Browsing by Author "Cave N"

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    A pilot study to detect the effects of a green-lipped mussel (Perna canaliculus) nutraceutical on working farm dogs with musculoskeletal abnormalities using accelerometry.
    (Taylor and Francis Group, 2024-08-07) Cave N; Bolton S; Cogger N
    AIMS: To obtain preliminary data on changes in gait from the use of a green-lipped mussel (Perna canaliculus) extract product in working farm dogs with musculoskeletal abnormalities using accelerometry. METHODS: New Zealand working farm dogs (n = 32) with signs of musculoskeletal abnormalities were enrolled in a double-blinded, placebo-controlled cross-over study. Each dog was allocated to one of six groups to receive three trial substances (180 mg full fat green-lipped mussel extract (GLME180); 220 mg full fat green-lipped mussel extract (GLME220); placebo) in one of the six possible different orders. Each trial substance was administered orally once a day for an 8-week period, with a 4-week washout in between each. Dogs wore a collar-mounted triaxial accelerometer for the study duration. Diet and activity were not controlled. Accelerations were recorded continuously and analysed (n = 27) in 10-second activity epochs partitioned into daytime and night-time periods. Analysis of activity during the daytime period was limited to epochs when dogs were gaiting faster than a walk. The median and IQR of activity were determined for the daytime and night-time. Additionally, the 75th and 90th percentiles of daytime activity for each 24-hour period were determined. Mixed effects linear regression models were constructed to determine if each trial substance altered the response variables. RESULTS: During the daytime, the 90th percentile was higher when dogs were given GLME220 compared with the placebo (β coefficient 2.6; 95% CI = 0.25-4.94; p = 0.03). Dogs that started the trial with the GLME products had a higher 90th percentile activity compared with dogs that began with the placebo (β coefficient 26.26; 95% CI = 0.45-52.06; p = 0.046). The 75th percentile for activity was not affected by the GLME product. The daytime IQR was larger when dogs were given the GLME180 product compared with the placebo (β coefficient 1.25; 95% CI = 0.12-2.37; p = 0.03). Night-time median activity and the IQR was greater in dogs that started the trial with the GLME products than in dogs that began with the placebo. The night-time IQR for activity was greater for GLME180 than for the placebo. CONCLUSIONS: Administration of a low dose of the GLME-containing product increased peak activity in working farm dogs with signs of musculoskeletal abnormalities and may improve their performance. CLINICAL RELEVANCE: Even mildly affected working farm dogs might benefit from support of their musculoskeletal abnormalities, and this particular GLME-based product shows promise as an adjunct to other management strategies.
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    Use of a Collar-Mounted Triaxial Accelerometer to Predict Speed and Gait in Dogs
    (MDPI (Basel, Switzerland), 2021-05) Bolton S; Cave N; Cogger N; Colborne GR; Gaunet F
    Accelerometry has been used to measure treatment efficacy in dogs with osteoarthritis, although interpretation is difficult. Simplification of the output into speed or gait categories could simplify interpretation. We aimed to determine whether collar-mounted accelerometry could estimate the speed and categorise dogs' gait on a treadmill. Eight Huntaway dogs were fitted with a triaxial accelerometer and then recorded using high-speed video on a treadmill at a slow and fast walk, trot, and canter. The accelerometer data (delta-G) was aligned with the video data and records of the treadmill speed and gait. Mixed linear and logistic regression models that included delta-G and a term accounting for the dogs' skeletal sizes were used to predict speed and gait, respectively, from the accelerometer signal. Gait could be categorised (pseudo-R2 = 0.87) into binary categories of walking and faster (trot or canter), but not into the separate faster gaits. The estimation of speed above 3 m/s was inaccurate, though it is not clear whether that inaccuracy was due to the sampling frequency of the particular device, or whether that is an inherent limitation of collar-mounted accelerometers in dogs. Thus, collar-mounted accelerometry can reliably categorise dogs' gaits into two categories, but finer gait descriptions or speed estimates require individual dog modelling and validation. Nonetheless, this accelerometry method could improve the use of accelerometry to detect treatment effects in osteoarthritis by allowing the selection of periods of activity that are most affected by treatment.