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Web‐based decision support system for patient‐tailored selection of antiseizure medication in adolescents and adults: An external validation study
Author(s) -
Hadady Levente,
Klivényi Péter,
Perucca Emilio,
Rampp Stefan,
Fabó Dániel,
Bereczki Csaba,
Rubboli Guido,
AsadiPooya Ali A.,
Sperling Michael R.,
Beniczky Sándor
Publication year - 2022
Publication title -
european journal of neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.881
H-Index - 124
eISSN - 1468-1331
pISSN - 1351-5101
DOI - 10.1111/ene.15168
Subject(s) - medicine , discontinuation , clinical decision support system , adverse effect , propensity score matching , decision support system , physical therapy , data mining , computer science
Antiseizure medications (ASMs) should be tailored to individual characteristics, including seizure type, age, sex, comorbidities, comedications, drug allergies, and childbearing potential. We previously developed a web-based algorithm for patient-tailored ASM selection to assist health care professionals in prescribing medication using a decision support application (https://epipick.org). In this validation study, we used an independent dataset to assess whether ASMs recommended by the algorithm are associated with better outcomes than ASMs considered less desirable by the algorithm.