White M E, Glickman L T, Barnes-Pallesen F D, Stem E S, Dinsmore P, Powers M S, Powers P, Smith M C, Montgomery M E, Jasko D
Cornell Vet. 1986 Oct;76(4):342-7.
We tested an equation, which had been developed previously using discriminant analysis, for predicting whether a cow has coliform mastitis. Variables indicating a high probability of coliform infection included history of previous mastitis in the affected quarter, weakness, clear or white color of milk, water consistency of the milk, swelling of the udder, lack of previous mastitis in other quarters, lack of palpable udder abscesses, and a high body temperature. Application of this predictive equation to 114 cows with mastitis to determine if they would have coliform organisms cultured from the affected quarters resulted in an accuracy of 71% (sensitivity = 0.42, specificity = 0.85), compared to an accuracy of 62% (sensitivity = .64, specificity = .61) for cowside prediction by the attending clinicians. Changing the cutoff score of the discriminant rule so that the sensitivity of the discriminant prediction was similar to that of the clinicians yielded an accuracy of 64% (sensitivity = .64, specificity = .64).
我们测试了一个先前使用判别分析开发的方程，用于预测奶牛是否患有大肠埃希菌性乳腺炎。表明大肠埃希菌感染可能性高的变量包括患侧乳房先前患乳腺炎的病史、虚弱、乳汁颜色清澈或呈白色、乳汁呈水样、乳房肿胀、其他乳房无先前乳腺炎病史、未触及乳房脓肿以及体温高。将这个预测方程应用于114头患有乳腺炎的奶牛，以确定从患侧乳房培养出的是否为大肠埃希菌，结果准确率为71%（敏感性=0.42，特异性=0.85），而主治临床医生在现场的预测准确率为62%（敏感性=0.64，特异性=0.61）。改变判别规则的临界值，使判别预测的敏感性与临床医生的相似，准确率为64%（敏感性=0.64，特异性=0.64）。
