Assessment of l-lactatemia as a predictor of respiratory disease recognition and severity in feedlot steers

Buczinski, Sébastien; Rademacher, Ryan D.; Tripp, Holt M.; Edmonds, Matthew D.; Johnson, Edward G.; Dufour, Simon

doi:10.1016/j.prevetmed.2014.12.003

Cited by 21 publications

(28 citation statements)

References 33 publications

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“…Calves in the REDI group in the current study may have been identified earlier in the feeding phase compared with previous work due to concurrent administration of metaphylaxis in the CONV group. The diagnosis with the REDI system is based on changes in behavior and previous research has illustrated that temperament is associated with the risk for BRD (Buczinski et al, 2015). The earlier treatments in the REDI pens could be influenced by the 5-d postmetaphylaxis interval used in the CONV pens; however, Fig.…”

Section: Discussionmentioning

confidence: 99%

Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations1

White

Amrine²,

Goehl³

2015

Journal of Animal Science

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Section: Discussionmentioning

confidence: 99%

Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations1

White

Amrine²,

Goehl³

2015

Journal of Animal Science

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“…Buczinski et al ( 121 ) reported that for each 1-unit increase of the log-lactemia there was an increase of 36.5 in hazard of dying of BRD. In general, enhanced L-lactate levels are associated with hypoxemia ( 122 ) and /or endotoxemia ( 123 ) that characterizes ongoing BRD episodes.…”

Section: Energy and Protein Metabolismmentioning

confidence: 99%

“…Thus, L-lactate might be considered a biomarker for assessing an ongoing disease process, such as pneumonia (based on clinical signs and hypoxemia) and for predicting death of clinically ill calves within 24 h. However, contradictory results merit further research into the use of L-lactate and lactate as biomarkers for respiratory diseases in young veal calves. At the same time, practical application of this biomarker might be highly feasible, because it can be measured by a portable analyser at a relatively low cost and results are available in 60 s ( 121 ).…”

Section: Energy and Protein Metabolismmentioning

confidence: 99%

Evaluating Potential Biomarkers of Health and Performance in Veal Calves

et al. 2018

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Veal calves undergo many challenges in the early stages of their life. Such challenges, including mixing procedures and transportation of calves to the veal farm, may have a negative influence on growth rate, feed intake, metabolism, immunity and disease susceptibility of calves. As a consequence, many hematological, physiological, metabolic and immunological parameters of stressed calves might be altered on arrival at the veal farm. Some of these response variables might be useful as biomarkers of performance of calves at the veal farm as they might provide information about an ongoing disease process, or may predict future diseases. Biomarkers might be helpful to group and manage calves in different risk categories after arrival. By adopting treatment decisions and protocols on a risk-group or individual basis, it would be possible to improve animal health and reduce both disease incidence and antibiotic use. Moreover, the use of biomarkers might be an economically feasible approach as some of them do not need invasive techniques and others can be measured in blood already taken during routine checks. Previous literature mainly assessed the physiological responses of calves to transportation. However, information on the link between on-farm arrival data and future health and performance of veal calves is limited. This review, therefore, examined a wide range of papers and aimed to identify potential biomarkers of future health and performance.

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“…The plausible ranges for the relative costs of false negative to false positive cases ratio are presently unknown for dairy calves. We used wide ranges that were obtained on a previous study where four different experts were asked to determine this value in feedlot calves (Buczinski et al, 2015a). In the absence of specific studies on dairy calves reporting this ratio, we assumed plausible ranges variations (1:1, 3:1; 8:1, and 20:1) indicating that the cost of false negative case is generally higher than a false positive case.…”

Section: From Logistic Regression Parameters To Prediction Rulesmentioning

confidence: 99%

Validation of a clinical scoring system for bovine respiratory disease complex diagnosis in preweaned dairy calves using a Bayesian framework

Buczinski

Fecteau

Dubuc

et al. 2018

Preventive Veterinary Medicine

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Bovine respiratory disease complex is a major cause of illness in dairy calves. The diagnosis of active infection of the lower respiratory tract is challenging on daily basis in the absence of accurate clinical signs. Clinical scoring systems such as the Californian scoring system, are appealing but were developed without considering the imperfection of reference standard tests used for case definition. This study used a Bayesian latent class model to update Californian prediction rules. The results of clinical examination and ultrasound findings of 608 preweaned dairy calves were used. A model accounting for imperfect accuracy of thoracic ultrasound examination was used to obtain updated weights for the clinical signs included in the Californian scoring system. There were 20 points (95% Bayesian credible intervals: 11-29) for abnormal breathing pattern, 16 points (95% BCI: 4-29) for ear drop/head tilt, 16 points (95% BCI: 9-25) for cough, 10 points (95% BCI: 3-18) for the presence of nasal discharge, 7 points (95% BCI: -1 to 8) for rectal temperature ≥39.2 °C, and -1 points (95% BCI: -9 to 8) for the presence of ocular discharge. The optimal cut-offs were determined using the misclassification cost-term term (MCT) approach with different possible scenarios of expected prevalence and different plausible ratio of false negative costs/false positive costs. The predicted probabilities of active infection of the lower respiratory tract were also obtained using posterior densities of the main logistic regression model. Depending on the context, cut-off varying from 9 to 16 can minimized the MCT. The optimal cut-off decreased when expected prevalence of disease and false negative/false positive ratio increased.

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Assessment of l-lactatemia as a predictor of respiratory disease recognition and severity in feedlot steers

Cited by 21 publications

References 33 publications

Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations1

Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations1

Evaluating Potential Biomarkers of Health and Performance in Veal Calves

Validation of a clinical scoring system for bovine respiratory disease complex diagnosis in preweaned dairy calves using a Bayesian framework

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