Abstract
The annual outbreaks of cutaneous and renal glomerular vasculopathy (CRGV) reported in UK dogs display a distinct seasonal pattern (November to May) suggesting possible climatic drivers of the disease. The...
Highlights
Cutaneous and renal glomerular vasculopathy (CRGV) – known as ‘Alabama Rot’ - is a disease of unknown aetiology variably associated with clinically relevant acute kidney injury (AKI)
All cutaneous and renal glomerular vasculopathy (CRGV) cases diagnosed between November 2012 and May 2017 were included in the analysis
As there was considerable collinearity between the two variables habitat and landcover, models were run with either habitat or landcover to determine which of the two predictors had the higher relative contribution to CRGV distribution and this variable was retained in the model while the other was dropped
Summary
Cutaneous and renal glomerular vasculopathy (CRGV) – known as ‘Alabama Rot’ - is a disease of unknown aetiology variably associated with clinically relevant acute kidney injury (AKI). Pairwise combinations of a range of potential lr and tc were trialled to determine the best combination for identifying the optimal number of trees (a tree complexity of 4 and learning rate of 0.005) This optimum combination should result in more than 1000 trees (Elith and others 2008b) while allowing the model to converge. In order to determine whether any variables were best omitted from the model, variables were removed in turn, starting with those having the smallest relative influence, and average change in predictive deviance calculated. Variables for which this value exceeded the model’s original estimated standard error were excluded from the model
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