Initial validation of the new browser-based application DREEP for diagnosis of common chronic sleep disorders

• Published in: Somnologie : Schlafforschung und Schlafmedizin = Somnology : sleep research and sleep medicine 2024-03, Vol.28 (1), p.13-20
• Main Authors: Dietz-Terjung, Sarah, Eggert, Torsten, Judickiene, Julija, Hofherr, Georg, Schöbel, Christoph
• Format: Article
• Language: English
• Subjects: Abdomen; Body mass index; Cardiology; Insomnia; Internal Medicine; Medicine; Medicine & Public Health; Neurology; Original Studies; Otorhinolaryngology; Oxygen saturation; Pneumology/Respiratory System; Psychology; Questionnaires; Restless legs syndrome; Sleep apnea; Sleep deprivation; Sleep disorders
• ISSN: 1432-9123; 1439-054X
• DOI: 10.1007/s11818-024-00443-w

Background Traditionally, individuals with chronically disordered sleep are referred to a sleep specialist, who would usually arrange diagnostic investigations including polygraphy and/or polysomnography (PSG). Dr. Sleep (DREEP) is a browser-based application developed for diagnosing common chronic sleep disorders such as obstructive sleep apnea (OSA), periodic leg movements (PLMD), and insomnia in adults. The DREEP algorithm is based on disease-specific questions adapted from validated sleep questionnaires. This study evaluated the preliminary performance of DREEP for the diagnosis and severity assessment of sleep disorders in adults with chronically disordered sleep. Methods Sixty-four individuals admitted to the sleep laboratory of the Department of Sleep Medicine at the University of Essen, Germany, were recruited. Medical sleep history was taken by a sleep specialist. Each participant underwent full-night PSG and used the DREEP application on a tablet in the evening of admission or the morning after diagnostic sleep testing. Results DREEP predicted OSA with a sensitivity of 97%, but specificity was low at 25% (it had a tendency to overestimate OSA). DREEP had sensitivity of 79.2% and specificity of 80% for detecting PLMD/restless legs syndrome (RLS). The application showed the best performance for detection of insomnia (sensitivity 90%, specificity 83%), and successfully detected one individual with clinically confirmed narcolepsy. Conclusion This initial validation study has shown that the browser-based application DREEP is adequately able to assess risk and improve the pre-test probability for prescribing further tests in individuals with common chronic sleep disorders, including OSA, PLMD/RLS, and insomnia. In addition, DREEP was able to correctly identify most individuals without these conditions despite a tendency to overestimate. In a follow-up study, the promising clinical accuracy of DREEP needs to be substantiated by adding a healthy control group.