The application of faecal egg count results and statistical inference for clinical decision making in foals

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Abstract

This study investigated the impact of variability in Parascaris spp. and strongyle faecal egg counts (FEC)from foals on treatment decision-making and detection of a patent infection. A single faecal sample was collected once daily for three days from 53 foals and a FEC was performed on three separate portions of each sample (total of nine egg counts per foal). Differences in the decision to administer an anthelmintic using the results of a single count (C 1 ), the mean of three (X¯ 1–3 )or nine counts (X¯ 1–9 )and the upper 5% confidence limit of the gamma confidence interval (CI)of the estimate of the distribution mean (μ)from three (UCL 1–3 )and nine counts (UCL 1–9 )were determined for a range of egg count thresholds. The UCL 1–9 was used as the best estimate of μ, hypothesis testing for treatment and the comparison of treatment decision-making using C 1 , X¯ 1–3 , X¯ 1–9 and UCL 1–3 . The results of this study demonstrated that a point estimate (C 1 or X¯ 1–3 )was of limited value for estimating the distribution mean of egg counts in faeces and there was overall poor agreement in treatment decision-making for individual foals using C 1 compared with UCL 1–9 . Of the foals with C 1 of zero eggs per gram, 54% and 47% had Parascaris and strongyle eggs in subsequent counts, respectively. The egg density in faeces is inhomogeneous, resulting in considerable variability in egg count results for an individual foal: between faecal piles, different portions of a faecal pile and days. The use of the negative binomial distribution CI for μ takes this variability into account and is recommended for use when interpreting FEC data from horses.
Original languageEnglish
Pages (from-to)7-12
Number of pages6
JournalVeterinary Parasitology
Volume270
Early online date29 Apr 2019
DOIs
Publication statusPublished - Jun 2019

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