Jorge Abad1,2,3, Aida Muñoz-Ferrer1,2, Miguel Ángel Cervantes4,5, Cristina Esquinas3,6, Alicia Marin1,2,3, Carlos Martínez1,2,3, Josep Morera1, Juan Ruiz1,2,3. 1. Department of Respiratory Medicine, Hospital Universitari Germans Trias i Pujol, Badalona, Spain. 2. Universitat Autònoma de Barcelona (UAB), Department of Medicine. Barcelona, Spain. 3. Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain. 4. Universitat Politécnica de Catalunya (UPC), Barcelona, Spain. 5. Smart Vision Technologies, S.L, Barcelona, Spain. 6. Pneumology Department, University Hospital Vall d'Hebron. Barcelona, Spain.
Abstract
STUDY OBJECTIVES: We investigated the diagnostic accuracy for the identification of obstructive sleep apnea (OSA) and its severity of a noninvasive technology based on image processing (SleepWise). METHODS: This is an observational, prospective study to evaluate the degree of agreement between polysomnography (PSG) and SleepWise. We recruited 56 consecutive subjects with suspected OSA who were referred as outpatients to the Sleep Unit of the Hospital Universitari Germans Trias i Pujol (HUGTiP) from January 2013 to January 2014. All patients underwent laboratory PSG and image processing with SleepWise simultaneously the same night. Both PSG and SleepWise analyses were carried independently and blindly. RESULTS: We analyzed 50 of the 56 patients recruited. OSA was diagnosed through PSG in a total of 44 patients (88%) with a median apnea-hypopnea index (AHI) of 25.35 (24.9). According to SleepWise, 45 patients (90%) met the criteria for a diagnosis of OSA, with a median AHI of 22.8 (22.03). An analysis of the ability of PSG and SleepWise to classify patients by severity on the basis of their AHI shows that the two diagnostic systems distribute the different groups similarly. According to PSG, 23 patients (46%) had a diagnosis of severe OSA, 11 patients (22%) moderate OSA, and 10 patients (20%) mild OSA. According to SleepWise, 20, 13, and 12 patients (40%, 26%, and 24%, respectively) had a diagnosis of severe, moderate, and mild OSA respectively. For OSA diagnosis, SleepWise was found to have sensitivity of 100% and specificity of 83% in relation to PSG. The positive predictive value was 97% and the negative predictive value was 100%. The Bland-Altman plot comparing the mean AHI values obtained through PSG and SleepWise shows very good agreement between the two diagnostic techniques, with a bias of -3.85, a standard error of 12.18, and a confidence interval of -0.39 to -7.31. CONCLUSIONS: SleepWise was reasonably accurate for noninvasive and automatic diagnosis of OSA in outpatients. SleepWise determined the severity of OSA with high reliability. The current study including simultaneous laboratory PSG and SleepWise processing image is proposed as a reasonable validation standard.
STUDY OBJECTIVES: We investigated the diagnostic accuracy for the identification of obstructive sleep apnea (OSA) and its severity of a noninvasive technology based on image processing (SleepWise). METHODS: This is an observational, prospective study to evaluate the degree of agreement between polysomnography (PSG) and SleepWise. We recruited 56 consecutive subjects with suspected OSA who were referred as outpatients to the Sleep Unit of the Hospital Universitari Germans Trias i Pujol (HUGTiP) from January 2013 to January 2014. All patients underwent laboratory PSG and image processing with SleepWise simultaneously the same night. Both PSG and SleepWise analyses were carried independently and blindly. RESULTS: We analyzed 50 of the 56 patients recruited. OSA was diagnosed through PSG in a total of 44 patients (88%) with a median apnea-hypopnea index (AHI) of 25.35 (24.9). According to SleepWise, 45 patients (90%) met the criteria for a diagnosis of OSA, with a median AHI of 22.8 (22.03). An analysis of the ability of PSG and SleepWise to classify patients by severity on the basis of their AHI shows that the two diagnostic systems distribute the different groups similarly. According to PSG, 23 patients (46%) had a diagnosis of severe OSA, 11 patients (22%) moderate OSA, and 10 patients (20%) mild OSA. According to SleepWise, 20, 13, and 12 patients (40%, 26%, and 24%, respectively) had a diagnosis of severe, moderate, and mild OSA respectively. For OSA diagnosis, SleepWise was found to have sensitivity of 100% and specificity of 83% in relation to PSG. The positive predictive value was 97% and the negative predictive value was 100%. The Bland-Altman plot comparing the mean AHI values obtained through PSG and SleepWise shows very good agreement between the two diagnostic techniques, with a bias of -3.85, a standard error of 12.18, and a confidence interval of -0.39 to -7.31. CONCLUSIONS: SleepWise was reasonably accurate for noninvasive and automatic diagnosis of OSA in outpatients. SleepWise determined the severity of OSA with high reliability. The current study including simultaneous laboratory PSG and SleepWise processing image is proposed as a reasonable validation standard.
Authors: A Roebuck; V Monasterio; E Gederi; M Osipov; J Behar; A Malhotra; T Penzel; G D Clifford Journal: Physiol Meas Date: 2013-12-17 Impact factor: 2.833
Authors: Clete A Kushida; Michael R Littner; Timothy Morgenthaler; Cathy A Alessi; Dennis Bailey; Jack Coleman; Leah Friedman; Max Hirshkowitz; Sheldon Kapen; Milton Kramer; Teofilo Lee-Chiong; Daniel L Loube; Judith Owens; Jeffrey P Pancer; Merrill Wise Journal: Sleep Date: 2005-04 Impact factor: 5.849
Authors: Nancy A Collop; W McDowell Anderson; Brian Boehlecke; David Claman; Rochelle Goldberg; Daniel J Gottlieb; David Hudgel; Michael Sateia; Richard Schwab Journal: J Clin Sleep Med Date: 2007-12-15 Impact factor: 4.062