Use of hyaluronidase in the comparison between manual and automated hematology analysis with the ADVIA 120 to improve analysis of feline body cavity effusions.
J Vet Diagn Invest
; 29(2): 212-216, 2017 Mar.
Article
em En
| MEDLINE
| ID: mdl-28064834
Classification of body cavity effusions is an important step in the investigation and diagnosis of disease in cats. Feline inflammatory effusions are often highly proteinaceous and viscous, which can cause clumping of white cells and subsequently inaccurate nucleated cell counts (NCCs) using automated and manual methods. Microscopic assessment of cellularity can also be difficult given the variable thickness of smears and cell clumping, which skews white cell distribution. The ADVIA 120 uses 2 white cell-counting channels, the basophil/lobularity (WBC/baso) and differential/peroxidase channels, which can provide quite different results in highly viscous feline samples and often disagree with smear assessment of cellularity. We investigated the effects of pre-incubation of feline effusion samples with hyaluronidase and its effects on NCCs and cellularity assessment. NCCs were obtained by automated analysis using the ADVIA 120 and by manual counting methods. Agreement was assessed using a Bland-Altman chart. Pretreatment of samples with hyaluronidase resulted in good agreement between the ADVIA basophil channel and manual counting methods in all samples in the study. However, improvements in NCCs after hyaluronidase treatment were significantly greater in clumped samples, and cell distribution of these samples on direct smears was also improved. Therefore, when nucleated cell clumping is observed on a direct smear, pretreatment of the sample with hyaluronidase prior to analysis on an automated analyzer is advised, with the WBC/baso channel displaying the most accurate NCC.
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01-internacional
Base de dados:
MEDLINE
Assunto principal:
Líquido Ascítico
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Doenças do Gato
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Contagem de Leucócitos
Tipo de estudo:
Diagnostic_studies
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Evaluation_studies
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Guideline
Limite:
Animals
Idioma:
En
Revista:
J Vet Diagn Invest
Ano de publicação:
2017
Tipo de documento:
Article