Erythrocyte osmotic fragility and select hematologic variables in postparturient mares and their foals. (17th March 2016)

• Record Type: Journal Article
• Authors: Arfuso, Francesca; Quartuccio, Marco; Bazzano, Marilena; Fazio, Francesco; Piccione, Giuseppe
• Is Part Of: Veterinary clinical pathology. Volume 45:Number 2(2016)
• Page Start: 260
• Page End: 270
• Publication Date: 2016-03-17
• Subjects: Erythrocyte osmotic resistance -- red blood cells -- hemolysis -- neonatal period; Veterinary pathology -- Periodicals; 636.089607
• DOI: 10.1111/vcp.12344
• Languages: English
• ISSNs: 0275-6382

Abstract

Abstract : Background: Knowledge of hematologic function in postparturient mares and foals is crucial for the monitoring of their health status and for the prompt diagnosis of pathologic conditions. Objectives: The aim of this study was to evaluate erythrocyte osmotic fragility (EOF) and select hematologic variables in mares and their foals during the first month after foaling. Methods: Blood samples were collected from each animal every 3 days from day 1 until day 30 after foaling, and tested for RBC count, HGB, HCT, MCV, and EOF. Two‐way repeated measures analysis of variance (ANOVA) and Bonferroni post hoc comparison test were applied to determine the effects of time and age (mares vs foals). Pearson correlation coefficients were computed for EOF and time or MCV values. Results: There was a significant effect of time in RBC, HGB, HCT, and EOF ( P < .001). Statistically significant differences were observed between mares and foals for RBC, MCV, and EOF ( P < .05) throughout the experimental period. Significant correlations between EOF and both time and MCV ( P < .05) were found in mares as well as in foals. Conclusion: These results contribute to the understanding of perinatal changes in hematologic variables in mares and foals. In addition, the data support the relevance of specific reference intervals for postparturient mares and foals. The findings also provide useful information that could help clinicians to better interpret clinical data and diagnose equine disease.