O3 | Post‐anesthetic pain scores in surgical and non‐surgical equine patients: An observational study
Bibliographic record
Abstract
Introduction: Objective pain scales are an important tool in clinical practice guiding pain management strategies. The Composite Pain Scale (CPS) and Equine Utrecht University Scale for Facial Assessment of Pain (EQUUS-FAP) have been validated for pain assessment in horses after orthopedic surgery and trauma. We hypothesized that residual effects of anesthetic agents would affect these pain scores. Methods: A prospective observational study was performed using 50 adult horses presenting for elective anesthesia (n = 26 for surgical; n = 24 for non-surgical). CPS and EQUUS-FAP were assessed by direct observation of subjects by two independent observers. Each horse was scored at 6 different time points: prior to anesthesia (T0) and then hourly following recovery to standing (T1–T5). Data were analyzed utilizing a generalized mixed effects model, with α = 0.05. Results: For both overall CPS and EQUUS-FAP scores, there was no significant effect of reason for anesthesia (surgical vs. non-surgical). There was a significant effect of timepoint for both CPS and EQUUS-FAP (p < .001, for both) with horses scoring significantly higher than baseline in the hours immediately following anesthetic recovery (CPS: p < .001 for T1-T4, p = .025 for T5; EQUUS-FAP: p < .001 for T1 and T2, p = .002 for T3, p = .646 for T4, p = .994 for T5). Conclusions: These results suggest that the CPS and EQUUS-FAP may not be reliable tools for assessing pain in horses in the hours immediately following anesthetic recovery and may result in unnecessary administration of rescue analgesia.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".