Cardiac electrophysiological effects of ibuprofen in dog and rabbit ventricular preparations: possible implication to enhanced proarrhythmic risk
Bibliographic record
Abstract
Ibuprofen is a widely used nonsteroidal anti-inflammatory drug, which has recently been associated with increased cardiovascular risk, but its electrophysiological effects have not yet been properly studied in isolated cardiac preparations. We studied the effects of ibuprofen on action potential characteristics and several transmembrane ionic currents using the conventional microelectrode technique and the whole-cell configuration of the patch-clamp technique on cardiac preparations and enzymatically isolated ventricular myocytes. In dog (200 µM; n = 6) and rabbit (100 µM; n = 7) papillary muscles, ibuprofen moderately but significantly prolonged repolarization at 1 Hz stimulation frequency. In dog Purkinje fibers, repolarization was abbreviated and maximal rate of depolarization was depressed in a frequency-dependent manner. Levofloxacin (40 µM) alone did not alter repolarization, but augmented the ibuprofen-evoked repolarization lengthening in rabbit preparations (n = 7). In dog myocytes, ibuprofen (250 µM) did not significantly influence IK1, but decreased the amplitude of Ito and IKr potassium currents by 28.2% (60 mV) and 15.2% (20 mV), respectively. Ibuprofen also depressed INaL and ICa currents by 19.9% and 16.4%, respectively. We conclude that ibuprofen seems to be free from effects on action potential parameters at lower concentrations. However, at higher concentrations it may alter repolarization reserve, contributing to the observed proarrhythmic risk in patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".