Web-based decision support system for patient-tailored selection of antiseizure medication in adolescents and adults An external validation study /

Antiseizure medications (ASMs) should be tailored to individual characteristics, including seizure type, age, sex, comorbidities, co-medications, drug allergies, and child-bearing potential. We previously developed a web-based algorithm for patient-tailored ASM selection to assist healthcare profess...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Hadady Levente
Klivényi Péter
Perucca Emilio
Rampp Stefan
Fabó Dániel
Bereczki Csaba
Rubboli Guido
Asadi-Pooya Ali A.
Sperling Michael R.
Beniczky Sándor
Dokumentumtípus: Cikk
Megjelent: 2022
Sorozat:EUROPEAN JOURNAL OF NEUROLOGY 29 No. 2
Tárgyszavak:
doi:10.1111/ene.15168

mtmt:32480235
Online Access:http://publicatio.bibl.u-szeged.hu/23741
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245 1 0 |a Web-based decision support system for patient-tailored selection of antiseizure medication in adolescents and adults  |h [elektronikus dokumentum] :  |b An external validation study /  |c  Hadady Levente 
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520 3 |a Antiseizure medications (ASMs) should be tailored to individual characteristics, including seizure type, age, sex, comorbidities, co-medications, drug allergies, and child-bearing potential. We previously developed a web-based algorithm for patient-tailored ASM selection to assist healthcare 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. Four hundred and twenty-five consecutive patients with newly diagnosed epilepsy were followed for at least one year after starting an ASM chosen by their physician. Patient characteristics were fed into the algorithm, blinded to the physician´s ASM choices and outcome. The algorithm recommended ASMs, ranked in hierarchical groups, with Group-1 ASMs labelled as best option for that patient. We evaluated retention rates, seizure-freedom rates and adverse effects leading to treatment discontinuation. Survival analysis contrasted outcomes between patients who received favored drugs and those who received lower ranked drugs. Propensity score matching corrected for possible imbalances between the groups. ASMs classified by the algorithm as best options had higher retention-rate (79.4% vs. 67.2%; p=0.005), higher seizure freedom rate (76.0% vs. 61.6%; p=0.002), and lower rate of discontinuation due to adverse effects (12.0% vs. 29.2%; p<0.001) than ASMs ranked less desirable by the algorithm. Use of the freely available decision-support system is associated with improved outcomes. This drug-selection application can provide valuable assistance to healthcare professionals prescribing medication for individuals with epilepsy. 
650 4 |a Klinikai orvostan 
700 0 1 |a Klivényi Péter  |e aut 
700 0 1 |a Perucca Emilio  |e aut 
700 0 1 |a Rampp Stefan  |e aut 
700 0 1 |a Fabó Dániel  |e aut 
700 0 1 |a Bereczki Csaba  |e aut 
700 0 1 |a Rubboli Guido  |e aut 
700 0 2 |a Asadi-Pooya Ali A.  |e aut 
700 0 2 |a Sperling Michael R.  |e aut 
700 0 2 |a Beniczky Sándor  |e aut 
856 4 0 |u http://publicatio.bibl.u-szeged.hu/23741/1/Hadady-Webbaseddecisionsupportsystemforpatienttailoredselectionofantiseizure.pdf  |z Dokumentum-elérés