Effects of injectable anesthetic combinations on left ventricular function and cardiac morphology in Sprague-Dawley rats.
Bibliographic record
Abstract
Novel anesthetic agents or combinations may provide superior general anesthesia for echocardiography in rodents with the potential for reduced adverse effects. This study sought to characterize the effects of 3 injectable anesthetics on left ventricular (LV) systolic function and cardiac morphology in healthy male and female rats. Rats underwent echocardiographic assessment after general anesthesia via pentobarbital or combinations of ketamine and medetomidine (KME) and ketamine and midazolam (KMI) according to a crossover Latin-square design. Blood samples for serum estradiol measurements were obtained from all females after echocardiography with each anesthetic. Rats given KMI showed superior LV systolic function with the highest values for fractional shortening (FS), ejection fraction (EF) and stroke volume, whereas heart rate was greatest with pentobarbital, followed by KMI and then KME. KME produced the greatest effects on cardiac morphology, most notably during systole, including reduced septal and posterior wall thickness and increased LV chamber dimensions and volumes. In addition, KME had the greatest cardiac-depressing effects on LV systolic function, including reduced FS, EF, and heart rate values. Compared with male rats, female rats had superior LV function with greater EF and FS values, whereas male rats showed higher heart rate. Significant negative correlations were noted between serum estradiol levels and FS and EF values in female rats receiving KME. We conclude that the combination of KMI may be a superior anesthetic for use in male and female rats undergoing echocardiography.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".