Correlation Between Sonographic and In Vivo Measurement of A1 Pulleys in Trigger Fingers

The thickness of 210 A1 pulleys of 21 male and female healthy volunteers in two different age groups (20-35 y and 50-70 y) were measured by ultrasound. In a second group, the thickness of 15 diseased A1 pulleys and 15 A1 pulleys of the corresponding other hand of 10 patients with the clinical diagnosis of trigger finger were measured by ultrasound. During open trigger finger release, a strip of A1 pulley was excised and immediately measured using an electronic caliper. The average pulley thickness of healthy volunteers was 0.43-0.47 mm, compared to 0.77-0.79 mm in patients with trigger finger. Based on the receiver operating characteristic (ROC) curve, a diagnostic cut-off value of the pulley thickness at 0.62 mm was defined in order to differ a trigger finger from a healthy finger (sensitivity and specificity of 85%). The correlation between sonographic and effective intra-operative measurements of pulley thickness was linear and very strong (Pearson coefficient 0.86-0.90). In order to distinguish between healthy and diseased A1 pulleys, 0.62 mm is a simple value to use, which can be applied regardless of age, sex, body mass index (BMI) and height in adults.

Use of Extended Characteristics of Locomotion and Feeding Behavior for Automated Identification of Lame Dairy Cows.

This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow's gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.