Terikalant and Barium Decrease the Area of Vulnerability to Ventricular Fibrillation Induction by T-Wave Shocks
Bibliographic record
Abstract
The area of vulnerability (AOV) to ventricular fibrillation (VF) induction by high-voltage shocks has been proposed as a measure of vulnerability to VF. Biphasic shocks spanning the T wave and ranging between 50 V and the upper limit of vulnerability (ULV) to VF were delivered before and after terikalant (1 mg/kg) and barium (1.1 mg/kg load followed by 0.05-0.10 mg/kg/min maintenance) or vehicle in dogs. The AOV decreased by 34% and 28% (p < 0.01) after terikalant and barium (n = 8 dogs each), respectively. Mean ULV, defibrillation threshold (DFT), and ventricular vulnerability period (VVP) decreased by 16%, 23%, and 31% (p < 0.01), respectively, after terikalant, and by 25%, 17% (p < 0.01), and 13% (p = 0.08), respectively, after barium. Vehicle (n = 14) did not significantly alter any of these variables. The ULV was correlated with the DFT before and after terikalant (r = 0.78, p < 0.01) and barium (r = 0.83, p < 0.01). Potassium channel blockers of the current reduce the ability to induce VF; this effect may be related to the anti-fibrillatory action of class III anti-arrhythmic drugs and their ability to decrease DFT.
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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 | 0.001 |
| 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 | 0.001 |
| 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".