Abstract 342: Developing an In Vivo Model of Ventricular Refibrillation
Bibliographic record
Abstract
Background Ventricular refibrillation, defined as re-emergence of VF following successful defibrillation, is as frequent as 79% after out of hospital cardiac arrest, with at least 50% of patients experiencing more than 1 episode of refibrillation. Re-fibrillations are harder to defibrillate and are inversely associated with survival. The mechanism of refibrillation is not known. In order to test hypotheses on preventing or treating refibrillation, a reliable in-vivo refibrillation model is necessary. Pigs have been used as a reliable model to study the efficacy of CPR. Here we present a swine model of ventricular refibrillation following VF. Methods & Results Twenty-four Yorkshire pigs were anesthetized. Three Millar catheters were used to measure pressure from abdominal Aorta, RA and LV. An EP catheter was introduced in the RV to induce VF. VF was induced by burst pacing and left untreated for 4 minutes. Then chest compressions were delivered using a pneumatic device at a constant rate of 120/min and manual ventilation was delivered at 6 breaths/min. All animals were defibrillated after 3 min of CPR at 150J, and increasing energy in case of failure. After successful defibrillation, they were observed for a period of 30 min for any occurrence of refibrillation. Refibrillations were treated with defibrillation. The initial VF could not be defibrillated in 3 (12%). Refibrillation occurred in 13 (62%). The mean time to onset of refibrillation was 629 sec after successful defibrillation ranging from 8 to 1600 sec. Mean number of re-fibrillations was 1.14±1.15 (max: 4) with 33.33% (n=7) experiencing more than one episode of refibrillation. Forty-six percent of refibrillations occurred within first 5 min after defibrillation. Overall Survival was 37.5% (n=9). Survival was 38% in re-fibrillation group vs. 44.4% in non-refibrillation group (p=nsS). With regards to initiation, 60% of episodes were preceded by 1 PVC and 20% were preceded by 2 PVCs or more. Conclusion We have developed a swine model of ventricular re-fibrillation that resembles reported human data in terms of incidence of re-fibrillation and initiation following VF arrest. This model will serve as a test bed for different pharmacologic and interventional strategies focused on modulating refibrillation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".