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Diagnostic reference frames for seizures: A validation study
J F van Ast1, W O Renier, J L Talmon
1University of Maastricht, Research Institute Caphri, Department of Medical Informatics, 616, 6200 MD Maastricht, The Netherlands. w.vanast@mi.unimaas.nl
Introduction:
We developed structured descriptions of signs and symptoms for specific seizure types (called Diagnostic Reference Frames-DRFs-by us) that can serve as a frame of reference in the process of classifying patients with epileptic seizures. In this study the validity of the DRFs for clinical use is evaluated and described.
Material And Methods:
In this study we use a decision support system based on the DRFs and using Bayes's rule for the validation of the DRFs. Patient's manifestations are entered in the decision support system and by successively applying Bayes's rule posterior probabilities are calculated. The DRFs with the highest posterior probability gives an indication of the classification of the seizure. The validation of the DRFs was performed by comparing the seizure type with the highest posterior probability with the classification of experienced epileptologists on a series of test cases with known epileptic seizures. In this way we assessed the accuracy of the DRFs in classifying patients with epileptic seizures.
Results:
We included sixty-six patients in this efficacy study. The patients and/or their relatives described the manifestations occurring during a seizure. Sixty cases (91%) were correctly classified using the decision support system.
Discussion:
The accuracy of 91 % indicates that the knowledge encoded in the DRFs for the included seizure types is valid. The next step is to test the DRFs in a clinical setting to evaluate the applicability in daily practice.
