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Validation Study of Airgo, an Innovative Device to Screen Sleep Respiratory Disorders

BACKGROUND: Obstructive sleep apnea affects a consistent percentage of the population, and only a minority of patients have been diagnosed and treated because of a discrepancy between resources available for diagnosis and the epidemiology of a disorder possibly affecting nearly one billion people in...

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Detalles Bibliográficos
Autores principales: Braghiroli, Alberto, Kuller, David, Godio, Massimo, Rossato, Fabio, Sacco, Carlo, Morrone, Elisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283899/
https://www.ncbi.nlm.nih.gov/pubmed/35847776
http://dx.doi.org/10.3389/fmed.2022.938542
Descripción
Sumario:BACKGROUND: Obstructive sleep apnea affects a consistent percentage of the population, and only a minority of patients have been diagnosed and treated because of a discrepancy between resources available for diagnosis and the epidemiology of a disorder possibly affecting nearly one billion people in the world. AIM: We conducted a study to compare a standard home respiratory monitoring system (Nox T3) with a novel device (Airgo™) consisting of an elastic band and a small recorder, light, comfortable for the patient, and low-cost complete with automatic analysis of the data that produces a screening report indicating the type and severity of sleep respiratory disorder. PATIENTS AND RESULTS: We examined 120 patients, reduced to 118 for technical problems. The mean (SD) age of the patients is 55.7 ± 13 years, their BMI is 27.8 ± 4.3 kg/m(2), and their AHI is 22 ± 22 events/h. Patients belong to all the different severity rates of OSA, with a percentage of them classified as free of respiratory disorders. The Airgo™ showed excellent agreement with the results of the gold standard, reporting high levels of sensitivity, specificity, positive and negative predicted value, and accuracy. CONCLUSION: Airgo™ is a reliable tool to screen patients with suspected sleep respiratory disorders, well tolerated by the patient based on totally automatic analysis and reporting system, leading to more efficient use of doctor’s and clinician’s time and resources and extending the opportunity to diagnose more possible candidates for treatment.