Title: 2015 ACVIM Forum Research Abstract Program Document date: 2015_5_27
ID: 3pnuj5ru_908
Snippet: Horses of any age, breed, and sex from the continental US were eligible for study enrollment as long as they were documented to be exhibiting one or more of the following clinical signs: generalized or regional hypertrichosis, muscle wasting, abnormal fat distribution, lethargy, laminitis (unknown etiology), polyuria, polydipsia, susceptibility to infections, abnormal sweating, and/or inappropriate lactation. Normal horses were excluded from the .....
Document: Horses of any age, breed, and sex from the continental US were eligible for study enrollment as long as they were documented to be exhibiting one or more of the following clinical signs: generalized or regional hypertrichosis, muscle wasting, abnormal fat distribution, lethargy, laminitis (unknown etiology), polyuria, polydipsia, susceptibility to infections, abnormal sweating, and/or inappropriate lactation. Normal horses were excluded from the study. At initial visit, demographic data, signalment, a physical examination was conducted, clinical signs documented, and blood was drawn for basal ACTH, fasting insulin, and glucose. Blood samples were processed and shipped overnight to the Animal Health Diagnostic Center, Cornell University, Ithaca, NY for analysis. Non-PPID horses (PPID -) were characterized with ACTH levels <35 pg/mL (November-July) and ACTH <100 pg/mL (August-October). PPID+ horses were characterized with ACTH levels >35 pg/mL (November through July) and ACTH >100 pg/mL (August-October). Hyperinsulinemia was characterized as fasting insulin >20 ulU/mL. Glucose was considered to be elevated if >113 mg/mL. In order to evaluate the combined effects of these variables on PPID status, multiple logistic regression (MLR) analysis was applied to PPID status using backward elimination of variables at the 5% level of significance. Odds ratios for the significant predictors of PPID status in the MLR analyses were computed along with their corresponding 95% confidence intervals.
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