REASONS FOR PERFORMING STUDY: The ability to predict ponies at increased risk of laminitic episodes, when exposed to nutrient dense pasture, would facilitate management to avoid disease. OBJECTIVES: To identify variables and clinically useful cut-off values with reproducible diagnostic accuracy for the prediction of ponies that subsequently developed laminitis when exposed to nutrient dense pasture. METHODS: A cohort of predominantly Welsh and Dartmoor ponies from a closed herd was evaluated in March 2006 (n = 74) and March 2007 (n = 57). Ponies were categorised as never laminitic or previously laminitic according to reported laminitic history and as clinically laminitic (CL) if laminitis was observed within 3 months following evaluation. Body condition score (BCS), cresty neck score (CNS), girth and neck circumferences (NC), withers height, blood pressure and hoof surface temperature, and plasma insulin, glucose, triglyceride, leptin, cortisol, ACTH, uric acid and TNF-alpha concentrations were measured. Analysis of sensitivity, specificity and receiver operating characteristic curves was used to evaluate the diagnostic accuracy for a variable to predict CL ponies. RESULTS: Variables with diagnostic accuracy for the prediction of CL ponies included insulin, leptin, BCS, CNS, and NC:height ratio. Specific cut-off values of insulin (>32 mu/l), leptin (>73 ng/ml), BCS (> or = 7), CNS (> or = 4) and NC:height ratio (>0.71) had reproducible diagnostic accuracy for the prediction of laminitis. Combining tests did not result in higher diagnostic accuracy than individual tests of insulin or leptin during either evaluation. CONCLUSIONS: Tests of insulin and leptin concentrations and measures of generalised (BCS) and localised (CNS or NC:height ratio) obesity were beneficial in the prediction of laminitic episodes. POTENTIAL RELEVANCE: These results highlight the importance of monitoring and reducing insulin concentration, and generalised and regional obesity in ponies to reduce risk of laminitis.
REASONS FOR PERFORMING STUDY: The ability to predict ponies at increased risk of laminitic episodes, when exposed to nutrient dense pasture, would facilitate management to avoid disease. OBJECTIVES: To identify variables and clinically useful cut-off values with reproducible diagnostic accuracy for the prediction of ponies that subsequently developed laminitis when exposed to nutrient dense pasture. METHODS: A cohort of predominantly Welsh and Dartmoor ponies from a closed herd was evaluated in March 2006 (n = 74) and March 2007 (n = 57). Ponies were categorised as never laminitic or previously laminitic according to reported laminitic history and as clinically laminitic (CL) if laminitis was observed within 3 months following evaluation. Body condition score (BCS), cresty neck score (CNS), girth and neck circumferences (NC), withers height, blood pressure and hoof surface temperature, and plasma insulin, glucose, triglyceride, leptin, cortisol, ACTH, uric acid and TNF-alpha concentrations were measured. Analysis of sensitivity, specificity and receiver operating characteristic curves was used to evaluate the diagnostic accuracy for a variable to predict CL ponies. RESULTS: Variables with diagnostic accuracy for the prediction of CL ponies included insulin, leptin, BCS, CNS, and NC:height ratio. Specific cut-off values of insulin (>32 mu/l), leptin (>73 ng/ml), BCS (> or = 7), CNS (> or = 4) and NC:height ratio (>0.71) had reproducible diagnostic accuracy for the prediction of laminitis. Combining tests did not result in higher diagnostic accuracy than individual tests of insulin or leptin during either evaluation. CONCLUSIONS: Tests of insulin and leptin concentrations and measures of generalised (BCS) and localised (CNS or NC:height ratio) obesity were beneficial in the prediction of laminitic episodes. POTENTIAL RELEVANCE: These results highlight the importance of monitoring and reducing insulin concentration, and generalised and regional obesity in ponies to reduce risk of laminitis.
Authors: S A Durward-Akhurst; N E Schultz; E M Norton; A K Rendahl; H Besselink; P A Behnisch; A Brouwer; R J Geor; J R Mickelson; M E McCue Journal: Chemosphere Date: 2018-11-26 Impact factor: 7.086
Authors: Richard J Johnson; Chris Rivard; Miguel A Lanaspa; Silvia Otabachian-Smith; Takuji Ishimoto; Christina Cicerchi; Peter R Cheeke; Bridgett Macintosh; Tanja Hess Journal: J Equine Vet Sci Date: 2013-02 Impact factor: 1.583
Authors: Philippa K Morrison; Chen Bing; Patricia A Harris; Charlotte A Maltin; Dai Grove-White; Caroline McG Argo Journal: PLoS One Date: 2014-11-12 Impact factor: 3.240