Use of tiletamine-zolazepam versus xylazine-ketamine as a sedation and anesthetic combination for ovariohysterectomy procedure in registered feral feline colonies.
Bibliographic record
Abstract
In female cats, spaying eliminates the risk of developing pathologies related to the \novaries and uterus, such as pyometra, uterine tumors and metritis. It also reduces the \nprobability of having hormone-dependent pathologies, such as breast tumors and \npseudogestation. Sterilization by TNR program (Trap-Neuter-Return) allows us to \ncontrol the overpopulation of colony cats, which causes, apart from other negative \nconsequences, a threat to the local fauna. \nThe aim of this study was to compare the use of Zoletil with Ketamine and xylazine \ncombination versus routine ketamine and xylazine shelter protocol in order to increase \nthe sedation level and improve the management of ovariohysterectomies in feral cats. \nThis study was carried out by using a total of 30 feral cats divided into two groups: \nGroup G1 routine combination of ketamine and xylazine (KX) used in the shelter and \ngroup G2 based on a combination of ketamine, xylazine, tiletamine and zolazepam. \nIn both groups, heart rate, oxygen saturation, temperature, systolic, diastolic, and \nmean arterial blood pressures of all cats were monitored. Post-surgical pain was also \nevaluated using two different scales: Feline Glasgow Scale and Feline Grimace Scale \nof University of Montreal. \nThe group G1 showed better results of sedation and less isoflurane requirement in \ncomparing to group G2 where isoflurane was needed in approximately 50% of the \nanimals. Nevertheless, group G2 showed shorter recovery times. \nWe conclude that the shelter routine protocol showed by the group G1 developed a \nbetter sedation quality for the ovariohysterectomy procedures in feral cats. \nFinally, further studies are needed in order to improve the combination used in the \ngroup G2 by increasing Zoletil doses and a larger size of the sample should be taken \ninto consideration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".