A multimodal approach to equine thoracolumbar myofascial pain: integrating clinical examination, AI-based gait analysis, and the ridden horse pain ethogram.

Overview

• This study investigates thoracolumbar myofascial pain syndrome (MPS) in horses by combining clinical palpation, AI-driven gait analysis, and behavioral pain assessments during ridden exercise.
• It explores how physical pain signs relate to gait asymmetry and pain behaviors, and examines the influence of a rider on horse gait symmetry.

Background and Objectives

• Myofascial Pain Syndrome (MPS) is common in horses but often underdiagnosed due to challenges in recognizing its clinical signs and objectively measuring its impact.
• The thoracolumbar region (middle to lower back area) is a common site for MPS in horses, affecting their movement and performance.
• The study aimed to examine relationships between:
• Palpation-based clinical indicators of thoracolumbar MPS (e.g., trigger points, muscle tension)
• Gait asymmetries measured both in-hand (horse led by handler) and while ridden
• Behavioral pain signs using the Ridden Horse Pain Ethogram (RHpE), a standardized tool to evaluate pain during ridden work
• It also aimed to assess how carrying a rider affects gait asymmetry by comparing within-horse data for in-hand versus ridden conditions.

Methods

• Subjects were 20 police horses actively used in mounted police duties from the Spanish National Police in Madrid.
• Clinical examination involved:
• Detecting myofascial trigger points characterized by taut muscle bands and hypersensitive spots
• Assessing for common signs such as the “jump sign” (horse’s reaction to palpation) and restrictions in range of motion
• Checking for local twitch responses—muscle contractions often seen in myofascial pain (none found in this study)
• Gait analysis was done using AI-based methods to objectively measure asymmetries in limb movement, specifically focusing on forelimb push-off asymmetry (HDmax).
• Behavioral assessment employed the RHpE, recording pain-related expressions such as ear position, mouth opening, and gaze intensity during ridden work.

Key Findings

• Prevalence of MPS signs: 100% of horses exhibited at least one thoracolumbar myofascial trigger point.
• Common clinical signs included:
• Jump sign observed in 85% of horses
• Restricted range of motion in 80%
• No local twitch responses detected
• Gait asymmetry analysis:
• No correlation was found between clinical MPS indicators and objective measures of gait asymmetry in either in-hand or ridden conditions.
• Forelimb push-off asymmetry (HDmax) increased significantly when horses were ridden versus led in hand, indicating rider influence on gait symmetry.
• The degree of asymmetry increase was greater in horses with higher training levels, suggesting that more highly trained horses might display more pronounced gait changes under saddle.
• Behavioral pain assessment (RHpE):
• Mean RHpE score was 7.2 out of a possible higher number indicating pain behaviors, where 40% of horses scored 8 or above.
• Most frequent pain behaviors included:
• Ears rotated back (95%)
• Mouth opening (95%)
• Intense stare (80%)
• No significant link was found between RHpE scores and either clinical MPS signs or gait asymmetries during ridden exercise.

Conclusions and Implications

• This study is the first to combine palpation-based clinical examination, objective gait analysis, and behavioral pain assessment to study equine thoracolumbar MPS.
• Palpation remains the cornerstone of diagnosing thoracolumbar MPS, as it identified trigger points in all horses despite no clear connections to measurable gait asymmetries or observed pain behaviors during ridden work.
• The increase in forelimb push-off asymmetry under ridden conditions highlights the rider’s influence on biomechanics, particularly in highly trained horses.
• The lack of correlation between behavioral pain scores and clinical or gait findings suggests that pain expression is complex and multifactorial, requiring a multimodal assessment approach.
• The multimodal approach integrating clinical, biomechanical, and behavioral data may enhance understanding and management of myofascial pain in horses, supporting more accurate diagnosis and targeted treatments.