Objective: To evaluate the influence of 3 anesthetic protocols and multiples of minimum alveolar concentration (MAC) on heart rate variability (HRV) with and without nociceptive stimulation in dogs. Animals: 6 healthy adult Beagles. Procedures: Each dog was anesthetized 3 times: with isoflurane alone, with isoflurane and a constant rate infusion of dexmedetomidine (IsoD; 3 μg/kg/h, IV), and with isoflurane and a constant rate infusion of remifentanil (IsoR; 18 μg/kg/h, IV). Individual MAC was determined via supramaximal electrical stimulation. Sinus rhythm–derived intervals between 2 adjacent R-R intervals were exported from ECG recordings. Selected HRV time and frequency domain variables were obtained (at 2-minute intervals) and analyzed offline with signed rank tests before and after stimulation at 0.75, 1.0, and 1. 5 MAC for each anesthetic session. Results: The isoflurane session had the overall lowest prestimulation SDNN (SD of all R-R intervals) values. Prestimulation SDNN values decreased significantly with increasing MAC in all sessions. For the IsoD session, SDNN (milliseconds) or high-frequency power (milliseconds2) was inversely correlated with MAC (Spearman rank correlation coefficient for both variables, −0.77). In the isoflurane and IsoR sessions, heart rate increased significantly after stimulation. In the IsoD session, poststimulation SDNN was increased significantly, compared with prestimulation values, at 0.75 and 1.0 MAC. Conclusions and Clinical Relevance: On the basis of SDNN and high-frequency power values, anesthetic levels between 0.75 and 1.5 MAC within the same anesthetic protocol could be differentiated, but with a large overlap among protocols. Usefulness of standard HRV variables for assessment of anesthetic depth and nociception in dogs is questionable.

Objective: To evaluate the use of high-resolution MRI for hippocampal volumetry in dogs and to define a lower reference limit for hippocampal formation (HF) volume. Animals: 20 dogs (with no history of seizures and no underlying structural brain disease) that underwent MRI of the brain. Procedures: The MRI protocol included a high-resolution T1-weighted 3-D ultrafast gradient-echo sequence aligned in a dorsal plane perpendicular to the long axis of the HF. Images obtained with MRI were retrospectively analyzed by 2 observers (A and B). Intraobserver and interobserver agreement were calculated with the Lin concordance correlation coefficient. Volume measurements of the HF were adjusted for intracranial volume, and a lower 95% reference limit for adjusted HF volume was calculated. Results: There was substantial intraobserver agreement (Lin concordance correlation coefficient, 0.97 [95% confidence interval {CI}, 0.94 to 0.99]) but poor interobserver agreement (Lin concordance correlation coefficient, 0.63 [95% CI, 0.37 to 0.79]). The lower 95% reference limit for adjusted HF volume was 0.56 cm3 (90% CI, 0.52 to 0.60 cm3) for the right HF and 0.55 cm3 (90% CI, 0.52 to 0.58 cm3) for the left HF. Conclusions and Clinical Relevance: HF volumes should be adjusted for intracranial volume to account for the large variation in canine skull size. The amount of time required to perform HF volumetry and low interobserver agreement may restrict this technique to research applications, such as the investigation of epileptic patients for hippocampal sclerosis or other cognitive disorders.

A study was conducted to determine the interdependence among the conformation traits of 28 “Pallaresa” cows using principal component analysis. Originally 21 body linear measurements were obtained, from which eight traits are subsequently eliminated. From the principal components analysis, with raw varimax rotation of the transformation matrix, two principal components were extracted, which accounted for 65.8% of the total variance. The first principal component alone explained 51.6% of the variation, and tended to describe general size, while the second principal component had its loadings for back-sternal diameter. The two extracted principal components, which are traits related to dorsal heights and back-sternal diameter, could be considered in selection programs.

Objective—To determine the association between urine osmolality and specific gravity (USG) in dogs and to evaluate the effect of commonly measured urine solutes on that association. Animals—60 dogs evaluated by an internal medicine service. Procedures—From each dog, urine was obtained by cystocentesis and USG was determined with a refractometer. The sample was divided, and one aliquot was sent to a diagnostic laboratory for urinalysis and the other was frozen at −80°C until osmolality was determined. Urine samples were thawed and osmolality was measured in duplicate with a freezing-point depression osmometer. The correlation between mean urine osmolality and USG was determined; the effect of pH, proteinuria, glucosuria, ketonuria, bilirubinuria, and hemoglobinuria on this relationship was investigated with multiple regression analysis. Results—The Pearson correlation coefficient between urine osmolality and USG was 0.87. The final multivariable regression model for urine osmolality included USG and the presence of ketones; ketonuria had a small negative association with urine osmolality. Conclusions and Clinical Relevance—Results indicated a strong linear correlation between osmolality and USG in urine samples obtained from dogs with various pathological conditions, and ketonuria had a small negative effect on that correlation.