Prevalence, survival analysis and multimorbidity of chronic diseases in the general veterinarian-attended horse population of the UK

Welsh, Claire E., Duz, Marco, Parkin, Timothy D.H. and Marshall, John F. (2016) Prevalence, survival analysis and multimorbidity of chronic diseases in the general veterinarian-attended horse population of the UK. Preventive Veterinary Medicine, 131 . pp. 137-145. ISSN 0167-5877

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Abstract

he average age of the global human population is increasing, leading to increased interest in the effects of chronic disease and multimorbidity on health resources and patient welfare. It has been posited that the average age of the general veterinarian-attended horse population of the UK is also increasing, and therefore it could be assumed that chronic diseases and multimorbidity would pose an increasing risk here also. However, evidence for this trend in ageing is very limited, and the current prevalence of many chronic diseases, and of multimorbidity, is unknown. Using text mining of first-opinion electronic medical records from seven veterinary practices around the UK, Kaplan-Meier and Cox proportional hazard modelling, we were able to estimate the apparent prevalence among veterinarian-attended horses of nine chronic diseases, and to assess their relative effects on median life expectancy following diagnosis. With these methods we found evidence of increasing population age. Multimorbidity affected 1.2% of the study population, and had a significant effect upon survival times, with co-occurrence of two diseases, and three or more diseases, leading to 6.6 and 21.3 times the hazard ratio compared to no chronic disease, respectively. Laminitis was involved in 74% of cases of multimorbidity. The population of horses attended by UK veterinarians appears to be aging, and chronic diseases and their co-occurrence are common features, and as such warrant further investigation.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/803459
Keywords: Horse, electronic medical records, text mining
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Veterinary Medicine and Science
Identification Number: https://doi.org/10.1016/j.prevetmed.2016.07.011
Depositing User: Duz, Marco
Date Deposited: 03 Feb 2017 14:24
Last Modified: 04 May 2020 18:04
URI: https://eprints.nottingham.ac.uk/id/eprint/40318

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