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Ikelos-RWA. Validation of an Automatic Tool to Quantify REM Sleep Without Atonia.
Papakonstantinou, Alexandra; Klemming, Jannis; Haberecht, Martin; Kunz, Dieter; Bes, Frederik.
Afiliación
  • Papakonstantinou A; Sleep Research & Clinical Chronobiology, Institute of Physiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freien Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
  • Klemming J; Clinic for Sleep- and Chronomedicine, St. Hedwig-Krankenhaus, Berlin, Germany.
  • Haberecht M; Department of Ophthalmology, University Medical Center Goettingen, Göttingen, Germany.
  • Kunz D; Clinic for Sleep- and Chronomedicine, St. Hedwig-Krankenhaus, Berlin, Germany.
  • Bes F; Sleep Research & Clinical Chronobiology, Institute of Physiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freien Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
Clin EEG Neurosci ; : 15500594231175320, 2023 May 16.
Article en En | MEDLINE | ID: mdl-37192675
ABSTRACT
Study Objectives. To present and evaluate an automatic scoring algorithm for quantification of REM-sleep without atonia (RWA) in patients with REM-sleep behaviour disorder (RBD) based on a generally accepted, well-validated visual scoring method, ("Montreal" phasic and tonic) and a recently developed, concise scoring method (Ikelos-RWA). Methods. Video-polysomnographies of 20 RBD patients (68.2 ± 7.2 years) and 20 control patients with periodic limb movement disorder (65.9 ± 6.7 years) were retrospectively analysed. RWA was estimated from chin electromyogram during REM-sleep. Visual and automated RWA scorings were correlated, and agreement (a) and Cohen's Kappa (k) calculated for 1735 minutes of REM-sleep of the RBD patients. Discrimination performance was evaluated with receiver operating characteristic (ROC) analysis. The algorithm was then applied on the polysomnographies of a cohort of 232 RBD patients (total analysed REM-sleep 17,219 minutes) and evaluated, while correlating the different output parameters. Results. Visual and computer-derived RWA scorings correlated significantly (tonic Montreal rTM = 0.77; phasic Montreal rPM = 0.78; Ikelos-RWA rI = 0.97; all p < 0.001) and showed good to excellent Kappa coefficients (kTM = 0.71; kPM = 0.79; kI = 0.77). The ROC analysis showed high sensitivities (95%-100%) and specificities (84%-95%) at the optimal operation points, with area under the curve (AUC) of 0.98, indicating high discriminating capacity. The automatic RWA scorings of 232 patients correlated significantly (rTM{I} = 0.95; rPM{I} = 0.91, p < 0.0001). Conclusions. The presented algorithm is an easy-to-use and valid tool for automatic RWA scoring in patients with RBD and may prove effective for general use being publicly available.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Clin EEG Neurosci Asunto de la revista: CEREBRO / NEUROLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Clin EEG Neurosci Asunto de la revista: CEREBRO / NEUROLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Alemania