Use of inline measures of L-lactate dehydrogenase for classification of posttreatment mammary Staphylococcus aureus infection status in dairy cows
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
An automated method for determining whether dairy cows with subclinical mammary infections recover after antibiotic treatment would be a useful tool in dairy production. For that purpose, inline L-lactate dehydrogenase (LDH) measurements was modeled using a dynamic linear model; the variance parameters were estimated using the expectation-maximization algorithm. The method used to classify cows as infected or uninfected was based on a multiprocess Kalman filter. Two learning data sets were created: infected and uninfected. The infected data set consisted of records from 48 cows with subclinical Staphylococcus aureus infection from 4 herds collected in 2010. The uninfected data set came from 35 uninfected cows collected during 2013 from 2 herds. Bacteriological culturing was used as gold standard. To test the model, we collected data from the 48 infected cows 50 d after antibiotic treatment. As a result of the treatment, this test data set consisted of 25 cows that still had a subclinical infection and 23 cows that were recovered. Model sensitivity was 36.0% and specificity was 82.6%. To a large extent, L-lactate dehydrogenase reflected the cow's immune response to the presence of pathogens in the udder. However, cows that were classified correctly before treatment had a better chance of correct classification after treatment. This indicated a variation between cows in immune response to subclinical mammary infection that may complicate the detection of subclinically infected cows and determination of recovery.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Journal of Dairy Science |
Vol/bind | 99 |
Udgave nummer | 10 |
Sider (fra-til) | 8375-8383 |
Antal sider | 9 |
ISSN | 0022-0302 |
DOI | |
Status | Udgivet - 2016 |
ID: 167477634