Date of Award

2018

Document Type

Master Thesis

Degree Name

Masters of Science (Research)

Department

Biological & Pharmaceutical Science

First Advisor

Dr. Gearoid Sayers

Second Advisor

Dr. Riona Sayers

Third Advisor

Dr. Lea Krump

Abstract

Neonatal calf diarrhoea (NCD) is a major problem to calf health worldwide. Metabolic acidosis, electrolyte imbalances are common complications of NCD, consequently, blood gas analysis is regarded as the gold standard test to assess of severity of these abnormalities in diarrhoeic calves. The objective of this research was to develop blood gas reference ranges for neonatal calves accounting for influencing physiological and environmental factors. As this disease is commonly treated by primary producers, previously published clinical assessment scoring chart was also analysed and compared to gold standard blood gas, in addition to next- generation biomarkers for severity diagnosis for NCD.

Blood gas analysis was conducted on healthy bovines (n = 288). Regression procedures examined the combined effect of year, farm, age, breed type, sex and hours post feeding on each variable. Significant effects were observed for age, sex and breed type on several of the blood gas variables (f* < 0.05 in all cases). Consequently, specific ranges based on the neonate’s age, sex and breed type will allow for more detailed and accurate diagnosis of health and ill- health in neonatal calves.

Evaluation of the clinical assessment scoring (CAS) chart involved the assessment of 443 healthy and diarrhoeic calves. The CAS chart rated a calf s health from healthy to varying degrees of ill-health. Evaluation was performed by comparison of the CAS score with blood gas profiles using ordinal logistic regression and a non-parametric estimation of the Receiver Operating Characteristics (ROC). ROC analysis indicated that the CAS chart can accurately differentiate between health and disease (CAS > 1) when adopting a pH cut-off of 7.34, a bicarbonate cut-off of 25 mM and a base excess cut-off of 0.6 mM (sensitivity > 0.86; specificity > 0.93; AUC > 0.92 in each case). Furthermore, assessment of individual severity classes indicated that the CAS chart can accurately differentiate healthy from mild, and severe from grave (AUC > 0.8 in each case). However, the scoring chart has reduced accuracy in differentiating mild from moderate and moderate from severe cases (AUC < 0.8 in each case).

Assessment of predictive biomarkers anion gap (AG) and strong ion difference (SID) for NDC diagnosis was performed by a non-parametric estimation of ROC analysis by comparison with gold standard variables pH and base excess profiles to determine the health status of bovine neonates (n = 443) and selected biomarkers. Results indicated that AG demonstrated an acceptable degree of accuracy in distinguishing health from ill-health (sensitivity of > 80%, specificity of> 40%, and AUC of> 0.72) and particularly for varying degrees of severity (AUC = 0.9). However, SID showed to have reduced accuracy in distinguishing between health and disease severity (AUC > 0.21).

The development of simple but effective diagnostic tools, are required as useful guides to aid standardised diagnosis and treatment options to reduce illness and fatalities from NCD.

Comments

Submitted to Quality and Qualifications Ireland, July 2018

Access Level

info:eu-repo/semantics/openAccess

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