Milne M H, Biggs A M, Fitzpatrick J L, Innocent G T, Barrett D C
Division of Farm Animal Medicine and Production, Department of Veterinary Clinical Studies, Institute of Comparative Medicine, University of Glasgow Veterinary School, Bearsden Road, Glasgow G61 1QH.
Vet Rec. 2003 May 17;152(20):615-7. doi: 10.1136/vr.152.20.615.
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.
农民记录了临床型乳腺炎奶牛的临床症状，并提交牛奶样本进行细菌学检查，以便将临床症状与细菌学检查结果相关联。针对根据微生物学分类为肠杆菌科、主要革兰氏阳性病原体、次要病原体、“无生长”或“所有其他病原体”的乳腺炎病例，计算了奶牛的行为、牛奶外观、产奶量、乳房质地以及注射用抗生素使用情况的优势比。感染肠杆菌科的动物被报告产奶量下降、乳房肿胀或坚硬、牛奶呈水样和/或出现全身症状的几率最高。使用逻辑回归模型预测引起临床型乳腺炎的细菌的革兰氏染色特征。在该模型中被发现为显著预测因子的临床发现是奶牛的行为及其产奶量。该回归模型被用作预测测试的基础。使用一个测试数据集，该测试的敏感性为28%，特异性为96%，阳性预测值为74%，阴性预测值为80%。这些预测的总体准确率为79%。
