Seizure anticipation: from algorithms to clinical practice.
OBJECTIVE
Our understanding of the mechanisms that lead to the occurrence of epileptic seizures is rather incomplete. If it were possible to identify preictal precursors from the EEG of epilepsy patients, therapeutic possibilities could improve dramatically. Studies on seizure prediction have advanced from preliminary descriptions of preictal phenomena via proof of principle studies and controlled studies to studies on continuous multi-day recordings.


RESULTS
Following mostly promising early reports, recent years have witnessed a debate over the reproducibility of results and suitability of approaches. The current literature is inconclusive as to whether seizures are predictable by prospective algorithms. Prospective out-of-sample studies including a statistical validation are missing. Nevertheless, there are indications of a superior performance for approaches characterizing relations between different brain regions.


CONCLUSIONS
Prediction algorithms must be proven to perform better than a random predictor before prospective clinical trials involving seizure intervention techniques in patients can be justified.
Mormann
Florian
F
Department of Epileptology, University of Bonn, Sigmund-Freud-Strasse 25, 53105 Bonn, Germany. fmormann@yahoo.de
Elger
Christian E
CE
Lehnertz
Klaus
K
D000465:Algorithms; D000818:Animals; D002986:Clinical Trials as Topic / Q000379:methods*; D004569:Electroencephalography; D006801:Humans; D011237:Predictive Value of Tests; D012640:Seizures / Q000503:physiopathology* / Q000628:therapy*