Effect of video angle on detection of induced front limb lameness in horses.

BACKGROUND: Lameness examinations are commonly performed in equine medicine. Advancements in digital technology have increased the use of video recordings for lameness assessment, however, standardization of ideal video angle is not available yielding videos of poor diagnostic quality. The objective of this study was to evaluate the effect of video angle on the subjective assessment of front limb lameness. A randomized, blinded, crossover study was performed. Six horses with and without mechanically induced forelimb solar pain were recorded using 9 video angles including horses trotting directly away and towards the video camera, horses trotting away and towards a video camera placed to the left and right side of midline, and horses trotting in a circle with the video camera placed on the inside and outside of the circle. Videos were randomized and assessed by three expert equine veterinarians using a 0-5 point scoring system. Objective lameness parameters were collected using a body-mounted inertial sensor system (Lameness Locator®, Equinosis LLC). Interobserver agreement for subjective lameness scores and ease of grading scores were determined. RESULTS: Induction of lameness was successful in all horses. There was excellent agreement between objective lameness parameters and subjective lameness scores (AUC of the ROC = 0.87). For horses in the "lame" trials, interobserver agreement was moderate for video angle 2 when degree of lameness was considered and perfect for video angle 2 and 9 when lameness was considered as a binary outcome. All other angles had no to fair agreement. For horses in the "sound" trials, interobserver agreement was perfect for video angle 5. All other video angles had slight to moderate agreement. CONCLUSIONS: When video assessment of forelimb lameness is required, a video of the horse trotting directly towards the video camera at a minimum is recommended. Other video angles may provide supportive information regarding lameness characteristics.

Characterization of spatiotemporal and kinetic gait variables in dogs with hindlimb ataxia and bilateral hindlimb lameness.

BACKGROUND: Discriminating the underlying cause of gait abnormalities can be challenging in a clinical setting, especially in the presence of bilateral disease. Pressure-sensitive walkways (PSWs) have been utilized to characterize the gait of dogs with various neurologic or orthopaedic conditions. The potential use of the PSW includes the discrimination of conditions that can be similar in clinical presentation, such as bilateral hindlimb lameness and hindlimb ataxia. The primary aim of this study was to describe the spatial, temporal, and kinetic gait parameters of dogs with hindlimb ataxia or bilateral hindlimb lameness and compare them to those of normal dogs. Forty-six dogs were prospectively recruited. The normal group included 20 dogs with normal neurologic and orthopaedic exams. The orthopaedic group included 15 dogs with bilateral hindlimb orthopaedic diseases with weight-bearing hindlimb lameness and normal neurologic exams. The neurologic group included 11 dogs with ambulatory paraparesis and normal orthopaedic exams. Each dog was walked across the PSW, and at least 3 valid trials were collected. The stride time, stance time, swing time, stride length, gait velocity, peak vertical force (PVF), vertical impulse (VI), and limb symmetry were recorded. The mean values of all parameters from the valid trials were calculated and used for data analysis. The outcomes were compared among all groups. RESULTS: Compared with the normal group, the orthopaedic group had a significantly greater percent body weight distribution (%BWD) and vertical impulse distribution (VID) in the forelimbs. When comparing the spatiotemporal parameters, the neurologic group showed an increase in forelimb stance time compared to that of the normal group. Compared with that in the normal group, the stride velocity in the forelimbs in the orthopaedic group was greater. There were no significant differences in the kinetic parameters between the neurologic group and the normal group, nor in stride time or stride length among the groups. CONCLUSION: The gait parameters obtained by PSW demonstrated that the orthopaedic and neurologic groups may have different compensatory mechanisms for their gait deficiencies. These parameters can potentially be used to construct a predictive model to evaluate PSW as a diagnostic tool in future studies.

Cow key point detection in indoor housing conditions with a deep learning model.

Lameness in dairy cattle is a costly and highly prevalent problem that affects all aspects of sustainable dairy production, including animal welfare. Automation of gait assessment would allow monitoring of locomotion in which the cows' walking patterns can be evaluated frequently and with limited labor. With the right interpretation algorithms, this could result in more timely detection of locomotion problems. This in turn would facilitate timely intervention and early treatment, which is crucial to reduce the effect of abnormal behavior and pain on animal welfare. Gait features of dairy cows can potentially be derived from key points that locate crucial anatomical points on a cow's body. The aim of this study is 2-fold: (1) to demonstrate automation of the detection of dairy cows' key points in a practical indoor setting with natural occlusions from gates and races, and (2) to propose the necessary steps to postprocess these key points to make them suitable for subsequent gait feature calculations. Both the automated detection of key points as well as the postprocessing of them are crucial prerequisites for camera-based automated locomotion monitoring in a real farm environment. Side-view video footage of 34 Holstein-Friesian dairy cows, captured when exiting the milking parlor, were used for model development. From these videos, 758 samples of 2 successive frames were extracted. A previously developed deep learning model called T-LEAP was trained to detect 17 key points on cows in our indoor farm environment with natural occlusions. To this end, the dataset of 758 samples was randomly split into a train (n = 22 cows; no. of samples = 388), validation (n = 7 cows; no. of samples = 108), and test dataset (n = 15 cows; no. of samples = 262). The performance of T-LEAP to automatically assign key points in our indoor situation was assessed using the average percentage of correctly detected key points using a threshold of 0.2 of the head length (PCKh0.2). The model's performance on the test set achieved a good result with PCKh0.2: 89% on all 17 key points together. Detecting key points on the back (n = 3 key points) of the cow had the poorest performance PCKh0.2: 59%. In addition to the indoor performance of the model, a more detailed study of the detection performance was conducted to formulate postprocessing steps necessary to use these key points for gait feature calculations and subsequent automated locomotion monitoring. This detailed study included the evaluation of the detection performance in multiple directions. This study revealed that the performance of the key points on a cows' back were the poorest in the horizontal direction. Based on this more in-depth study, we recommend the implementation of the outlined postprocessing techniques to address the following issues: (1) correcting camera distortion, (2) rectifying erroneous key point detection, and (3) establishing the necessary procedures for translating hoof key points into gait features.

Sensitivity and specificity of mobility scoring for the detection of foot lesions in pasture-based Irish dairy cows.

Lameness is an important production disease in dairy cows worldwide and has detrimental effects on cows' welfare, production, and reproductive performance, thus affecting the sustainability of dairy farming. Timely and effective detection of lameness allows for effective treatment, minimizing progression of disease, and maximizing the prognosis of recovery. Mobility scoring (MSc) is a 4 point (0-3) visual lameness scoring system that is the industry standard in several countries. However, few studies have examined the sensitivity (Se) and specificity (Sp) of MSc to detect foot lesions. The aim of this observational study was to determine the Se and Sp of MSc to detect foot lesions in dairy cattle in a pasture-based system. Five hundred ninety-five primi- and multiparous cows were randomly selected from 12 commercial Irish dairy farms and recruited for the study. Recruited cows were mobility scored and passed through a foot-paring crate where all 4 feet were lifted for examination. The team recorded the anatomical location and severity of any foot lesions present based on appearance only. Then, based on the type and severity of the lesions present, cows were classified according to 3 case definitions case definition 1: Any lesion present; case definition 2: Moderate lesions present (excluding minor lesions expected to have a low probability of affecting gait); and case definition 3: Severe lesions present (only including lesions most likely to result in a detectable gait abnormality). Sensitivity and Sp of MSc was calculated based on a threshold of MSc ≥2, defined as impaired (MSc = 2) or severely impaired (MSc = 3) mobility for each of the 3 case definitions, at the overall level and disaggregated by parity. The overall cow-level lesion prevalence based on the case definition 1 was 0.54 with significant between-herd variation. The overall Se and Sp of MSc for the detection of foot lesions were 0.18 and 0.96, 0.35 and 0.94, 0.43 and 0.94 for the case definitions 1, 2, and 3, respectively. Our findings showed poor Se, but high Sp of MSc for the detection of cows with foot lesions in a pasture-based system.

Allogeneic chondrogenic-induced mesenchymal stem cells for the treatment of tarsometatarsal lameness in horses.

OBJECTIVE: To assess the efficacy of commercial intra-articular blood-derived allogeneic-induced mesenchymal stem cells (CIMSCs) to treat tarsometatarsal lameness in horses. STUDY DESIGN: This was a retrospective cohort study. ANIMALS: Records from 167 adult light breed horses with bilateral tarsometatarsal lameness. METHODS: Horses with tarsometatarsal lameness were retrospectively selected from medical records. Diagnosis followed subjective graded lameness assessment before and after intra-articular analgesia, with graded radiographic tarsal examination. Horses were excluded if they were diagnosed or treated for any other concurrent lameness conditions during the study. Time to last follow-up and time of recurrence of lameness was recorded at veterinary re-assessment. RESULTS: A total of 67 horses were recruited to the CIMSC-treated group and 100 to the corticosteroid (CS)-treated group. Median age was 9 years, with no difference in signalment, use or radiographic grade between groups. First re-examination was 38 days (95% CI: 38-49), with no difference between groups, CIMSC 42 (35-45), control 34 (25-42). Median follow-up was 438 days for CIMSC, 546 for controls. Symptoms of lameness recurred in 86/100 controls compared to 17/67 (25%) CIMSC. Median time to lameness recurring in CIMSC was 336 days (95% CI: 239-400), control 90 days (95% CI: 80-108), p < .0001. Cox proportional hazard ratio for treatment was 8.35, 95% CI: 4.67 to 14.92, p < .0001. CONCLUSIONS: Lameness was abolished in all treated horses. It recurred significantly less often, and later, in CIMSC-treated horses. CLINICAL SIGNIFICANCE: Intra-articular CIMSC treatment results in prolonged soundness in horses with tarsometatarsal lameness.

Feline lung-digit syndrome: A differential diagnosis for shifting, waxing and waning lameness in a cat.

The clinical presentation, cytologic findings, radiographic findings, and postmortem assessment of a cat with primary pulmonary adenocarcinoma with multiple digital metastasis are described. An unusual shifting, waxing and waning pattern of lameness, suspected to be an early manifestation of digital metastasis before any gross lesions were visible, was documented. Initial cytologic finding of a lung nodule was equivocal for diagnosis of neoplasia despite being strongly suspicious. Palliative management was short-lived, with rapid progression culminating in widespread metastasis to multiple digits, muscles, and other organs. The diagnosis of pulmonary adenocarcinoma was confirmed via necropsy and histopathology. Key clinical message: This case report highlights that feline lung-digit syndrome is an important differential diagnosis for an acute, waxing and waning, shifting leg lameness in an older cat. This pattern of lameness should raise the index of suspicion for an underlying primary lung neoplasm, and thoracic imaging (radiographs) should be considered.

Syndrome pulmonaire-digital félin : un diagnostic différentiel des boiteries changeantes, croissantes et décroissantes chez un chatLa présentation clinique, les résultats cytologiques, les résultats radiographiques et l'évaluation post mortem d'un chat atteint d'adénocarcinome pulmonaire primaire avec métastases numériques multiples sont décrits. Un schéma inhabituel de boiterie, variable, croissante et décroissante, suspecté d'être une manifestation précoce de métastases digitales avant que des lésions macroscopiques ne soient visibles, a été documenté. La découverte cytologique initiale d'un nodule pulmonaire était équivoque pour le diagnostic de néoplasie bien qu'elle soit fortement suspecte. La prise en charge palliative a été de courte durée, avec une progression rapide aboutissant à des métastases généralisées à plusieurs doigts, muscles et autres organes. Le diagnostic d'adénocarcinome pulmonaire a été confirmé par autopsie et histopathologie.Message clinique clé :Ce rapport de cas souligne que le syndrome pulmonaire-digital félin est un diagnostic différentiel important pour une boiterie aiguë, croissante et décroissante et mobile des pattes chez un chat ágé. Ce type de boiterie devrait faire suspecter une tumeur primaire du poumon sous-jacente, et une imagerie thoracique (radiographies) devrait être envisagée.(Traduit par Dr Serge Messier).

Predicting lameness in dairy cattle using untargeted liquid chromatography-mass spectrometry-based metabolomics and machine learning.

Lameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness. The aims of this study were to investigate the use of metabolomics and machine learning to develop novel methods to detect lameness. Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) alongside machine learning models and a stability selection method were utilized to evaluate the predictive accuracy of differences in the metabolomics profile of first-lactation dairy cows before (during the transition period) and at the time of lameness (based on visual assessment using the 0-3 scale of the Agriculture and Horticulture Development Board). Urine samples were collected from 2 cohorts of dairy heifers and stored at -86°C before analysis using LC-MS. Cohort 1 (n = 90) cows were recruited as current first-lactation cows with weekly mobility scores recorded over a 4-mo timeframe, from which newly lame and nonlame cows were identified. Cohort 2 (n = 30) cows were recruited within 3 wk before calving, and lameness events (based on mobility score) were recorded through lactation until a minimum of 70 d in milk (DIM). All cows were matched paired by DIM ± 14 d. The median DIM at lameness identification was 187.5 and 28.5 for cohort 1 and 2, respectively. The best performing machine learning models predicted lameness at the time of lameness with an accuracy of between 81 and 82%. Using stability selection, the prediction accuracy at the time of lameness was 80 to 81%. For samples collected before and after calving, the best performing machine learning model predicted lameness with an accuracy of 71 and 75%, respectively. The findings from this study demonstrate that untargeted LC-MS profiling combined with machine learning methods can be used to predict lameness as early as before calving and before observable changes in gait in first-lactation dairy cows. The methods also provide accuracies for detecting lameness at the time of observable changes in gait of up to 82%. The findings demonstrate that these methods could provide substantial advancements in the early prediction and prevention of lameness risk. Further external validation work is required to confirm these findings are generalizable; however, this study provides the basis from which future work can be conducted.

Cost of lameness in dairy herds: An integrated bioeconomic modeling approach.

Foot disorders are costly health disorders in dairy farms, and their prevalence is related to several factors such as breed, nutrition, and farmer's management strategy. Very few modeling approaches have considered the dynamics of foot disorders and their interaction with farm management strategies within a holistic farm simulation model. The aim of this study was to estimate the cost of foot disorders in dairy herds by simulating strategies for managing lameness. A dynamic and stochastic simulation model (DairyHealthSim) was used to simulate the herd dynamics, reproduction management, and health events. A specific module was built for lameness and related herd-level management strategies. Foot disorder occurrences were simulated with a base risk for each etiology [digital dermatitis (DD), interdigital dermatitis, interdigital phlegmon, sole ulcer (SU), white line disease (WLD)]. Two state machines were implemented in the model: the first was related to the disease-induced lameness score (from 1 to 5), and the second concerned DD-state transitions. A total of 880 simulations were run to represent the combination of the following 5 scenarios: (1) housing (concrete vs. textured), (2) hygiene (2 different scraping frequencies), (3) the existence of preventive trimming, (4) different thresholds of DD prevalence detected and from which a collective footbath is applied to treat DD, and (5) farmer's ability to detect lameness (detection rate). Housing, hygiene, and trimming scenarios were associated with risk factors applied for each foot disorder etiologies. The footbath and lameness detection scenarios both determined the treatment setup and the policy of herd observance. The economic evaluation outcome was the gross margin per year. A linear regression model was run to estimate the cost per lame cow (lameness score ≥3), per case of DD and per week of a cow's medium lameness duration. The bioeconomic model reproduced a lameness prevalence varying from 26 to 98% depending on the management scenario, demonstrating a high capacity of the model to represent the diversity of the field situations. Digital dermatitis represented half of the total lameness cases, followed by interdigital dermatitis (28%), SU (19%), WLD (13%), and interdigital phlegmon (4%). The housing scenarios dramatically influenced the prevalence of SU and WLD, whereas scraping frequency and threshold for footbath application mainly determined the presence of DD. Interestingly, the results showed that preventive trimming allowed a better reduction in lameness prevalence than spending time on early detection. Scraping frequency was highly associated with DD occurrence, especially with a textured floor. The regression showed that costs were homogeneous (i.e., did not change with lameness prevalence; marginal cost equals average cost). A lame cow and a DD-affected cow cost €307.50 ± 8.40 (SD) and €391.80 ± 10.0 per year on average, respectively. The results also showed a cost of €12.10 ± 0.36 per week-cow lameness. The present estimation is the first to account for interactions between etiologies and for the complex DD dynamics with all the M-stage transitions, bringing a high level of accuracy to the results.

Crowd sourcing remote comparative lameness assessments for dairy cattle.

Lameness assessments are rarely conducted routinely on dairy farms and when completed typically underestimate lameness prevalence, hampering early diagnosis and treatment. A well-known feature of many perceptual tasks is that relative assessments are more accurate than absolute assessments, suggesting that creating methods that allow for the relative scoring of which cow is more lame will allow for reliable lameness assessments. Here we developed and tested a remote comparative lameness assessment method: we recruited nonexperienced crowd workers via an online platform and asked them to watch 2 videos side-by-side, each showing a cow walking, and to identify which cow was more lame and by how much (on a scale of -3 to 3). We created 11 tasks, each with 10 video pairs for comparison, and recruited 50 workers per task. All tasks were also completed by 5 experienced cattle lameness assessors. We evaluated data filtering and clustering methods based on worker responses and determined the agreement among workers, among experienced assessors, and between these groups. A moderate to high interobserver reliability was observed (intraclass correlation coefficient, ICC = 0.46 to 0.77) for crowd workers and agreement was high among the experienced assessors (ICC = 0.87). Average crowd-worker responses showed excellent agreement with the average of experienced assessor responses (ICC = 0.89 to 0.91), regardless of data processing method. To investigate if we could use fewer workers per task while still retaining high agreement with experienced assessors, we randomly subsampled 2 to 43 (1 less than the minimum number of workers retained per task after data cleaning) workers from each task. The agreement with experienced assessors increased substantially as we increased the number of workers from 2 to 10, but little increase was observed after 10 or more workers were used (ICC > 0.80). The proposed method provides a fast and cost-effective way to assess lameness in commercial herds. In addition, this method allows for large-scale data collection useful for training computer vision algorithms that could be used to automate lameness assessments on farm.

Inertial Sensor Technologies-Their Role in Equine Gait Analysis, a Review.

Objective gait analysis provides valuable information about the locomotion characteristics of sound and lame horses. Due to their high accuracy and sensitivity, inertial measurement units (IMUs) have gained popularity over objective measurement techniques such as force plates and optical motion capture (OMC) systems. IMUs are wearable sensors that measure acceleration forces and angular velocities, providing the possibility of a non-invasive and continuous monitoring of horse gait during walk, trot, or canter during field conditions. The present narrative review aimed to describe the inertial sensor technologies and summarize their role in equine gait analysis. The literature was searched using general terms related to inertial sensors and their applicability, gait analysis methods, and lameness evaluation. The efficacy and performance of IMU-based methods for the assessment of normal gait, detection of lameness, analysis of horse-rider interaction, as well as the influence of sedative drugs, are discussed and compared with force plate and OMC techniques. The collected evidence indicated that IMU-based sensor systems can monitor and quantify horse locomotion with high accuracy and precision, having comparable or superior performance to objective measurement techniques. IMUs are reliable tools for the evaluation of horse-rider interactions. The observed efficacy and performance of IMU systems in equine gait analysis warrant further research in this population, with special focus on the potential implementation of novel techniques described and validated in humans.

Comparing Inertial Measurement Units to Markerless Video Analysis for Movement Symmetry in Quarter Horses.

BACKGROUND: With an increasing number of systems for quantifying lameness-related movement asymmetry, between-system comparisons under non-laboratory conditions are important for multi-centre or referral-level studies. This study compares an artificial intelligence video app to a validated inertial measurement unit (IMU) gait analysis system in a specific group of horses. METHODS: Twenty-two reining Quarter horses were equipped with nine body-mounted IMUs while being videoed with a smartphone app. Both systems quantified head and pelvic movement symmetry during in-hand trot (hard/soft ground) and on the lunge (left/right rein, soft ground). Proportional limits of agreement (pLoA) were established. RESULTS: Widths of pLoA were larger for head movement (29% to 50% in-hand; 22% to 38% on lunge) than for pelvic movement (13% to 24% in-hand; 14% to 24% on lunge). CONCLUSION: The between-system pLoAs exceed current "lameness thresholds" aimed at identifying the affected limb(s) in lame horses. They also exceed published limits of agreement for stride-matched data but are similar to repeatability values and "lameness thresholds" from "non-lame" horses. This is encouraging for multi-centre studies and referral-level veterinary practice. The narrower pLoA values for pelvic movement asymmetry are particularly encouraging, given the difficulty of grading hind limb lameness "by eye".

Evaluation of a small-bore needle arthroscope for diagnosis and treatment of medial coronoid disease in dogs: a pilot study with short-term assessment.

CASE HISTORY: Dogs (n = 15) that were presented to a single veterinary teaching hospital with elbow dysplasia-associated lameness between September 2021 and May 2022, and were determined to require arthroscopy based on imaging results, were prospectively recruited into the study. The median duration of lameness was 4 (min 1, max 24) months. CLINICAL FINDINGS: Various breeds were represented with a median body weight of 31.6 (min 15, max 46.4) kg and median age at presentation of 14 (min 8, max 83) months. Results of imaging modalities (CT) were consistent with medial coronoid disease with fissured or fragmented medial coronoid process in all dogs. ARTHROSCOPIC FINDINGS: Feasibility of the needle arthroscopy (NA) procedure was firstly assessed in a preliminary cadaveric study in forelimbs (n = 10) collected from 10 adult dogs euthanised for reasons unrelated to the study. Elbow exploration was performed through a medial approach beginning with NA (1.9 mm 0° angle scope) followed by standard arthroscopy (SA; 2.4 mm 30° angle scope). The quality and extent of visualisation (scored through the number of anatomical structures visualised) were recorded and statistically compared. As the cadaver study indicated that NA allowed safe inspection of all structures in medial/caudal compartments, this procedure was then used in the dogs requiring treatment. In the clinical setting, elbow exploration was successful in all dogs and the treatment (removal of osteochondral fragments) was performed without requiring conversion into SA. One month after surgery, all dogs had an improvement in their lameness score (0-5) and 12/15 dogs were no longer lame. There was a reduction in Canine Orthopaedic Index scores measured a median of 99 (min 47, max 180) days after surgery (24 (IQR 19.5-31.5)) compared to the pre-operative period (49 (IQR 46.5-57); p < 0.001). CLINICAL RELEVANCE: Needle arthroscopy-assisted removal of osteochondral fragments was performed in all dogs with satisfactory short-term clinical outcome. NA is a feasible technique for diagnosis and lesion assessment in dogs with a fissured or fragmented coronoid process. Larger clinical studies with longer follow-up are necessary to validate the NanoScope operative arthroscopy system as an alternative strategy to SA for video-assisted treatment of medial coronoid disease.

Diagnosis of lameness via data mining algorithm by using thermal camera and image processing method in Brown Swiss cows.

Lameness is one of the culling factors such as mastitis, low milk yield, and infertility that cause economic losses in herd management as they threaten animal health and welfare. The purpose of this study was to evaluate the early detection of lameness in Brown Swiss cattle by using a data mining algorithm by both integrating lameness scores and some image parameters such as Lab (CIE L*, a*, b*), HSB (hue, saturation, brightness), RGB (red, green, blue) by processing thermal images with ImageJ program. In the study, the variables obtained as a result of processing the skin surface temperatures and thermal images taken at the fetlock joint of 33 Brown Swiss cattle were used as independent variables. Also, healthy cows (lameness scores 1 and 2) and unhealthy cows (lameness scores 3, 4, and 5) used in the diagnosis of lameness were used as a binary response variable. Classification and regression tree (CART) was used as a data mining algorithm in the diagnosis of lameness. As a result, the CART algorithm correctly classified 12 of the 13 heads unhealthy cows according to locomotion scores. According to locomotion scores by using CART analysis in this study, independent variables that are used to classify healthy and unhealthy (lame) animals were determined as maximum temperature (Tmax), green (mean), L (max), and age (P<0.05). The cut-off values of these independent variables were predicted as 32.40, 149.14, 97.11, and 5.50 for Tmax, green (mean), L (max), and age, respectively. Also, the sensitivity, specificity, and area under the ROC curve (AUC) of the CART algorithm for locomotion scoring were found as 92.31%, 95%, and 93.7% respectively. The area under ROC curve (AUC) was found to be significant in the diagnosis of lameness (P<0.01). Results showed that the use of CART classification algorithm together with thermal camera and image processing methods is a usefull tool in the detection of lameness in the herds. It is recommended that more comprehensive studies by increasing the number of animals in the future would be more beneficial.

DEVELOPMENT AND EVALUATION OF A STANDARDIZED SYSTEM FOR THE ASSESSMENT OF LOCOMOTOR HEALTH IN ELEPHANTS UNDER HUMAN CARE.

Although lameness is a common problem in elephants (Asian elephant [Elephas maximus] and African elephants Loxodonta africana and Loxodonta cyclotis) under human care, there has not been a standardized lameness assessment system to date. This study developed and evaluated a standardized system for the assessment of locomotion in elephants under human care regardless of husbandry system. In total, 72 elephants out of a possible 73 in the United Kingdom and Ireland were filmed from behind, from in front, and from both sides. Using a questionnaire and a select panel of elephant specialists, a zoo veterinarian, and a locomotion expert, a numerical rating scoring (NRS) system was proposed. Locomotion was scored on a 4-point scale with numerical values 0-4 corresponding to specific criteria as follows: 0 = clinically sound, 1 = stiffness, 2 = abnormal tracking, and 4 = reluctance to bear weight. The intra- and interobserver repeatability of five veterinary surgeons using this system was determined and compared with a visual analog scale (VAS) expressed as a 100-mm line. Overall intraobserver reliability was moderate (Cohen's kappa [κ] = 0.676) and interobserver reliability was fair (κ = 0.37) for the presence of lameness. Interobserver agreement improved from the first scoring to second scoring from slight agreement to fair agreement for stiffness and reluctance to bear weight. Abnormal tracking had moderate intraobserver agreement for both scoring sessions. There were wide widths of agreement for the VAS interobserver (67 mm); however, they were narrower for the intraobserver (33 mm). The developed NRS can be used on freely moving elephants to evaluate elephant locomotion, regardless of husbandry methods, and has been shown to be more reliable than a VAS.

Metabolic alterations in dairy cattle with lameness revealed by untargeted metabolomics of dried milk spots using direct infusion-tandem mass spectrometry and the triangulation of multiple machine learning models.

Lameness is a major challenge in the dairy cattle industry in terms of animal welfare and economic implications. Better understanding of metabolic alteration associated with lameness could lead to early diagnosis and effective treatment, there-fore reducing its prevalence. To determine whether metabolic signatures associated with lameness could be discovered with untargeted metabolomics, we developed a novel workflow using direct infusion-tandem mass spectrometry to rapidly analyse (2 min per sample) dried milk spots (DMS) that were stored on commercially available Whatman® FTA® DMPK cards for a prolonged period (8 and 16 days). An orthogonal partial least squares-discriminant analysis (OPLS-DA) method validated by triangulation of multiple machine learning (ML) models and stability selection was employed to reliably identify important discriminative metabolites. With this approach, we were able to differentiate between lame and healthy cows based on a set of lipid molecules and several small metabolites. Among the discriminative molecules, we identified phosphatidylglycerol (PG 35:4) as the strongest and most sensitive lameness indicator based on stability selection. Overall, this untargeted metabolomics workflow is found to be a fast, robust, and discriminating method for determining lameness in DMS samples. The DMS cards can be potentially used as a convenient and cost-effective sample matrix for larger scale research and future routine screening for lameness.

Graduate Student Literature Review: A systematic review on the associations between nonsteroidal anti-inflammatory drug use at the time of diagnosis and treatment of claw horn lameness in dairy cattle and lameness scores, algometer readings, and lying times.

The objectives of this systematic review were to investigate the association between nonsteroidal anti-inflammatory drug (NSAID) use during the treatment of claw horn lameness in dairy cattle and locomotion score (LS), nociceptive threshold, and lying times. A total of 229 studies were initially identified and had their title and abstract screened. From this, we screened the full text of 23 articles, identifying 6 articles for inclusion in the systematic review. Of these 6, 5 reported LS, 2 reported nociceptor thresholds, and 1 reported lying times. The quality of evidence was assessed using a Cochrane risk-of-bias tool and CONSORT items reported for each included study. Due to heterogeneity between the studies, data were reported following Cochrane's Synthesis without meta-analysis guidelines. Identified heterogeneity between the studies included differences in LS systems and statistical analyses, length of time from enrollment to outcome reported, the NSAID used, concomitant treatments administered, and severity and chronicity of lameness. Recommendations are made with respect to consistency of LS reporting and analysis, along with improvements that may be noted with compulsory reporting guidelines. There were at least some concerns over the risk of bias in 4 of the studies, with risks of bias present in missing outcome data between the study groups. Within the 5 studies included with LS outcomes, there were 22 different pairwise comparisons with either NSAID or NSAID + block as the intervention, with measures of association with presence or absence of lameness as the outcome available for 20 of these comparisons. Animals in the NSAID intervention groups had a lower point estimate lameness risk than animals in the comparison groups in 3 of 8 and 9 of 14 analyses for LS outcomes <10 and ≥10 d post-treatment, respectively. However, there was no difference identified between animals in the NSAID intervention groups compared with the animals in the control group in any of these pairwise comparisons with lameness as the outcome. Twelve pairwise comparisons were reported in the 2 studies with nociceptor threshold as an outcome. Animals in the NSAID intervention groups had a greater nociceptor threshold point estimate compared with animals in the comparison groups in 6 of 6 and 1 of 6 analyses for outcomes <10 and ≥10 d post-treatment, respectively. However, no differences were identified between animals in the NSAID intervention groups and those in the comparison groups. All 4 pairwise comparisons reported in the study with lying times as an outcome found no differences between animals in the NSAID groups and those in the comparison groups. Despite the widespread use of NSAID in the treatment of claw horn lameness, there is a lack of studies of NSAID association with LS, nociceptive thresholds, or lying times. The limited evidence is consistent with no association with NSAID use and those parameters, but comparability across studies was limited by heterogeneity.

The negative impact of lameness on dairy cow reproduction.

Lameness in modern dairy farms is a prevalent disorder that negatively affects all aspects of production. Additionally, is a prevailing contributor to the decreased welfare of cows. Recent research has added valuable knowledge on the negative impacts of lameness on dairy cow reproduction. Lame cows have marked behavioural changes, as well as increased inflammatory and stress indicators compared to healthy herd mates. As a result, the functioning of the hypothalamus-pituitary-ovarian axis is significantly affected and leads to suppressed reproductive performance. Lame cows seem to be more prone to uterine infections post-partum, experience higher levels of negative energy balance, resume ovarian cyclicity to a lower proportion during puerperium and show decreased potential to conceive and higher pregnancy losses. Hormonal treatments of lame cows compensate for some of these disturbances yet fail to fully restore fertility potential. From the available scientific literature is apparent that compromised fertility due to lameness can only be achieved through prevention and prompt diagnosis and treatment of lame cows.

Development of a Novel Approach for Detection of Equine Lameness Based on Inertial Sensors: A Preliminary Study.

Both as an aid for less experienced clinicians and to enhance objectivity and sharp clinical skills in professionals, quantitative technologies currently bring the equine lameness diagnostic closer to evidence-based veterinary medicine. The present paper describes an original, inertial sensor-based wireless device system, the Lameness Detector 0.1, used in ten horses with different lameness degrees in one fore- or hind-leg. By recording the impulses on three axes of the incorporated accelerometer in each leg of the assessed horse, and then processing the data using custom-designed software, the device proved its usefulness in lameness identification and severity scoring. Mean impulse values on the horizontal axis calculated for five consecutive steps above 85, regardless of the leg, indicated the slightest subjectively recognizable lameness, increasing to 130 in severe gait impairment. The range recorded on the same axis (between 61.2 and 67.4) in the sound legs allowed a safe cut-off value of 80 impulses for diagnosing a painful limb. The significance of various comparisons and several correlations highlighted the potential of this simple, affordable, and easy-to-use lameness detector device for further standardization as an aid for veterinarians in diagnosing lameness in horses.

Movement Disorders and Cerebellar Abiotrophy.

Movement disorders are defined as involuntary movements that are not due to a painful stimulus or associated with changes in consciousness or proprioception. Diagnosis involves ruling out any lameness and neurologic disease and characterizing the gait during walking backward and forward and trotting. Shivers causes abnormal hindlimb hypertonicity during walking backward and, when advanced, a few strides walking forward. Stringhalt causes consistent hyperflexion during walking forward and trotting and variable difficulty when walking backward. Classification and potential causes are discussed as well as other enigmatic movement disorders in horses are presented. Cerebellar abiotrophy is reviewed.

Pairwise comparison locomotion scoring for dairy cattle.

Conventional locomotion scoring is a subjective, absolute, and discrete assessment of locomotion. Here we assess pairwise comparison scoring to improve upon the limited intra- and interobserver consistency typical of conventional locomotion scoring. Five observers performed conventional 4-level locomotion scoring using 50 video recordings of dairy cattle, and also assessed 90 pairs of videos (composed from the same 50 recordings) using relative pairwise scoring. Intra- and interobserver consistency of pairwise scores [intraobserver: percentage agreement (PA) = 82%, κ = 0.63; interobserver: PA = 79%, κ = 0.57] were greater than of 4-level absolute scores (intraobserver: PA = 72%, κw = 0.74; interobserver: PA = 56%, κw = 0.59). Pairwise scores were scaled with an optimization method to obtain the position of the 50 recordings on a continuous locomotion scale. These continuous locomotion scores (CLS) were compared with the conventional mean absolute visual locomotion scores (VLS). Correlation between CLS and VLS was strong (τ = 0.69), and consistency between binarized CLS and binarized VLS was high (PA = 84%, κ = 0.66 for threshold VLS ≥1). Just noticeable difference (JND) for locomotion scoring was 0.3 on a 4-level scale ranging from 0 to 3. Pairwise scoring and scaling had the scoring consistency of binary absolute scoring with finer continuous granularity than 4-level absolute scoring. The pairwise scoring method, and associated scaling, offer a more consistent and informative alternative to conventional absolute multilevel locomotion scoring.