Influence of multiple factors on hematologic reference intervals in horses residing in livery yards in Spain

Abstract

The hemogram is a valuable tool for equine veterinary practitioners to check the health status and response to exercise in their patients.It is also used as an aid in the investigation of clinical disease. 1 Equine blood values are influenced by many factors, such as age, 2 gender, 2 breed, 3-5 season, 6,7 and exercise, 8-10 among other factors, and are intimately linked to the management practices in each country or geographical region. [2][3][4] However, most of these physiologic features have been studied individually, often in specific breeds or horse types. To our knowledge, there are no reports that examined the possible influence of combining multiple factors and their interactions on equine blood values in one study.In Spain, there are some studies published regarding hematologic values in horses; however, most studies were of Spanish purebred horses residing in stud farms. 2,11,12 No studies have evaluated

Life tables of annual life expectancy and risk factors for mortality in cats in the UK

“…First, the subset of covariates with the lowest weighted sum of standardised differences between the Akaike information criterion and Bayesian information criterion from all possible combinations of the covariates was selected. 20 Next, all possible models using the selected subset of covariates with biologically meaningful pairwise interactions between the covariates were made, and the final model was chosen from these models using the aforementioned method. 20 Diagnostic plots and variance inflation factors were generated to examine the assumptions and collinearity of the final models, respectively.…”

“… 20 Next, all possible models using the selected subset of covariates with biologically meaningful pairwise interactions between the covariates were made, and the final model was chosen from these models using the aforementioned method. 20 Diagnostic plots and variance inflation factors were generated to examine the assumptions and collinearity of the final models, respectively. The significance level was set at 0.05 for all analyses.…”

A stochastic assessment to quantify the risk of introduction of African swine fever virus to Taiwan via illegal pork products carried by international travellers

“…Association between the number of detected PPTs between 1 January 2017 and 31 December 2017 and four factors, namely, origin of the flight or ship (not the origin of a PPT), d (including Port of Kinmen), m , and the type of travel (i.e., by flight, ship from China to Taiwan proper, ship from China to Kinmen Island, and ship from other countries) were examined using multivariable Poisson modelling with the number of travellers as the offset (Civil Aeronautics Administration, 2020). The optimal model among models of all possible combinations of the covariates (i.e., 2 4 combinations) was selected using an equal‐weighted sum of standardised differences of the Akaike information criterion and the Bayesian information criterion (Buendia et al., 2021).…”

“…Association between the number of detected PPTs between 1 January ). The optimal model among models of all possible combinations of the covariates (i.e., 2 4 combinations) was selected using an equal-weighted sum of standardised differences of the Akaike information criterion and the Bayesian information criterion (Buendia et al, 2021).…”

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