| Autor: |
Helen Aceto, David A. Wilson, Jeff B. Bender, J.H. Wilson, D.C. Van Metre, Mary Rose Paradis, S. P. Shaw, J. S. Weese, A. Ruple-Czerniak, Paul S. Morley |
| Rok vydání: |
2013 |
| Předmět: |
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| Zdroj: |
Equine Veterinary Journal. 46:435-440 |
| ISSN: |
0425-1644 |
| DOI: |
10.1111/evj.12190 |
| Popis: |
Summary Reasons for performing study Methods that can be used to estimate rates of healthcare-associated infections and other nosocomial events have not been well established for use in equine hospitals. Traditional laboratory-based surveillance is expensive and cannot be applied in all of these settings. Objectives To evaluate the use of a syndromic surveillance system for estimating rates of occurrence of healthcare-associated infections among hospitalised equine cases. Study design Multicentre, prospective longitudinal study. Methods This study included weaned equids (n = 297) that were admitted for gastrointestinal disorders at one of 5 participating veterinary referral hospitals during a 12-week period in 2006. A survey form was completed by the primary clinician to summarise basic case information, procedures and treatments the horse received, and whether one or more of 7 predefined nosocomial syndromes were recognised at any point during hospitalisation. Adjusted rates of nosocomial events were estimated using Poisson regression. Risk factors associated with the risk of developing a nosocomial event were analysed using multivariable logistic regression. Results Among the study population, 95 nosocomial events were reported to have occurred in 65 horses. Controlling for differences among hospitals, 19.7% (95% confidence interval, 14.5–26.7) of the study population was reported to have had at least one nosocomial event recognised during hospitalisation. The most commonly reported nosocomial syndromes that were unrelated to the reason for hospitalisation were surgical site inflammation and i.v. catheter site inflammation. Conclusions Syndromic surveillance systems can be standardised successfully for use across multiple hospitals without interfering with established organisational structures, in order to provide useful estimates of rates related to healthcare-associated infections. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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