changes during VF in myopathic human hearts; these changes can be reversed by a short duration of reperfusion.
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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) | 0.001 | 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".