The Berlin questionnaire (BQ) has been used to help identify patients at high risk of having sleep apnea in primary care and atrial fibrillation patients. The BQ may be a useful adjunct in sleep medicine and research, but it has never been validated in a sleep clinic population. The aim of the study is to determine the specificity and sensitivity of the BQ compared to the respiratory disturbance index (RDI) values obtained from two nights of polysomnographic recording in a sleep clinic population. This is a retrospective chart review study of 130 sleep clinic patients. Patients' demographics, BQ scores, RDI measurements, and sleep study parameters were extracted from the patients' chart. Of the 130 charts reviewed, the BQ identified 76 (58.5%) as being at high-risk of having sleep apnea, but overnight polysomnography found only 34 of the 130 patients (26.2%) had an RDI > 10. The BQ performed with 0.62 sensitivity and 0.43 specificity at the RDI > 10 level. Due to the low sensitivity and specificity as well as the large number of false negatives and positives, the Berlin questionnaire is not an appropriate instrument for identifying patients with sleep apnea in a sleep clinic population.

Utilizing a large patient population, this study supports the significant night-to-night variability in PSG respiratory variables. Identification of sleep apnea in some patients is reduced when sleep experts are provided with only one PSG recording. The clinical implication is that about 13% of sleep clinic patients might benefit from a second night of PSG.

Epilepsy and psychogenic non-epileptic seizures (PNES) often show over-lap in symptoms, especially at an early disease stage. During a PNES, the electrical activity of the brain remains normal but in case of an epileptic seizure the brain will show epileptiform discharges on the electroencephalogram (EEG). In many cases an accurate diagnosis can only be achieved after a long-term video monitoring combined with EEG recording which is quite expensive and time-consuming. In this paper using short-term EEG data, the classification of epilepsy and PNES subjects is analyzed based on signal, functional network and EEG microstate features. Our results showed that the beta-band is the most useful EEG frequency sub-band as it performs best for classifying subjects. Also the results depicted that when the coverage feature of the EEG microstate analysis is calculated in beta-band, the classification shows fairly high accuracy and precision. Hence, the beta-band and the coverage are the most important features for classification of epilepsy and PNES patients.

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DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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