Use of inline measures of l-lactate dehydrogenase for classification of posttreatment mammary Staphylococcus aureus infection status in dairy cows
| Autor: | Anders Kristensen, Søren Dinesen Østergaard, T.W. Bennedsgaard, C. Hildebrandt Jørgensen |
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| Rok vydání: | 2016 |
| Předmět: |
Veterinary medicine
Antibiotics Staphylococcal Infections/drug therapy Mastitis medicine.disease_cause 0403 veterinary science MILK Mammary Glands Animal/drug effects Udder Mastitis Bovine l-lactate dehydrogenase Subclinical infection food and beverages 04 agricultural and veterinary sciences Staphylococcal Infections Anti-Bacterial Agents Milk medicine.anatomical_structure Staphylococcus aureus L-Lactate Dehydrogenase/analysis BOVINE Female Mastitis Bovine/drug therapy 040301 veterinary sciences medicine.drug_class Multiprocess model Staphylococcus aureus/drug effects Biology Staphylococcal infections Sensitivity and Specificity Mammary Glands Animal Dairy cow Genetics medicine Animals Milk/microbiology L-Lactate Dehydrogenase 0402 animal and dairy science Gold standard (test) medicine.disease 040201 dairy & animal science BETA-D-GLUCOSAMINIDASE MODEL Anti-Bacterial Agents/therapeutic use Immunology Linear Models Herd SOMATIC-CELL COUNTS Cattle Animal Science and Zoology Food Science |
| Zdroj: | Jørgensen, C, Kristensen, A R, Østergaard, S & Bennedsgaard, T W 2016, ' Use of inline measures of l-lactate dehydrogenase for classification of posttreatment mammary Staphylococcus aureus infection status in dairy cows ', Journal of Dairy Science, vol. 99, no. 10, pp. 8375-8383 . https://doi.org/10.3168/jds.2016-10858 |
| ISSN: | 0022-0302 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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