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检测奶牛泌乳末期的乳房内感染。

Detecting intramammary infection at the end of lactation in dairy cows.

机构信息

Cognosco, Anexa FVC, PO Box 21, Morrinsville, 3300, New Zealand.

DairyNZ Ltd., Private Bag 3221, Hamilton, 3240, New Zealand.

出版信息

J Dairy Sci. 2021 Sep;104(9):10232-10249. doi: 10.3168/jds.2020-20036. Epub 2021 May 28.

Abstract

To reduce antimicrobial use, infusion of antimicrobials into only infected cows at the end of lactation (selective dry cow therapy) is preferable to infusion of every cow with antimicrobials. Use of selective dry cow antimicrobial therapy requires differentiation of probably infected from uninfected cows to enable treatment allocation. Milk somatic cell count (SCC) has been used to distinguish between cows with and without intramammary infection (IMI). However, SCC may be influenced by milk yield, stage of lactation, breed, and herd-level variables such as prevalence of infection. Cut points for SCC, to distinguish between cows with and without an IMI, may need to differ between cow age groups and breeds, or among herds. This study evaluated associations between SCC and major pathogen IMI in one or more quarters of 2,606 cows from 36 herds in 4 regions of New Zealand. In the last week of lactation, cows selected at random had milk samples collected from each quarter, and the teat-end condition and hygiene of the udder were scored. Herd- and cow-level data including age, breed, milk volume, and SCC at each production were recorded, and bulk tank milk SCC and volume of milk shipped were collated. At cow level, the association between average, maximum, and last cow-composite SCC, and presence of a major pathogen IMI in one or more quarters of cows, was examined using receiver operator curves. Predictive logistic regression models were then developed that included potential effect modifiers such as age, milk yield, and bulk tank milk SCC. The population average prevalence of major pathogen IMI was 7.2% of cows (95% confidence interval = 5.9-8.6), and this varied significantly between herds. The average, maximum, and last cow-composite SCC of lactation were all predictive of presence of a major pathogen IMI and did not differ in their ability to discriminate infected from uninfected cows. However, the optimal cut points for the last SCC, the maximum SCC, and average SCC were 108, 152, and 105 × 1,000 cells/mL, respectively. Inclusion of age, bulk tank SCC, and history of clinical mastitis improved overall model fit. However, inclusion of these variables did not improve the discriminatory power of maximum cow-composite SCC used alone. We conclude that cow-composite SCC on its own resulted in sensitivities and specificities of between 0.76 and 0.86, and 0.71 to 0.80, respectively, for determination of presence of major pattern IMI, and the predictive value was not improved by addition of other predictor variables.

摘要

为了减少抗菌药物的使用,在泌乳末期仅对感染的奶牛进行抗菌药物输注(选择性干奶牛疗法)优于对所有奶牛进行抗菌药物输注。使用选择性干奶牛抗菌治疗需要区分可能感染和未感染的奶牛,以便进行治疗分配。牛奶体细胞计数(SCC)已用于区分有和无乳腺炎(IMI)的奶牛。然而,SCC 可能受产奶量、泌乳阶段、品种以及感染流行等牛群水平变量的影响。用于区分有和无 IMI 的奶牛的 SCC 截断值可能因奶牛年龄组和品种的不同,或因牛群的不同而有所不同。本研究评估了 SCC 与新西兰 4 个地区 36 个牛群中 2606 头奶牛的一个或多个乳区的主要病原体 IMI 之间的关系。在泌乳的最后一周,随机选择的奶牛从每个乳区采集奶样,并对乳头末端状况和乳房卫生进行评分。记录了牛群和奶牛水平的数据,包括年龄、品种、产奶量以及每次生产时的 SCC,同时整理了奶罐 SCC 和牛奶产量。在奶牛水平上,使用接收器操作曲线检查了平均、最大和最后奶牛综合 SCC 与奶牛一个或多个乳区存在主要病原体 IMI 之间的关系。然后,开发了包含潜在效应修饰因子(如年龄、产奶量和奶罐 SCC)的预测逻辑回归模型。主要病原体 IMI 的人群平均流行率为 7.2%(95%置信区间=5.9-8.6),且在牛群间存在显著差异。泌乳期间的平均、最大和最后奶牛综合 SCC 均预测存在主要病原体 IMI,且在区分感染和未感染奶牛方面能力无差异。然而,最后 SCC、最大 SCC 和平均 SCC 的最佳截断值分别为 108、152 和 105×1000 个细胞/ml。包含年龄、奶罐 SCC 和临床乳腺炎史可提高整体模型拟合度。然而,包含这些变量并不能提高单独使用最大奶牛综合 SCC 的判别能力。我们得出的结论是,奶牛综合 SCC 的灵敏度和特异性分别在 0.76 到 0.86 之间和 0.71 到 0.80 之间,用于确定主要模式 IMI 的存在,并且添加其他预测变量并不能提高预测值。

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