Association of antiseizure medications and adverse cardiovascular events: a global health federated network analysis
<h3>Introduction</h3> The aim of this study was to compare the risk of adverse cardiovascular events (CVEs) associated with antiseizure medications in patients with epilepsy (PWE). <h3>Methods</h3> A retrospective case-control cohort study was conducted using TriNetX, a global-health federated network. Patients >18 years, with a diagnosis of epilepsy and a medication code of carbamazepine, lamotrigine or valproate were compared. Patients with cardiovascular disease prior to the diagnosis of epilepsy were excluded. Cohorts were 1:1 propensity score matched according to age, sex, ethnicity, cardiovascular risk factors and epilepsy classification. The primary outcome was a composite of acute adverse CVEs (ischaemic stroke, ischaemic heart disease, and heart failure) at 10 years. <h3>Results</h3> Of 374,950 PWE included; three cohorts were established: 1) Carbamazepine compared to lamotrigine, n=4,722; 2) Valproate compared to lamotrigine, n=5,478; 3) Valproate compared to carbamazepine, n=4,544. Carbamazepine and valproate were associated with significantly higher risk of adverse CVE’s compared to lamotrigine, HR 1.390 (95%CI 1.160, 1.665) and 1.264 (95%CI 1.050, 1.521) respectively. Valproate was associated with a higher risk death than carbamazepine HR 1.226 (95%CI 1.017, 1.478). <h3>Conclusion</h3> Carbamazepine and valproate were associated with increased CVE risks compared to lamotrigine. Cardiovascular risk factor monitoring should be considered for these patients.
Authors
- Tommaso Bucci (ORCID: https://orcid.org/0000-0003-2895-6234)
- Gashirai K. Mbizvo (ORCID: https://orcid.org/0000-0002-9588-2944)
- Lynellen B. Gregory
- M. T. Anthony
- Mayer Josephine
Institutions
- University of Liverpool (GB)
- Walton Centre (GB)
- Liverpool John Moores University (GB)
- Aalborg University (DK)
Publication Details
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1136/jnnp-2024-abn.90
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.36