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タイトル: Screening for ketosis using multiple logistic regression based on milk yield and composition
著者: KAYANO, Mitsunori
KATAOKA, Tomoko
茅野, 光範
キーワード: herd test
metabolic disorder
perinatal disease
P/F ratio
regression analysis
発行日: 2015
出版者: 日本獣医学会
誌名: Journal of Veterinary Medical Science
巻: 77
号: 11
開始ページ: 1473-1478
抄録: Multiple logistic regression was applied to milk yield and composition data for 632 records of healthy cows and 61 records of ketotic cows in Hokkaido, Japan. The purpose was to diagnose ketosis based on milk yield and composition, simultaneously. The cows were divided into two groups: (1) multiparous, including 314 healthy cows and 45 ketotic cows and (2) primiparous, including 318 healthy cows and 16 ketotic cows, since nutritional status, milk yield and composition are affected by parity. Multiple logistic regression was applied to these groups separately. For multiparous cows, milk yield (kg/day/cow) and protein-to-fat (P/F) ratio in milk were significant factors (P<0.05) for the diagnosis of ketosis. For primiparous cows, lactose content (%), solid not fat (SNF) content (%) and milk urea nitrogen (MUN) content (mg/dl) were significantly associated with ketosis (P<0.01). A diagnostic rule was constructed for each group of cows: (1) 9.978 × P/F ratio + 0.085 × milk yield <10 and (2) 2.327 × SNF − 2.703 × lactose + 0.225 × MUN <10. The sensitivity, specificity and the area under the curve (AUC) of the diagnostic rules were (1) 0.800, 0.729 and 0.811; (2) 0.813, 0.730 and 0.787, respectively. The P/F ratio, which is a widely used measure of ketosis, provided the sensitivity, specificity and AUC values of (1) 0.711, 0.726 and 0.781; and (2) 0.678, 0.767 and 0.738, respectively.
URI: http://ir.obihiro.ac.jp/dspace/handle/10322/4221
ISSN: 1347-7439
0916-7250
権利情報: 日本獣医学会
出現コレクション:00A01学術雑誌論文

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