Veterinary clinical pathology最新文献

Background: In humans, deficiency of a disintegrin-like and metalloprotease with thrombospondin type 1 motifs, number 13 (ADAMTS13), a von Willebrand factor (vWF) cleaving protease, is an underlying mechanism for thrombosis. The role of ADAMTS13 in canine thromboembolic disease is largely unknown.

Objectives: The aims of this study were to evaluate plasma ADAMTS13 activity in healthy adult dogs using a commercially available human ADAMTS13 activity ELISA kit and to establish its reference interval (RI).

Methods: Forty healthy adult dogs were prospectively enrolled. Normal health status was confirmed using physical examination findings, history, and the results of hemogram, biochemical profile, screen test for vector-borne diseases, and urinalysis. Plasma ADAMTS13 activity was assessed using the Diapharma RUO Technozym ADAMTS13 Activity ELISA. The assay's precision, accuracy, and detection limits were also evaluated.

Results: The canine reference population was comprised of 21 spayed females, 14 castrated males, 3 intact females, and 2 intact males. The median plasma ADAMTS13 activity in healthy dogs was 0.76 IU/mL (range 0.45-1.04). The RI lower limit was 0.45 IU/mL (90% confidence interval 0.45-0.47). The upper limit, although calculated (1.04 IU/mL, 90% CI 1.04-1.04), likely does not reflect the true RI upper limit but a technical limitation of the assay; therefore, rendering an RI of > 0.45 IU/mL. The intra- and inter-assay precision and accuracy range were 9.6%, 11.5%, -8.8% to 3.4%, respectively.

Conclusions: The commercially available human ADAMTS13 activity ELISA kit was suitable to analyze canine samples, and the RI for adult dogs was established.

A 5-year-old LaMancha goat buck presented for evaluation of a 1-week history of progressive lameness and carpal swelling in the left thoracic limb. Cytology performed on an aspirate from the left radiocarpal joint identified abundant round to oval, thickly encapsulated, extracellular yeast organisms that occasionally exhibited narrow-based budding, features compatible with Cryptococcus spp. yeast. The patient was euthanized due to poor prognosis, and a necropsy was performed. Histopathology confirmed the presence of numerous fungal yeast associated with the left radiocarpal joint. A cryptococcal serum latex agglutination test was negative. However, panfungal PCR and fungal culture identified the organisms as Cryptococcus gattii. This report describes, for the first time, a case of a C. gattii infection affecting the joint of a goat.

Background: Population-based reference intervals (RIs) are fundamental for appropriate result interpretation. Current recommendations for their determination specify that a direct, de novo approach is preferable, including at least 120 carefully selected subjects. This is not always feasible due to logistical and financial constraints. Recently, several sophisticated algorithms for the indirect estimation of RIs have been proposed in human medicine and described as comparable with direct methods in many cases.

Objectives: Preliminary evaluation of the utility and feasibility of novel indirect methods for determining RIs in the veterinary clinical laboratory.

Methods: Calcium and alanine aminotransferase (ALT) were selected as representative measurands expected to show Gaussian and non-Gaussian distributions, respectively. After limited data filtering, canine results extracted from a laboratory database were used to estimate indirect RIs and 90% confidence intervals (CIs) using the RefineR algorithm. Using 90% CIs as well as permissible differences (pD), the indirect RIs were compared to direct RIs derived by the same laboratory, over the same period, from a population of healthy canine blood donors.

Results: The direct and indirect approaches yielded comparable reference limits for both measurands. Apart from the upper reference limit for Ca, 90% CIs for the reference limits calculated from the conventional direct and indirect methods overlapped. Direct reference limits were within pD calculated from the indirect reference limits.

Conclusion: The indirect method, using the RefineR algorithm, may represent a cost-effective option for RI determination. It may also complement direct approaches and has the potential to be more representative of animal populations.

Background: Lymph node (LN) aspirates are often obtained to distinguish large-cell lymphoma (LCL) from non-lymphoma (NL) in dogs with enlarged lymph nodes.

Objective: Images from cytology slides tested the effects of magnification, image type, and number on a convolutional neural network (CNN) differentiating canine LCL from NL.

Methods: Three hundred images of LCL and NL were used to train a CNN and interrogate the effects of image magnification, type, and number on the model's performance. Identified cases were imaged at 200×, 500×, and 1000× magnification in color and gray-scale and then used to train and identify optimal magnification and image type. The impact of the image number per cohort (50, 100, 150, 200, 250, 300) on the top model's performance was then assessed.

Results: The highest performance with color images was achieved at 1000× magnification, with an accuracy of 95.8%, a Receiving Operating Characteristic (ROC) area of 0.997, and an F-measure of 0.958. Similarly, the best results with gray images, also at 1000× magnification, showed an accuracy of 96.67%, a ROC area of 0.994, and an F-measure of 0.967. Performance improvements were most significant and plateaued as the number of images per class approached 150, with an accuracy of 95%, ROC area of 0.939, and F-measure of 0.95.

Conclusion: The analysis across models suggests that color versus greyscale did not significantly impact overall performance to distinguish LCL or NL. Optimal magnification was 1000×. A minimum of 150 images per class is recommended for pilot CNN studies in this 2-class problem.

Background: The empirical biologic variation (EBV) method to derive analytical performance specifications (APSs) has been provisionally evaluated for use in the veterinary clinical pathology laboratory. Analytical performance can affect EBV APSs. It has been argued that this effect is minimal, but the effect has not been evaluated for the range of performance found in veterinary laboratories.

Objective: Model and compare EBV APSs derived across a range of analytical CV (CV_A) observed in veterinary clinical pathology laboratories.

Method: Published data on biochemistry measurand CV_A in veterinary clinical pathology laboratories and dog reference intervals (RIs) were used to model EBV APSs using Monte Carlo simulation. The modeled EBV APSs were compared with analogous APSs from total allowable error (TE_A) and traditional BV models.

Results: Generally, the EBV-recommended permissible CV_A (pCV_A) was smaller than the observed CV_A when analytical performance was poor. The EBV APSs did not have a consistent relationship with analogous APSs from TE_A or traditional BV systems when analytical performance was judged acceptable using TE_A or BV APSs. When analytical performance was unacceptable, the resulting EBV APSs increased dramatically (sometimes by > 200%) and lost their initial relationship with TE_A or traditional BV-derived APSs. Using log-normal calculations for measurands with a Gaussian distribution produced wider EBV APSs.

Conclusion: The EBV method produces growth-oriented APSs under all modeled conditions and can produce notably more lenient APSs for poorly performing labs than better performing labs. The EBV method can produce acceptable APSs under some conditions and may not be suitable for use in veterinary medicine.