Prepartal Decrease in Plasma Total Cholesterol Concentration in Dairy Cows Developed Subclinical Ketosis

Ro, Younghye; Choi, Won; Kim, Hoyung; Kim, Danil

doi:10.17555/jvc.2017.06.34.3.222

Cited by 1 publication

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“…Also, a sudden increase in calcium (Ca) demand at the onset of lactation can lead to hypocalcemia as calcium homeostatic mechanism does not adapt to the change in demand optimally (8). These nutritional and physiological changes during the transition period increase the risk of metabolic and infectious diseases after calving in dairy cows (30).…”

Section: Introductionmentioning

confidence: 99%

“…Periparturient disease has a direct impact on the profitability of a dairy farm, owing to productivity loss as well as treatment costs (3). Therefore, early prediction of the occurrence of periparturient disease and the execution of preventive measures through timely monitoring and intervention can reduce economic losses (30). A metabolic profile refers to the analysis of blood biochemical parameters that are useful for the assessment and prevention of metabolic diseases in dairy cows (26).…”

Section: Introductionmentioning

confidence: 99%

“…A metabolic profile refers to the analysis of blood biochemical parameters that are useful for the assessment and prevention of metabolic diseases in dairy cows (26). Using metabolic parameters, many studies have predicted postpartum diseases such as displaced abomasum (20,25), retained placenta (17,25,27), ketosis (1,17,30), and hypocalcemia (4). These parameters include NEFA, total cholesterol (T-chol), and β-hydroxybutyrate (BHB).…”

Section: Introductionmentioning

confidence: 99%

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Receiver Operating Characteristic Analysis for Prediction of Postpartum Metabolic Diseases in Dairy Cows in an Organic Farm in Korea

Kim

Choi

et al. 2022

J Vet Clin

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Postpartum diseases should be predicted to prevent productivity loss before calving especially in organic dairy farms. This study was aimed to investigate the incidence of postpartum metabolic diseases in an organic dairy farm in Korea, to confirm the association between diseases and prepartum blood biochemical parameters, and to evaluate the accuracy of these parameters with a receiver operating characteristic (ROC) analysis for identifying vulnerable cows. Data were collected from 58 Holstein cows (16 primiparous and 42 multiparous) having calved for 2 years on an organic farm. During a transition period from 4 weeks prepartum to 4 weeks postpartum, blood biochemistry was performed through blood collection every 2 weeks with a physical examination. Thirty-one (53.4%) cows (9 primiparous and 22 multiparous) were diagnosed with at least one postpartum disease. Each incidence was 27.6% for subclinical ketosis, 22.4% for subclinical hypocalcemia, 12.1% for retained placenta, 10.3% for displaced abomasum and 5.2% for clinical ketosis. Between at least one disease and no disease, there were significant differences in the prepartum levels of parameters like body condition score (BCS), non-esterified fatty acid (NEFA), total bilirubin (T-bil), direct bilirubin (D-bil) and NEFA to total cholesterol (T-chol) ratio (p < 0.05). The ROC analysis of each of these prepartum parameters had the area under the curve (AUC) <0.7. However, the ROC analysis with logistic regression including all these parameters revealed a higher AUC (0.769), sensitivity (71.0%), and specificity (77.8%). The ROC analysis with logistic regression including the prepartum BCS, NEFA, T-bil, D-bil, and NEFA to T-chol ratio can be used to identify cows that are vulnerable to postpartum diseases with moderate accuracy.

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Section: Introductionmentioning

confidence: 99%