JOURNAL ARTICLE
Current treatment and prevention of orthopaedic infections in the horse.
Published In: Equine Veterinary Education, 2023, v. 35, n. 8. P. 437 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Crosby, Corinne E.; Redding, Laurel E.; Ortved, Kyla F. 3 of 3
Abstract
Summary: Orthopaedic infections, including synovial sepsis, osteomyelitis and infection of orthopaedic implants are common in equine medicine. Infections can be caused by haematogenous spread of pathogens, trauma or penetrating injuries, extension of local infections and iatrogenic causes such as surgery and synovial injections. Horses with orthopaedic infections are generally markedly lame and often require aggressive and prolonged therapy. Early diagnosis can greatly impact treatment outcomes and can be facilitated by careful physical examinations, haematology, diagnostic imaging and timely synovial fluid sampling. Concerted efforts should always be made to obtain a positive bacterial culture and sensitivity. Treatment is focused on antimicrobial therapy with local therapy, including intravenous regional limb perfusion and intrasynovial injections, being employed whenever possible; lavage and debridement; and analgesia and supportive care. Responsible use of antimicrobials and antimicrobial stewardship are critical when treating orthopaedic infections. Prognosis will depend on the source and severity of the infection, the causative agent and the time to intervention. Foals and horses can respond well to treatment and return to soundness with early, aggressive and targeted treatment. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Equine Veterinary Education. 2023/08, Vol. 35, Issue 8, p437
- Document Type:Article
- Subject Area:Consumer Health
- Publication Date:2023
- ISSN:0957-7734
- DOI:10.1111/eve.13770
- Accession Number:164701472
- Copyright Statement:Copyright of Equine Veterinary Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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