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Development of a facial expression scale using footrot and mastitis as models of pain in sheep

Abstract

Management of pain in sheep is limited by the challenges of recognising and accurately quantifying pain in this species. The use of facial expression scoring to assess pain is a well-utilised, practical tool in both humans and non-human animals. The objective of this study was to develop a standardised facial expression pain scale for adult sheep, that could be used reliably and accurately to detect pain associated with naturally occurring painful diseases, such as footrot and mastitis. We also investigated whether the scale could be reliably and accurately utilised by observers after training, enabling the development of an on-farm pain assessment tool. The Sheep Pain Facial Expression Scale (SPFES) was able to correctly identify sheep suffering from disease with a high degree of accuracy (AUC; Footrot: 0.81, Mastitis: 0.80). Diseased sheep scored higher on the scale than controls on the day of disease identification (P<0.05) and diseased sheep showed changes in their facial expression after treatment (P<0.001). The abnormal facial expressions of diseased sheep reduced over time, and at recovery were in line with control sheep. Control sheep did not change their facial expression over time. Five scorers who were trained to use the developed scale also assessed the facial expressions of sheep. The scorers were blind to treatment and session. Scorers reliably (ICC: 0.86) and accurately (α = 0.86) identified changes in the facial expression of sheep with footrot over time (P<0.05), and scored control sheep consistently low over time. The SPFES offers a reliable and effective method of assessing pain in sheep after minimal training.We would like to thank the EU VII Framework Program (FP7-KBBE-2010-4) for funding this study as part of the AWIN project. Boehringer Imgelheim Ltd are thanked for providing the meloxicam used in this study.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.applanim.2016.01.00

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