Reliability of equine visual lameness classification as a function of expertise, lameness severity and rater confidence.
Abstract: Visual equine lameness assessment is often unreliable, yet the full understanding of this issue is missing. Here, we investigate visual lameness assessment using near-realistic, three-dimensional horse animations presenting with 0-60 per cent movement asymmetry. Animations were scored at an equine veterinary seminar by attendees with various expertise levels. Results showed that years of experience and exposure to a low, medium or high case load had no significant effect on correct assessment of lame (P>0.149) or sound horses (P≥0.412), with the exception of a significant effect of case load exposure on forelimb lameness assessment at 60 per cent asymmetry (P=0.014). The correct classification of sound horses as sound was significantly (P<0.001) higher for forelimb (average 72 per cent correct) than for hindlimb lameness assessment (average 28 per cent correct): participants often saw hindlimb lameness where there was none. For subtle lameness, errors often resulted from not noticing forelimb lameness and from classifying the incorrect limb as lame for hindlimb lameness. Diagnostic accuracy was at or below chance level for some metrics. Rater confidence was not associated with performance. Visual gait assessment may overall be unlikely to reliably differentiate between sound and mildly lame horses irrespective of an assessor's background.
© British Veterinary Association 2018. No commercial re-use. See rights and permissions. Published by BMJ.
Publication Date: 2018-09-21 PubMed ID: 30242083DOI: 10.1136/vr.105058Google Scholar: Lookup
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Summary
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This research article examines the efficacy of visual assessments for identifying lameness in horses, finding that these assessments may not reliably distinguish between sound and mildly lame horses, regardless of the assessor’s experience or expertise.
Research Context and Methodology
- The researchers are focusing on understanding the reliability of visual assessments in diagnosing lameness in horses. These assessments are crucial but often prove to be unreliable, creating a need for executing more rigorous study.
- For this investigation, near-realistic three-dimensional horse animations were used, these animations showed varying degrees of movement asymmetry, ranging from 0-60 per cent.
- The analysis was done among attendees of an equine veterinary seminar who had diverse levels of professional experience and differing exposure to case loads.
Assessment Results and Findings
- The study showed that the level of the assessor’s experience and exposure to low, medium or high case loads did not significantly impact their accuracy in diagnosing lame or sound horses. A notable exception was that high case load exposure did have a significant effect on forelimb lameness assessment at 60 per cent asymmetry.
- It was found that assessors were significantly more accurate in identifying sound horses as sound when assessing for forelimb lameness than hindlimb lameness. There were more misdiagnoses with hindlimb lameness, with professionals often seeing lameness where there was none.
- For subtle lameness cases, the usual errors were in either not noticing forelimb lameness or marking the wrong limb as lame in cases of hindlimb lameness.
- In terms of some metrics, the diagnostic accuracy was at or below chance level, indicating a high level of inaccuracy in the visual assessments.
Rater Confidence and Overall Implication
- Rater confidence showed no significant association with their performance. That is, confidence in assessment did not equate to accuracy of assessment.
- The overall implication of the study is that visual gait assessments might not be a reliable way to differentiate between sound and mildly lame horses, irrespective of the assessor’s background or level of experience.
Cite This Article
APA
Starke SD, Oosterlinck M.
(2018).
Reliability of equine visual lameness classification as a function of expertise, lameness severity and rater confidence.
Vet Rec, 184(2), 63.
https://doi.org/10.1136/vr.105058 Publication
Researcher Affiliations
- School of Engineering, University of Birmingham, Birmingham, UK.
- Department of Surgery and Anaesthesiology of Domestic Animals, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.
MeSH Terms
- Animals
- Clinical Competence / statistics & numerical data
- Forelimb / physiopathology
- Gait / physiology
- Hindlimb / physiopathology
- Horse Diseases / diagnosis
- Horses
- Humans
- Lameness, Animal / diagnosis
- Reproducibility of Results
- Severity of Illness Index
Conflict of Interest Statement
Competing interests: None declared.
Citations
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