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Time budgets and weight shifting as indicators of pain in hospitalized horses.

Authors :
Nowak M
Martin-Cirera A
Jenner F
Auer U
Source :
Frontiers in pain research (Lausanne, Switzerland) [Front Pain Res (Lausanne)] 2024 Jul 23; Vol. 5, pp. 1410302. Date of Electronic Publication: 2024 Jul 23 (Print Publication: 2024).
Publication Year :
2024

Abstract

Introduction: Pain assessment in horses presents a significant challenge due to their nonverbal nature and their tendency to conceal signs of discomfort in the presence of potential threats, including humans. Therefore, this study aimed to identify pain-associated behaviors amenable to automated AI-based detection in video recordings. Additionally, it sought to determine correlations between pain intensity and behavioral and postural parameters by analyzing factors such as time budgets, weight shifting, and unstable resting. The ultimate goal is to facilitate the development of AI-based quantitative tools for pain assessment in horses.<br />Materials and Methods: A cohort of 20 horses (mean age 15 ± 8) admitted to a university equine hospital underwent 24-h video recording. Behaviors were manually scored and retrospectively analyzed using Loopy® software. Three pain groups were established based on the Pain Score Vetmeduni Vienna : pain-free (P0), mild to moderate pain (P1), and severe pain (P2).<br />Results: Weight shifting emerged as a reliable indicator for discriminating between painful and pain-free horses, with significant differences observed between pain groups ( p  < 0.001) and before and after administration of analgesia. Additionally, severely painful horses (P2 group) exhibited lower frequencies of feeding and resting standing per hour compared to pain-free horses, while displaying a higher frequency of unstable resting per hour.<br />Discussion: The significant differences observed in these parameters between pain groups offer promising prospects for AI-based analysis and automated pain assessment in equine medicine. Further investigation is imperative to establish precise thresholds. Leveraging such technology has the potential to enable more effective pain detection and management in horses, ultimately enhancing welfare and informing clinical decision-making in equine medicine.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (© 2024 Nowak, Martin-Cirera, Jenner and Auer.)

Details

Language :
English
ISSN :
2673-561X
Volume :
5
Database :
MEDLINE
Journal :
Frontiers in pain research (Lausanne, Switzerland)
Publication Type :
Academic Journal
Accession number :
39109240
Full Text :
https://doi.org/10.3389/fpain.2024.1410302