Combined inhibition of key potassium currents has different effects on cardiac repolarization reserve and arrhythmia susceptibility in dogs and rabbits
Bibliographic record
Abstract
A reliable assessment of the pro-arrhythmic potential for drugs in the development phase remains elusive. Rabbits and dogs are commonly used to create models of pro-arrhythmia, but the differences between them with respect to repolarizing potassium currents are poorly understood. We investigated the incidence of drug-induced torsades de pointes (TdP) and measured conventional ECG parameters and the short-term variability of the QT interval (STVQT) following combined pharmacological inhibition of IK1+IKs and IK1+IKr in conscious dogs and anesthetized rabbits. A high incidence of TdP was observed following the combined inhibition of IK1+IKs in dogs (67% vs. 14% in rabbits). Rabbits exhibited higher TdP incidence after inhibition of IK1+IKr (72% vs. 14% in dogs). Increased TdP incidence was associated with significantly larger STVQT in both models. The relatively different roles of IK1 and IKs in dog and rabbit repolarization reserve should be taken into account when extrapolating the results from animal models of pro-arrhythmia to humans. A stronger repolarization reserve in dogs (likely due to stronger IK1 and IKs), and the more human-like susceptibility to arrhythmia of rabbits argues for the preferred use of rabbits in the evaluation of adverse pro-arrhythmic effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".