Ozturan Yalcin Alper, Akin Ibrahim
Department of Surgery, Faculty of Veterinary Medicine, Aydin Adnan Menderes University, Efeler, Aydin, Turkey.
Vet Med Sci. 2025 Jul;11(4):e70496. doi: 10.1002/vms3.70496.
Lameness detection is essential for effective dairy cattle management, with accurate diagnosis improving animal welfare and reducing economic losses. Senior veterinary students must acquire these skills before graduation to ensure competent diagnosis in the field.
This study aimed to evaluate the reliability and accuracy of senior veterinary students in detecting and scoring lameness in dairy cows.
The study included 201 senior veterinary students who scored lameness in cows using video recordings and a 5-point scoring system. Students' lameness scores were compared to those assigned by an experienced observer using a confusion matrix, with sensitivity, specificity, and accuracy calculated. Intra-rater reliability was assessed using intraclass correlation coefficients, while inter-rater reliability was evaluated using Krippendorff's alpha. Binary logistic regression was performed to assess the impact of lameness severity on detection accuracy.
Students demonstrated high accuracy for severe lameness (93.67%) and healthy cases (85.93%), with sensitivities of 75.84% and 74.46%, respectively. However, sensitivity for mild to moderate lameness was lowest. Specificity ranged from 81.87% for mild cases to 98.12% for severe cases. Inter- and intra-rater reliability showed various agreement coefficients across lameness categories. Logistic regression indicated decreased accuracy with increasing lameness severity.
Gaps in detecting intermediate lameness highlight the need for enhanced training methods in veterinary education. Integrating advanced tools can improve diagnostic accuracy and support better lameness detection in practice.
跛行检测对于有效的奶牛管理至关重要,准确的诊断可改善动物福利并减少经济损失。高年级兽医专业学生必须在毕业前掌握这些技能,以确保在实际工作中能够进行准确的诊断。
本研究旨在评估高年级兽医专业学生检测奶牛跛行及对其进行评分的可靠性和准确性。
该研究纳入了201名高年级兽医专业学生,他们通过视频记录和五分制评分系统对奶牛的跛行情况进行评分。使用混淆矩阵将学生的跛行评分与经验丰富的观察者给出的评分进行比较,并计算敏感性、特异性和准确性。使用组内相关系数评估评分者内部的可靠性,而使用克里彭多夫阿尔法系数评估评分者之间的可靠性。进行二元逻辑回归以评估跛行严重程度对检测准确性的影响。
学生对重度跛行(93.67%)和健康病例(85.93%)表现出较高的准确性,敏感性分别为75.84%和74.46%。然而,对轻度至中度跛行的敏感性最低。特异性范围从轻度病例的81.87%到重度病例的98.12%。评分者之间和评分者内部的可靠性在不同跛行类别中显示出不同的一致性系数。逻辑回归表明随着跛行严重程度的增加准确性降低。
在检测中度跛行方面存在差距,这凸显了兽医教育中加强培训方法的必要性。整合先进工具可以提高诊断准确性,并在实践中更好地支持跛行检测。