Cystitis: significant associations between pathology, histology, and quantitative bacteriology in sows, a cross-sectional study.

Bacteriuria Cystitis E. coli Histopathology Pathology Porcine Sows Urinary tract infections

Journal

Porcine health management
ISSN: 2055-5660
Titre abrégé: Porcine Health Manag
Pays: England
ID NLM: 101684126

Informations de publication

Date de publication:
26 Sep 2023
Historique:
received: 30 04 2023
accepted: 12 09 2023
medline: 27 9 2023
pubmed: 27 9 2023
entrez: 26 9 2023
Statut: epublish

Résumé

The importance of cystitis in pig production is controversial and sparse information is available on its frequency and etiology in sows. The aim of this study was to determine the prevalence of bacteriuria, macroscopical and histological lesions of the urinary bladder in culled sows. Urinary bladders and urine samples were obtained from 176 culled sows at slaughter. The urine samples collected by cystocentesis were analyzed to determine bacterial content and pathological findings, macroscopic as well as microscopic, of the bladder were recorded for each sow. The prevalence of bacteriuria, defined by bacterial concentrations ≥ 10 This study shows that signs of cystitis are common in culled sows. The prevalence of cystitis was 34% based on bacteriological examination, 27% based on macroscopic examination and 46% based on histological examination. Significant associations were found between the three indicators of cystitis: bacteriuria, pathological and histological lesions of the bladder. Based on macroscopic changes and histopathology of the bladder, the cut-off of ≥ 10

Sections du résumé

BACKGROUND BACKGROUND
The importance of cystitis in pig production is controversial and sparse information is available on its frequency and etiology in sows. The aim of this study was to determine the prevalence of bacteriuria, macroscopical and histological lesions of the urinary bladder in culled sows. Urinary bladders and urine samples were obtained from 176 culled sows at slaughter. The urine samples collected by cystocentesis were analyzed to determine bacterial content and pathological findings, macroscopic as well as microscopic, of the bladder were recorded for each sow.
RESULTS RESULTS
The prevalence of bacteriuria, defined by bacterial concentrations ≥ 10
CONCLUSION CONCLUSIONS
This study shows that signs of cystitis are common in culled sows. The prevalence of cystitis was 34% based on bacteriological examination, 27% based on macroscopic examination and 46% based on histological examination. Significant associations were found between the three indicators of cystitis: bacteriuria, pathological and histological lesions of the bladder. Based on macroscopic changes and histopathology of the bladder, the cut-off of ≥ 10

Identifiants

pubmed: 37752562
doi: 10.1186/s40813-023-00336-8
pii: 10.1186/s40813-023-00336-8
pmc: PMC10523660
doi:

Types de publication

Journal Article

Langues

eng

Pagination

41

Informations de copyright

© 2023. BioMed Central Ltd., part of Springer Nature.

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Auteurs

Lola Kathe Tolstrup (LK)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Groennegaardsvej 15, 1870, Frederiksberg C, Denmark. lolatolstrup@gmail.com.

Páll Skúli Leifsson (PS)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Groennegaardsvej 15, 1870, Frederiksberg C, Denmark.

Luca Guardabassi (L)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Groennegaardsvej 15, 1870, Frederiksberg C, Denmark.

Jens Peter Nielsen (JP)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Groennegaardsvej 15, 1870, Frederiksberg C, Denmark.

Ken Steen Pedersen (KS)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Groennegaardsvej 15, 1870, Frederiksberg C, Denmark. ken@sund.ku.dk.
Ø-Vet A/S, Koeberupvej 33, 4700, Naestved, Denmark. ken@sund.ku.dk.

Classifications MeSH