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Evaluation of Reference Intervals of Some Selected Chemistry Parameters using Bootstrap Technique in Dogs  

Kim, Eu-Tteum (School of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University)
Pak, Son-Il (School of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University)
Publication Information
Journal of Veterinary Clinics / v.24, no.4, 2007 , pp. 509-513 More about this Journal
Abstract
Parametric and nonparametric coupled with bootstrap simulation technique were used to reevaluate previously defined reference intervals of serum chemistry parameters. A population-based study was performed in 100 clinically healthy dogs that were retrieved from the medical records of Kangwon National University Animal Hospital during 2005-2006. Data were from 52 males and 48 females(1 to 8 years old, 2.2-5.8 kg of body weight). Chemistry parameters examined were blood urea nitrogen(BUN)(mg/dl), cholesterol(mg/dl), calcium(mg/dl), aspartate aminotransferase(AST)(U/L), alanine aminotransferase(ALT)(U/L), alkaline phosphatase(ALP)(U/L), and total protein(g/dl), and were measured by Ektachem DT 60 analyzer(Johnson & Johnson). All but calcium were highly skewed distributions. Outliers were commonly identified particularly in enzyme parameters, ranging 5-9% of the samples and the remaining were only 1-2%. Regardless of distribution type of each analyte, nonparametric methods showed better estimates for use in clinical chemistry compare to parametric methods. The mean and reference intervals estimated by nonparametric bootstrap methods of BUN, cholesterol, calcium, AST, ALT, ALP, and total protein were 14.7(7.0-24.2), 227.3(120.7-480.8), 10.9(8.1-12.5), 25.4(11.8-66.6), 25.5(11.7-68.9), 87.7(31.1-240.8), and 6.8(5.6-8.2), respectively. This study indicates that bootstrap methods could be a useful statistical method to establish population-based reference intervals of serum chemistry parameters, as it is often the case that many laboratory values do not confirm to a normal distribution. In addition, the results emphasize on the confidence intervals of the analytical parameters showing distribution-related variations.
Keywords
reference interval; serum chemistry; simulation; bootstrap; dog;
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