Feasibility and reliability of electrical, mechanical and thermal nociceptive testing and assessment of diffuse noxious inhibitory control in dogs
Bibliographic record
Abstract
Purpose: Quantitative sensory testing has been used to assess the somatosensory system. This study aimed to evaluate the feasibility and reliability of electrical (ENT), mechanical (MNT) and thermal (TNT) nociceptive testing and the effect of a conditioning stimulus on MNT. Patients and methods: Sixteen healthy client-owned dogs were included in this study. Stimulation was applied bilaterally to the dorsal and plantar aspect of the metacarpus and metatarsus respectively, using transcutaneous electrical stimulator, algometry and a cold nociceptive device in a randomized order until a behavior response was observed or a cut-off reached. Tests were performed twice (60 seconds apart) by two observers. Retesting was performed 5 hours later. The diffuse noxious inhibitory control was tested by comparing MNT pre- and post-conditioning stimuli. Sham-testing was performed for ENT and TNT. Statistical analysis included linear model and intra-class correlation coefficient ( P <0.05). Results: Feasibility was 99% (ENT), 93.5% (MNT) and 93.6% (TNT). Data for TNT were not analyzed due to inconsistent results. Mean ± SD were 48±22.6 mA (ENT) and 11.9±3.5 N (MNT). MNT was higher for thoracic than for pelvic limbs ( P =0.002). Conditioning stimulus increased MNT ( P =0.049). Inter-observer reliability was 91.4% (ENT) and 60.9% (MNT). False-positive responses were 15% (ENT) and 35.7% (TNT). Conclusion: ENT was feasible, repeatable and superior to MNT and TNT. The assessment of the diffuse noxious inhibitory control with a conditioning stimulus showed promising results in dogs. These tools could be used in naturally-occurring disease to provide insight on their underlying mechanisms and therapeutics. Keywords: electrical threshold, mechanical threshold, thermal threshold, quantitative sensory testing, diffuse noxious inhibitory controls, canine
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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 | 0.013 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".