Use of clinical information to predict the characteristics of bacteria isolated from clinical cases of bovine mastitis.

Abstract

Farmers recorded the clinical signs of cows with clinical mastitis and submitted milk samples for bacteriological examination, so that the clinical signs could be correlated with the bacteriological findings. Odds ratios for the demeanour of the cow, the appearance of the milk, milk yield, udder texture, and the administration of parenteral antibiotics were calculated for mastitis cases classified in terms of their microbiology as either enterobacteriaceae, major Gram-positive pathogens, minor pathogens, 'no growths' or 'all other pathogens'. Animals infected with enterobacteriaceae had the highest odds of being reported as having a reduced milk yield, swollen or hard udders, watery milk and/or being systemically sick. A logistic regression model was used to predict the Gram-staining characteristics of the bacteria causing clinical mastitis. The clinical findings found to be significant predictors in the model were the demeanour of the cow and its milk yield. The regression model was used as a basis for a predictive test. Using a test data set, the sensitivity of the test was 28 per cent, its specificity was 96 per cent, the positive predictive value was 74 per cent and the negative predictive value was 80 per cent. The overall accuracy of these predictions was 79 per cent.