Clinical reasoning in canine spinal disease: what combination of clinical information is useful?

Spinal disease in dogs is commonly encountered in veterinary practice. Numerous diseases may cause similar clinical signs and presenting histories. The study objective was to use statistical models to identify combinations of discrete parameters from the patient signalment, history and neurological examination that could suggest the most likely diagnoses with statistical significance. A retrospective study of 500 dogs referred to the Queen Mother Hospital for Animals before June 2012 for the investigation of spinal disease was performed. Details regarding signalment, history, physical and neurological examinations, neuroanatomical localisation and imaging data were obtained. Univariate analyses of variables (breed, age, weight, onset, deterioration, pain, asymmetry, neuroanatomical localisation) were performed, and variables were retained in a multivariate logistic regression model if P<0.05. Leading diagnoses were intervertebral disc extrusion (IVDE, n=149), intervertebral disc protrusion (n=149), ischaemic myelopathy (IM, n=48) and neoplasms (n=44). Multivariate logistic regression characterised IM and acute non-compressive nucleus pulposus extrusions as the only peracute onset, non-progressive, non-painful and asymmetrical T3-L3 myelopathies. IVDE was most commonly characterised as acute onset, often deteriorating, painful and largely symmetrical T3-L3 myelopathy. This study suggests that most spinal diseases cause distinctive combinations of presenting clinical parameters (signalment, onset, deterioration, pain, asymmetry, neuroanatomical localisation). Taking particular account of these parameters may aid decision making in a clinical setting.