PubMed · 10183839
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M Goodman, B Wigley. 1993-02-25. After miscarriage.. https://pubmed.ncbi.nlm.nih.gov/10183839/
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OBJECTIVE: To determine whether cows with evidence of previous infection with Neospora caninum were less likely to abort or give birth prematurely during an outbreak of neosporosis, compared with herdmates with evidence of primary infection. DESIGN: Cohort study. ANIMALS: 208 pregnant beef cows. PROCEDURES: Aborted fetuses and calves born prematurely were examined during an outbreak of neosporosis in a herd of beef cows. Sera were collected from all cows during the outbreak and again 71 days later. Cows were classified into groups on the basis of normal and abnormal reproductive outcomes. Sera were examined, using an avidity ELISA procedure for N caninum, and results were compared between groups and among time points. RESULTS: Antibody concentrations decreased significantly and IgG avidity values increased significantly over time. During the outbreak, cows with normal reproductive outcomes were significantly more likely to have high IgG avidity values than cows with abnormal reproductive outcomes. CONCLUSIONS AND CLINICAL RELEVANCE: The herd had numerous abortions and premature births with evidence of recent point-source exposure to N caninum. Therefore, to reduce risk of transmission of N caninum to cattle, attempts should be made to prevent canine feces from contaminating feed, especially feedstuffs used to prepare mixed rations for cattle. Cows with evidence of previous exposure to N caninum were less likely to abort or give birth prematurely during the outbreak than cows with primary infections with N caninum; this finding suggests development of protective immunity in previously infected cows.
This paper discusses statistical methods for the classification of observations into one of two or more groups based on longitudinal observations. Measurements on subjects in longitudinal medical studies are often collected at different times and on a different number of occasions. Classical multivariate methods for linear discriminant analysis are difficult to apply to repeated measurements due to the highly unbalanced structure observed in these data. Linear models for the analysis of longitudinal data proposed by Laird and Ware and non-linear models proposed by Lindstrom and Bates can be used to estimate population parameters for a discriminant model that classifies individuals into distinct predefined groups or populations. An example is presented using data from a study in 150 pregnant women in Santiago, Chile, in order to predict normal versus abnormal pregnancy outcomes.
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