Biomedical subjects

J F van Ast

Publications and source records attributed to J F van Ast.

6 recordsLinked to original sources

PubMed2005

Diagnostic reference frames for seizures: A validation study.

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.

Adolescent↗

PubMed2004

An approach to knowledge base construction based on expert opinions.

OBJECTIVES: To describe, validate and demonstrate an approach for knowledge base construction based on expert opinions. METHODS: A knowledge base containing the frequency of occurrence of manifestations in epileptic seizures is constructed based on information provided by neurologists/epileptologists. The reliability of the responses is determined with the inter-rater intraclass correlation coefficient (ICC). If the ICC is not large enough the Spearman-Brown prophecy formula can be used to predict the number of additional experts. We propose a method to assess whether an additional expert provides information consistent with the already acquired data as well as a method to detect experts with deviating opinions. The power of the first method was determined. RESULTS: Data were collected for five seizure types. The ICCs determined from the responses for the various seizure types after inclusion of the additional experts was in all cases almost equal to 0.9, the target value. Yet one expert with diverging opinions concerning the frequency of occurrence of manifestations for different seizure types could be identified. Excluding this participant improved the reliability of the data. The power of the methods was good (> or =0.75). CONCLUSIONS: It is shown that human experts can provide reliable information about the frequency of occurrence of manifestations in epileptic seizures. In addition, the described approach correctly identified neurologists/epileptologists with both consistent and diverging opinions about the frequency of occurrence of manifestations in a number of seizure types.

Artificial Intelligence↗

PubMed2003

Development of diagnostic reference frames for seizures. Part 1: inter-participant agreement in the selection of symptoms.

OBJECTIVE: Our aim is to develop reliable descriptions of various seizure types, which will be used as a basis for decision support. We use expert opinions in this process. In this contribution we evaluate the inter-participant agreement in the selection of frequently occurring symptoms for the description of seizure types. METHOD: We compared the actual agreement among participants with the agreement that would result from random symptom selection as well as with the maximal agreement attainable. For each seizure type we calculated the reliability coefficients of the responses. RESULTS: For all seizure types we found that the agreement in symptom selection among the participants is significantly higher than expected by chance, but not reaching the maximum agreement attainable. The reliability coefficients varied between 0.56 and 0.74 for the various seizure types. CONCLUSION: Although the participants do not reach the maximum agreement attainable in the selection of symptoms, the majority agreement on characteristic frequently occurring symptoms for the different seizure types does approach the maximum agreement attainable. Therefore, we conclude that expert opinions can be used for building descriptions of seizure types. However, to derive a reliable set of symptoms for the construction of the diagnostic reference frames (DRFs) more participants are needed.

Decision Making, Computer-Assisted↗

PubMed2003

Development of diagnostic reference frames for seizures. Part 2: are seizure descriptions discriminative?

OBJECTIVE: To determine whether the seizure descriptions given by a group of neurologists/epileptologists are discriminative. METHOD: We constructed templates for various seizure types describing how often symptoms were selected by the participants. We defined a matching score to indicate the match between such a template and the symptoms selected by each neurologist/epileptologist individually and computed the scores for each of the sets of selected symptoms with all templates. Correlation coefficients were calculated between the templates. RESULTS: Data were collected from 24 participants. The matching scores and the correlation coefficients both show that participants provide discriminative descriptions of the seizure types. Descriptions of aggregated seizure types, such as primary generalized seizures, are less discriminatory than the descriptions of more specific seizure types. CONCLUSION: We concluded that the participants in our study selected symptoms that result in discriminative descriptions of the seizure types. This indicates that knowledge elicitation by using the opinions of a group of clinical experts is possible. The study also indicates that the design of the study could be ameliorated in several ways. These findings will be taken into account when designing the final study.

Decision Making, Computer-Assisted↗

PubMed2003

How many neurologists/epileptologists are needed to provide reliable descriptions of seizure types?

We are developing seizure descriptions as a basis for decision support. Based on an existing dataset we used the Spearman-Brown prophecy formula to estimate how many neurologist/epileptologists are needed to obtain reliable seizure descriptions (rho = 0.9). By extending the number of participants to the required level we found that the number of participants needed to obtain a reliability coefficient of 0.9 were in accordance with the number of participants determined from the Spearman-Brown prophecy formula. Systematic differences between the participants were minor and not statistically significant.

Clinical Competence↗

PubMed2002

Inter-participant agreement in the selection of symptoms for the description of seizures.

PURPOSE: To evaluate the inter-participant agreement in the selection of symptoms for the description of seizure types. METHODS: We evaluated the inter-participant agreement for a number of seizure types by comparing the actual agreement to the agreement that would result from random symptom selection as well as the maximal attainable agreement among participants that selected a different number of symptoms. RESULTS: For all seizure types the agreement in the symptom selection among the majority of the participants is significantly higher than expected by chance, but not reaching the maximum agreement attainable. CONCLUSION: Although the maximum agreement possible is not obtained, the symptoms selected by a majority of the participants seem to be adequate for the description of seizure types.

Humans↗