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应用潜在类别分析预测牛舍牛的呼吸疾病转归。

Predicting bovine respiratory disease outcome in feedlot cattle using latent class analysis.

机构信息

School of Life and Environmental Sciences, Faculty of Science, University of Sydney, Camden, NSW, Australia.

Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Camden, NSW, Australia.

出版信息

J Anim Sci. 2020 Dec 1;98(12). doi: 10.1093/jas/skaa381.

Abstract

Bovine respiratory disease (BRD) is the most significant disease affecting feedlot cattle. Indicators of BRD often used in feedlots such as visual signs, rectal temperature, computer-assisted lung auscultation (CALA) score, the number of BRD treatments, presence of viral pathogens, viral seroconversion, and lung damage at slaughter vary in their ability to predict an animal's BRD outcome, and no studies have been published determining how a combination of these BRD indicators may define the number of BRD disease outcome groups. The objectives of the current study were (1) to identify BRD outcome groups using BRD indicators collected during the feeding phase and at slaughter through latent class analysis (LCA) and (2) to determine the importance of these BRD indicators to predict disease outcome. Animals with BRD (n = 127) were identified by visual signs and removed from production pens for further examination. Control animals displaying no visual signs of BRD (n = 143) were also removed and examined. Blood, nasal swab samples, and clinical measurements were collected. Lung and pleural lesions indicative of BRD were scored at slaughter. LCA was applied to identify possible outcome groups. Three latent classes were identified in the best model fit, categorized as non-BRD, mild BRD, and severe BRD. Animals in the mild BRD group had a higher probability of having visual signs of BRD compared with non-BRD and severe BRD animals. Animals in the severe BRD group were more likely to require more than 1 treatment for BRD and have ≥40 °C rectal temperature, ≥10% total lung consolidation, and severe pleural lesions at slaughter. Animals in the severe BRD group were also more likely to be naïve at feedlot entry and the first BRD pull for Bovine Viral Diarrhoea Virus, Bovine Parainfluenza 3 Virus, and Bovine Adenovirus and have a positive nasal swab result for Bovine Herpesvirus Type 1 and Bovine Coronavirus. Animals with severe BRD had 0.9 and 0.6 kg/d lower overall ADG (average daily gain) compared with non-BRD animals and mild BRD animals (P < 0.001). These results demonstrate that there are important indicators of BRD severity. Using this information to predict an animal's BRD outcome would greatly enhance treatment efficacy and aid in better management of animals at risk of suffering from severe BRD.

摘要

牛呼吸道疾病(BRD)是影响育肥牛的最主要疾病。在育肥场中,常使用一些指标来评估 BRD,如临床症状、直肠温度、计算机辅助肺部听诊(CALA)评分、BRD 治疗次数、病毒病原体存在情况、病毒血清转换以及屠宰时的肺部损伤等,但这些指标预测动物 BRD 结果的能力各不相同,且目前尚无研究确定这些 BRD 指标的组合如何定义 BRD 疾病结果的分组数量。本研究的目的是(1)通过潜在类别分析(LCA)确定在育肥阶段和屠宰时使用 BRD 指标收集的 BRD 结果组,(2)确定这些 BRD 指标对预测疾病结果的重要性。通过临床症状识别患有 BRD 的动物(n = 127),并将其从生产围栏中移除进行进一步检查。无 BRD 临床症状的对照动物(n = 143)也被移除并进行了检查。收集了血液、鼻腔拭子样本和临床测量数据。屠宰时对肺部和胸膜病变进行评分,这些病变提示 BRD。应用 LCA 来确定可能的结果组。最佳模型拟合确定了三个潜在类别,分为非 BRD、轻度 BRD 和重度 BRD。与非 BRD 和重度 BRD 动物相比,轻度 BRD 动物出现 BRD 临床症状的可能性更高。重度 BRD 动物更有可能需要多次 BRD 治疗,直肠温度≥40°C、总肺实变≥10%以及严重的胸膜病变。重度 BRD 动物在进入育肥场时更有可能是初次感染 Bovine Viral Diarrhoea Virus、Bovine Parainfluenza 3 Virus 和 Bovine Adenovirus,并且鼻腔拭子结果对 Bovine Herpesvirus Type 1 和 Bovine Coronavirus 呈阳性。与非 BRD 动物和轻度 BRD 动物相比,重度 BRD 动物的总体日增重(ADG)分别低 0.9 和 0.6 kg/d(P<0.001)。这些结果表明,BRD 严重程度存在重要指标。使用这些信息预测动物的 BRD 结果将极大地提高治疗效果,并有助于更好地管理患有严重 BRD 的动物。

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