Clinical applicability of the Feline Grimace Scale: real-time versus image scoring and the influence of sedation and surgery
Bibliographic record
Abstract
Background The Feline Grimace Scale (FGS) is a facial expression-based scoring system for acute pain assessment in cats with reported validity using image assessment. The aims of this study were to investigate the clinical applicability of the FGS in real-time when compared with image assessment, and to evaluate the influence of sedation and surgery on FGS scores in cats. Methods Sixty-five female cats (age: 1.37 ± 0.9 years and body weight: 2.85 ± 0.76 kg) were included in a prospective, randomized, clinical trial. Cats were sedated with intramuscular acepromazine and buprenorphine. Following induction with propofol, anesthesia was maintained with isoflurane and cats underwent ovariohysterectomy (OVH). Pain was evaluated at baseline, 15 min after sedation, and at 0.5, 1, 2, 3, 4, 6, 8, 12 and 24 h after extubation using the FGS in real-time (FGS-RT). Cats were video-recorded simultaneously at baseline, 15 min after sedation, and at 2, 6, 12, and 24 h after extubation for subsequent image assessment (FGS-IMG), which was performed six months later by the same observer. The agreement between FGS-RT and FGS-IMG scores was calculated using the Bland & Altman method for repeated measures. The effects of sedation (baseline versus 15 min) and OVH (baseline versus 24 h) were assessed using linear mixed models. Responsiveness to the administration of rescue analgesia (FGS scores before versus one hour after) was assessed using paired t -tests. Results Minimal bias (−0.057) and narrow limits of agreement (−0.351 to 0.237) were observed between the FGS-IMG and FGS-RT. Scores at baseline (FGS-RT: 0.16 ± 0.13 and FGS-IMG: 0.14 ± 0.13) were not different after sedation (FGS-RT: 0.2 ± 0.15, p = 0.39 and FGS-IMG: 0.16 ± 0.15, p = 0.99) nor at 24 h after extubation (FGS-RT: 0.16 ± 0.12, p = 0.99 and FGS-IMG: 0.12 ± 0.12, p = 0.96). Thirteen cats required rescue analgesia; their FGS scores were lower one hour after analgesic administration (FGS-RT: 0.21 ± 0.18 and FGS-IMG: 0.18 ± 0.17) than before (FGS-RT: 0.47 ± 0.24, p = 0.0005 and FGS-IMG: 0.45 ± 0.19, p = 0.015). Conclusions Real-time assessment slightly overestimates image scoring; however, with minimal clinical impact. Sedation with acepromazine-buprenorphine and ovariohysterectomy using a balanced anesthetic protocol did not influence the FGS scores. Responsiveness to analgesic administration was observed with both the FGS-RT and FGS-IMG.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".