Comparison of the effect of three intramuscular sedation protocols on packed cell volume and total protein in cats
Bibliographic record
Abstract
Objectives The aim of this study was to evaluate the change in packed cell volume (PCV) and total protein following intramuscular preanesthetic sedation with one of three drug combinations in cats. Methods Thirty client-owned cats were enrolled in this prospective, randomized, blinded, clinical study. A venous blood sample was obtained prior to administration of any sedation and PCV, total protein, electrolytes (Na + , K + , Cl – , iCa 2+ ), glucose and lactate were measured. Cats were randomly assigned to receive one of three intramuscular sedation protocols (n = 10 cats/protocol): methadone 0.2 mg/kg + acepromazine 0.02 mg/kg (MA), methadone 0.2 mg/kg + dexmedetomidine 5 µg/kg (MD) or methadone 0.2 mg/kg + midazolam 0.2 mg/kg + alfaxalone 2 mg/kg (MMA). Twenty-five minutes later, cats were assessed for level of sedation followed by another venous blood sampling to evaluate the same variables as above. Results There were no significant differences in demographics (age, weight, sex) between groups. Level of sedation was significantly higher in MMA cats. Within groups, after premedication, PCV and hemoglobin significantly decreased in all groups, total protein significantly decreased in the MA and MMA groups and glucose significantly increased in the MD group. For electrolytes, statistical changes were not clinically relevant; Cl – mean difference was significantly different between MA and MD; in the MD group Na + and Cl – significantly decreased and in the MMA group Cl – significantly increased. Conclusions and relevance All three sedation protocols caused significant decreases in PCV and hemoglobin in healthy cats.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".