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Updated: Sep 26, 2026

Drug-Induced Sleep Endoscopy (DISE) with Target Controlled Infusion (TCI) and Bispectral Analysis in Obstructive Sleep Apnea
Published on: December 6, 2016
[Diagnosis of sleep disorders and medical sleep-related diseases--a review]
1Klinik für Innere Medizin, Schwerpunkt Pneumologie, Schlafmedizinisches Labor, Klinikum, Philipps-Universität Marburg. penzel@med.uni-marburg.de
Abstract:
A person's well-being and health are greatly affected by disorders of sleep and wakefulness. It is of the utmost importance to diagnose and treat such conditions, since the associated daytime sleepiness is a major risk factor for accidents. Early establishment of the correct diagnosis paves the way to achieving an excellent therapeutic outcome. Health-economic requirements of appropriateness and necessity mandate the specific use of cost- and time-intensive examinations in the sleep laboratory. In accordance with the guidelines for "non-restorative sleep", severe and chronic sleep disorders can be diagnosed outside the sleep lab if the underlying cause can already be identified on the basis of the patient's history. Such is usually the case in sleep disorders caused by external influences, disturbed circadian rhythm or pre-existing neurological, psychiatric or internal disorders. Standardized questionnaires are used to record and evaluate the patient's complaints, and vigilance testing to assess impaired sustained attention during the day. Excessive daytime sleepiness is quantified by the multiple sleep latency test (MSLT). In the case of some disorders such as apnoea, or periodic leg movements, simplified ambulatory methods have been developed to enable their detection at an early stage. The gold standard for the diagnosis of sleep disorders in the sleep lab is cardiorespiratory polysomnography. The relevant biosignals for the assessment of sleep, respiration, heart function, the cardiovascular system and movement are well established. Some of the sensors employed need further improvement. Numerous methods for signal analysis are still undergoing development, and currently available automatic evaluation systems are not yet reliable enough to obviate the need for manual interpretation.
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