Post-Stroke Seizure Predictive Models, SeLECT Model: Carolina Ferreira Atuesta, MD, MSc
The scientific researcher and clinical manager, Icahn School of Medicine at Mount Sinai, spoke about the clinical models used to predict seizures in poststroke patients. [WATCH TIME: 4 minutes]
WATCH TIME: 4 minutes
“In order for these trials to be effective, we need to have patients that eventually will develop seizures. We need to find those participants who are high risk.”
Identifying poststroke patients at risk for seizures is important for providing potential seizure control therapies before seizures occur. Predicting the risk of seizures in this patient population can be made through the use of clinical models such as the SeLECT model.
In a prior systematic review, the SeLECT model from Switzerland was externally validated in Italian, German, and Austrian cohort studies, with c-statistics ranged from 0.69 to 0.81. The review explored 7 articles from major databases (PubMed, SCOPUS, and Cochrane Library) on the impact of models to predict late-onset seizures. It was also the only model developed in line with proposed guidelines and was externally validated in a homogeneous population to predict late seizure onset among stroke survivors.
At the 2022 American Epilepsy Society Annual Meeting, held December 2 to 6, in Nashville, Tennessee, Carolina Ferreira Atuesta, MD, MSc, sat down for an interview with NeurologyLive®. Atuesta, scientific researcher and clinical manager, Icahn School of Medicine at Mount Sinai, spoke on identifying poststroke patients who are at high risk for seizures and including them in trials for future drug development. She explained how clinical models, such as the SeLECT model, are used for determining the probability of whether seizures may occur. Atuesta further described the prognostic ability of the model using prior research conducted in both high risk and low risk poststroke patients.
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