Inter-evaluator bias and applicability of feline body condition score from visual assessment

Abstract

Background: Body Condition Score (BCS) is an effective tool for assessing body weight and overall body composition. Objectives: To determine whether BCS can be accurately assessed solely from photographs of cats, and to evaluate inter-evaluator bias in visually assessed BCS. Animals: Thirty-eight client-owned cats enrolled during routine wellness checks. Methods: A set of cat images collected from online sources was administered as a quiz to nine evaluators. To validate the results, BCS was clinically assessed for 38 enrolled cats through palpation by one evaluator, and also visually assessed by all nine evaluators using only cat photographs. Results: Inter-evaluator bias was found to be relatively low in BCS assessment based on animal images (mean±SE=0.35±0.03). In the validation set of 38 client-owned cats, the visual assessment of BCS deviated from the clinically assessed BCS by 0.61±0.04, which was slightly higher than the deviation observed in the mock image set. In both scenarios, majority voting among nine evaluators achieved the highest accuracy, demonstrating its effectiveness in reducing evaluator bias. Inter-evaluator bias caused a 14% misclassification between ideal and overweight BCS, but only 1% between ideal and obese, indicating minimal bias in diagnosing feline obesity. Conclusions and clinical importance: The ability to accurately assess BCS through photographic evaluation will enhance remote consultations in telemedicine and support large-scale epidemiological studies on feline obesity. This study has developed a tool for evaluating and minimizing inter-evaluator bias in BCS assessments across diverse practitioners and settings, thereby improving the consistency and comparability of large feline obesity research.