OBJECTIVE To assess the effect of decreased platelet and WBC counts on platelet aggregation as measured by a multiple-electrode impedance aggregometer in dogs.
ANIMALS 24 healthy dogs.
PROCEDURES From each dog, 9 mL of blood was collected into a 10-mL syringe that contained 1 mL of 4% sodium citrate solution to yield a 10-mL sample with a 1:9 citrate-to-blood ratio. Each sample was then divided into unmanipulated and manipulated aliquots with progressively depleted buffy-coat fractions such that 2 to 3 blood samples were evaluated per dog. The Hct for manipulated aliquots was adjusted with autologous plasma so that it was within 2% of the Hct for the unmanipulated aliquot for each dog. All samples were analyzed in duplicate with a multiple-electrode impedance aggregometer following the addition of ADP as a platelet agonist. The respective effects of platelet count, plateletcrit, Hct, and WBC count on platelet aggregation area under the curve (AUC), aggregation, and velocity were analyzed with linear mixed models.
RESULTS WBC count was positively associated with platelet AUC, aggregation, and velocity; blood samples with leukopenia had a lower AUC, aggregation, and velocity than samples with WBC counts within the reference range. Platelet count, plateletcrit, and Hct did not have an independent effect on AUC, aggregation, or velocity.
CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that WBC count was positively associated with platelet aggregation when ADP was used to activate canine blood samples for impedance aggregometry. That finding may be clinically relevant and needs to be confirmed by in vivo studies.
Objective—To evaluate use of infrared spectroscopy for diagnosis of traumatic arthritis in horses.
Animals—48 horses with traumatic arthritis and 5 clinically and radiographically normal horses.
Procedures—Synovial fluid samples were collected from 77 joints in 48 horses with traumatic arthritis. Paired samples (affected and control joints) from 29 horses and independent samples from an affected (n = 12) or control (7) joint from 19 horses were collected for model calibration. A second set of 20 normal validation samples was collected from 5 clinically and radiographically normal horses. Fourier transform infrared spectra of synovial fluids were acquired and manipulated, and data from affected joints were compared with controls to identify spectroscopic features that differed significantly between groups. A classification model that used linear discriminant analysis was developed. Performance of the model was determined by use of the 2 validation datasets.
Results—A classification model based on 3 infrared regions classified spectra from the calibration dataset with overall accuracy of 97% (sensitivity, 93%; specificity, 100%). The model, with cost-adjusted prior probabilities of 0.60:0.40, yielded overall accuracy of 89% (sensitivity, 83%; specificity, 100%) for the first validation sample dataset and 100% correct classification of the second set of independent normal control joints.
Conclusions and Clinical Relevance—The infrared spectroscopic patterns of fluid from joints with traumatic arthritis differed significantly from the corresponding patterns for controls. These alterations in absorption patterns may be used via an appropriate classification algorithm to differentiate the spectra of affected joints from those of controls.