A pragmatic algorithm to select appropriate antiseizure medications in patients with epilepsy

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  • Ali A. Asadi-Pooya, Thomas Jefferson University, Shiraz University of Medical Sciences
  • ,
  • Sandor Beniczky
  • Guido Rubboli, Danish Epilepsy Centre, University of Copenhagen
  • ,
  • Michael R. Sperling, Thomas Jefferson University
  • ,
  • Stefan Rampp, University Hospitals Erlangen, University Hospital Halle
  • ,
  • Emilio Perucca, University of Pavia, Neurological Institute IRCCS Mondino, Pavia, Italy.

Objective Antiseizure medications (ASMs) are the first-line treatment for epilepsy. Many ASMs are available; this offers the opportunity to improve therapy by tailoring it to individual characteristics, but also increases the possibility of healthcare professionals making inappropriate treatment choices. To assist healthcare professionals, we developed a pragmatic algorithm aimed at facilitating medication selection for individuals whose epilepsy begins at age 10 years and older. Methods Utilizing available evidence and a Delphi panel-based consensus process, a group of epilepsy experts developed an algorithm for selection of ASMs, depending on the seizure type(s) and the presence of relevant clinical variables (age, gender, comorbidities, and comedications). The algorithm was implemented into a web-based application that was tested and improved in an iterative process. Results The algorithm categorizes ASMs deemed to be appropriate for each seizure type or combination of seizure types into three groups, with group 1 ASMs considered preferred, group 2 considered second line, and group 3 considered third line. Depending on the presence of relevant clinical variables, the ranking of individual ASMs is adjusted in the prioritization scheme to tailor recommendations to the characteristics of the individual. The algorithm is available on a web-based application at: #/. Significance The proposed algorithm is user-friendly, requires less than 2 minutes to complete, and provides the user with a range of appropriate treatment options from which to choose. This should facilitate its broad utilization and contribute to improve epilepsy management for healthcare providers who desire advice, particularly those who lack special expertise in the field.

Original languageEnglish
Pages (from-to)1668-1677
Number of pages10
Publication statusPublished - Aug 2020

    Research areas

  • algorithm, drug, epilepsy, seizure, treatment, ANTIEPILEPTIC DRUGS, DIAGNOSIS, SEIZURES, PEOPLE, ADULTS, APP

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