Paper published: Analysis of canine cardiovascular therapeutic agent prescriptions using electronic health records in primary care veterinary practices
The first paper of 2022 has been published in the Journal of Veterinary Cardiology led by Dr Liz Bode, RCVS and European Specialist in Cardiology who is based at Chestergates Veterinary Specialists. This work analysed the cardiovascular therapeutic agents prescribed in the UK, based on data submitted to SAVSNET by participating primary veterinary practices.
- Electronic health records describing 3,579,420 consultations (1,043,042 unique dogs) were collated (1 April 2014 and 31 December 2018) by the Small Animal Veterinary Surveillance Network from 270 veterinary practices. Consultations prescribing at least one CVTA were identified.
- Annual variation in individual prescriptions was analysed using mixed-effects binomial regression models. Free-text clinical narratives were manually read to determine the first-prescribing event for torasemide.
- Twenty-nine thousand and seven consultations (0.81% of all consultations, 95% confidence interval [CI], 0.76–0.86) prescribed CVTA in 14,148 (1.36%) dogs.
- Furosemide (52.8% of CV-prescribing consultations, 95% CI 50.7–54.9) and pimobendan (51.9%, 95% CI 50.1–53.7) were most prescribed. Longitudinal analysis (2014–2018) showed a significant negative temporal trend for angiotensin-converting enzyme inhibitors (p < 0.001), and furosemide (p = 0.003) and a positive temporal trend for pimobendan (p = 0.020) and torasemide (p < 0.001). First prescriptions of torasemide were identified in 16.5% of torasemide-prescribing consultations. Where justification for prescription of torasemide was identified (32.5%), furosemide resistance was the most common (92.0%).
- Electronic health records can be used to temporally monitor prescribing habits, including responses to market authorisations. Despite authorisation in the UK for torasemide use as a first-line diuretic, it was most commonly prescribed after furosemide resistance.
Read the full paper here
See our infographic summarising this work here