Antibiotic prescribing in canine infectious respiratory disease

Canine infectious respiratory disease (CIRD) is a common infection that is seen in veterinary practice. The condition is generally mild, self-limiting and does not usually require the use of antibiotics in the treatment of the infection. The aims of this study were to analyse risk factors for CIRD in a large sentinel UK pet population and secondly, identify risk factors for antibiotics being prescribed to cases of CIRD. Dogs were included in the study based on a regular expression applied to the Small Animal Veterinary Surveillance Network (SAVSNET) database at the University of Liverpool. A generalized linear mixed modelling approach was used to investigate risk factors to account for clustering of cases within individual practices. In total, 2163 cases of CIRD were included in the study, with CIRD cases being positively associated with male dogs (OR = 1.18, 95% CI: 1.07 - 1.30) and the autumn season (OR = 2.42, 95% CI: 2.12 - 2.77). Beta-lactamase antibiotics were the most frequently prescribed antibiotic in this study. The median age of dogs receiving an antibiotic was 8.4 years old. Being an older dog (Mature OR = 2.31, 95% CI: 1.60 - 3.34, Geriatric OR = 2.73, 95% CI: 1.62 - 4.58) and a male dog (OR = 1.44, 95% CI: 1.13, 1.84) was positively associated with the odds of receiving an antibiotic. This study provides information that can be used to aid antimicrobial stewardship programmes within the veterinary sector.

Authors

Institutions

Publication Details

Journal
Preventive Veterinary Medicine
Published
2026-04-06
DOI
https://doi.org/10.1016/j.prevetmed.2026.106880
Primary Topic
Antibiotic Use and Resistance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Antibiotic prescribing in canine infectious respiratory disease

Helen E. Clough, Alec Thomas, Alan D. Radford
Preventive Veterinary Medicine
Antibiotic Use and Resistance
article

Antibiotic prescribing in canine infectious respiratory disease

Helen E. Clough, Alec Thomas, Alan D. Radford
article en

Abstract

Canine infectious respiratory disease (CIRD) is a common infection that is seen in veterinary practice. The condition is generally mild, self-limiting and does not usually require the use of antibiotics in the treatment of the infection. The aims of this study were to analyse risk factors for CIRD in a large sentinel UK pet population and secondly, identify risk factors for antibiotics being prescribed to cases of CIRD. Dogs were included in the study based on a regular expression applied to the Small Animal Veterinary Surveillance Network (SAVSNET) database at the University of Liverpool. A generalized linear mixed modelling approach was used to investigate risk factors to account for clustering of cases within individual practices. In total, 2163 cases of CIRD were included in the study, with CIRD cases being positively associated with male dogs (OR = 1.18, 95% CI: 1.07 - 1.30) and the autumn season (OR = 2.42, 95% CI: 2.12 - 2.77). Beta-lactamase antibiotics were the most frequently prescribed antibiotic in this study. The median age of dogs receiving an antibiotic was 8.4 years old. Being an older dog (Mature OR = 2.31, 95% CI: 1.60 - 3.34, Geriatric OR = 2.73, 95% CI: 1.62 - 4.58) and a male dog (OR = 1.44, 95% CI: 1.13, 1.84) was positively associated with the odds of receiving an antibiotic. This study provides information that can be used to aid antimicrobial stewardship programmes within the veterinary sector.

Preventive Veterinary MedicineVol. 253
University of Liverpool (GB)
Zero hunger
Openalex Percentile: Top 19%
Antibiotic Use and Resistance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.