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“The present study aimed to obtain data on the occurrence of Giardia duodenalis in calves in four major cattle rearing countries in Europe (Germany, UK, France and Italy), along with genotyping data and risk factors associated with these infections. A total of 2072 calves were sampled on 207 farms. The majority of the animals were Holstein dairy or mixed Holstein calves (n = 1565 or 75.5%), and were female (n = 1640 or 79.1%). The average age was 7.8 weeks PARP inhibitor (SD = 4.1; median = 7; range = 2-16 weeks). All fecal samples were tested using a commercially available monoclonal antibody-based ELISA. The overall apparent prevalence

of G. duodenalis for the four countries was 45.4% (n = 942/2072) and the overall farm prevalence was 89.9% (186/207), with differences in both animal and farm prevalence between the four countries. The prevalence was significantly higher in animals up to 8 weeks (OR=1.88; P<0.001) compared to older calves, SBI-0206965 and several management factors including contact with the Dam, Frequency of cleaning of the Maternity Pens, and Disinfection of the Calf Housing were found to be associated with infection. Positive samples were withheld for genotyping using the beta-giardin and triose phosphate isomerase gene: G. duodenalis assemblage E was most prevalent,

although 43% of the isolates were typed as assemblage A, with differences in between countries. Furthermore, 32% of the examined samples was found to be a mixed assemblage A and E infection, which is consistent with previous reports. The results of the present study confirm previous findings in other European countries that G. duodenalis infections are common in calves.

The infection especially occurs in animals younger than 2 months, and the proportion of positive animals gradually decreased with increasing age. (C) 2012 Elsevier B.V. All rights reserved.”
“Aims: The prediction of individuals’ use of medical services and associated costs is crucial for medical systems. We modeled a risk assessment equation that included patient sociodemographic characteristics and health risk behaviors (obesity, smoking, and alcohol abuse) to strengthen the power of self-reported health status to predict healthcare resource use. We also sought to uncover gender-specific differences selleck inhibitor in the predictive value of the models.\n\nMethods: Before their first primary care visit, 509 new patients were interviewed. Data collected included sociodemographics, self-reported health status Medical Outcomes Study Short-Form (MOS SF-36), body mass index (BMI), and screening for alcoholism and smoking. Subsequent use of healthcare services for 1 year was determined by reviewing medical and billing records.\n\nResults: Generalized linear models and two-part regressions were estimated relating the five types of charges (plus total charges) to self-reported physical health status, controlling for gender, age, education, income, obesity, smoking, alcohol abuse, and mental health status.