Congratulations to Martin Prener for being granted a 1-year introduction stipend from the Research Council at Rigshospitalet for the project 'Choosing the Right Medication for Epilepsy: Extracting Information from Electronic Patient Records and Registries Using Artificial Intelligence'.

Objective of Martin's 1-year project:
The objective is to utilise text mining of electronic health records (EHR) from the Capital Region and Region Zealand, in combination with registry data from the period 2010 to 2024, to generate a retrospective cohort of approximately 25.000 newly diagnosed epilepsy patients followed for at least three years after prescription of the first antiseizure medication (ASM). We aim to address the following research questions regarding the use of ASM:

  1. How many newly diagnosed patients became seizure-free on monotherapy ASM over a period of 3 years, and how many patients did not achieve sustained seizure freedom despite multiple ASMs in monotherapy or polytherapy?
  2. Which first-line ASMs in monotherapy were associated with the highest occurrence of seizure freedom, and what were the outcomes of second-line (and third-line) ASMs if the first-line failed? What side effects led to switching ASM? Additionally, what was the effect of variables such as existing co-morbidity, other medications, sex, age, and epilepsy etiology?
  3. What is the outcome in terms of seizure freedom and side effects of using ASM in polytherapy compared to the use of first- and second-line ASMs in monotherapy? What is the outcome of using two-, three, four and five ASMs in combination?