Feline procedural sedation and analgesia: When, why and how
Bibliographic record
Abstract
PRACTICAL RELEVANCE: Procedural sedation and analgesia (PSA) describes the process of depressing a patient's conscious state to perform unpleasant, minimally invasive procedures, and is part of the daily routine in feline medicine. Maintaining cardiopulmonary stability is critical while peforming PSA. CLINICAL CHALLENGES: Decision-making with respect to drug choice and dosage regimen, taking into consideration the cat's health status, behavior, any concomitant diseases and the need for analgesia, represents an everyday challenge in feline practice. While PSA is commonly perceived to be an uneventful procedure, complications may arise, especially when cats that were meant to be sedated are actually anesthetized. AIMS: This clinical article reviews key aspects of PSA in cats while exploring the literature and discussing complications and risk factors. Recommendations are given for patient assessment and preparation, clinical monitoring and fasting protocols, and there is discussion of how PSA protocols may change blood results and diagnostic tests. An overview of, and rationale for, building a PSA protocol, and the advantages and disadvantages of different classes of sedatives and anesthetics, is presented in a clinical context. Finally, injectable drug protocols are reported, supported by an evidence-based approach and clinical experience.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".