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Peer-reviewed veterinary case report

Factors predictive of abnormal results for computed tomography of the head in horses affected by neurologic disorders: 57 cases (2001-2007).

Journal:
Journal of the American Veterinary Medical Association
Year:
2009
Authors:
Sogaro-Robinson, Cristina et al.
Affiliation:
Department of Veterinary Clinical Sciences · United States
Species:
horse

Abstract

OBJECTIVE: To determine neurologic indications associated with abnormal results for computed tomography (CT) imaging of the head of horses affected by neurologic disorders. DESIGN: Retrospective case series. ANIMALS: 57 horses. PROCEDURES: Signalment, history, clinical abnormalities, and clinicopathologic findings were obtained from medical records of horses examined because of neurologic disorders, and precontrast and postcontrast CT images of the head were reviewed. Data were analyzed by use of univariate and multivariate logistic regression. RESULTS: For a horse with abnormal mentation, odds of having abnormal results for CT imaging of the head was 30 times (95% confidence interval [CI], 2.36 to 374.63) the odds for a similar horse without abnormal mentation. For a horse with cranial nerve deficits, odds of having abnormal results for CT imaging of the head was 11 times (95% CI, 1.00 to 127.96) the odds for a similar horse without cranial nerve deficits. For a horse with seizure-like activity, odds of having abnormal results for CT imaging of the head was 0.05 times (95% CI, 0 to 0.90) the odds for a similar horse without seizures. CONCLUSIONS AND CLINICAL RELEVANCE: These results suggested that alterations in consciousness and cranial nerve deficits were strong predictors of abnormal CT findings for the head of affected horses. Thus, CT can be a useful complementary diagnostic test in horses with these neurologic deficits. In contrast, alternative diagnostic tests (eg, electroencephalography and magnetic resonance imaging) should be considered in horses with seizure-like activity that do not have head trauma or cranial nerve deficits.

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Original publication: https://pubmed.ncbi.nlm.nih.gov/19601739/