Roberto Hornero1, Leila Kheirandish-Gozal2, Gonzalo C Gutiérrez-Tobal1, Mona F Philby2, María Luz Alonso-Álvarez3, Daniel Álvarez1,4, Ehab A Dayyat5, Zhifei Xu6, Yu-Shu Huang7, Maximiliano Tamae Kakazu8, Albert M Li9, Annelies Van Eyck10,11, Pablo E Brockmann12, Zarmina Ehsan13, Narong Simakajornboon13, Athanasios G Kaditis14, Fernando Vaquerizo-Villar1, Andrea Crespo Sedano4, Oscar Sans Capdevila15, Magnus von Lukowicz16, Joaquín Terán-Santos3, Félix Del Campo1,4, Christian F Poets16, Rosario Ferreira17, Katalina Bertran15, Yamei Zhang6, John Schuen8, Stijn Verhulst10,11, David Gozal2. 1. 1 Biomedical Engineering Group, University of Valladolid, Valladolid, Spain. 2. 2 Section of Sleep Medicine, Department of Pediatrics, Pritzker School of Medicine, Biological Sciences Division, University of Chicago, Chicago, Illinois. 3. 3 Unidad Multidisciplinar del Sueño, Centro de Investigación Biomédica en Red Respiratorio, Hospital Universitario de Burgos, Burgos, Spain. 4. 4 Sleep-Ventilation Unit, Pneumology Service, Río Hortega University Hospital, Valladolid, Spain. 5. 5 Division of Child Neurology, Department of Pediatrics, LeBonheur Children's Hospital, University of Tennessee Health Science Center, School of Medicine, Memphis, Tennessee. 6. 6 Sleep Unit, Beijing Children's Hospital, Capital Medical University, Beijing, People's Republic of China. 7. 7 Department of Child Psychiatry and Sleep Center, Chang Gung Memorial Hospital and University, Taoyuan, Taiwan. 8. 8 Spectrum Health, Michigan State University, Grand Rapids, Michigan. 9. 9 Department of Pediatrics, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong, China. 10. 10 Laboratory of Experimental Medicine and Pediatrics and. 11. 11 Department of Pediatrics, University of Antwerp and Antwerp University Hospital, Antwerp, Belgium. 12. 12 Sleep Medicine Center, Department of Pediatric Cardiology and Pulmonology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile. 13. 13 Division of Pulmonary and Sleep Medicine, Cincinnati Children's Medical Center, Cincinnati, Ohio. 14. 14 Pediatric Pulmonology Unit, Sleep Disorders Laboratory, First Department of Pediatrics, National and Kapodistrian University of Athens School of Medicine and Aghia Sophia Children's Hospital, Athens, Greece. 15. 15 Sleep Unit, Department of Neurology, Sant Joan de Deu, Barcelona Children's Hospital, Barcelona, Spain. 16. 16 Department of Neonatology and Sleep Unit, University of Tubingen, Tubingen, Germany; and. 17. 17 Pediatric Respiratory Unit, Department of Pediatrics, Hospital de Santa Maria, Academic Medical Center of Lisbon, Lisbon, Portugal.
Abstract
RATIONALE: The vast majority of children around the world undergoing adenotonsillectomy for obstructive sleep apnea-hypopnea syndrome (OSA) are not objectively diagnosed by nocturnal polysomnography because of access availability and cost issues. Automated analysis of nocturnal oximetry (nSpO2), which is readily and globally available, could potentially provide a reliable and convenient diagnostic approach for pediatric OSA. METHODS: Deidentified nSpO2 recordings from a total of 4,191 children originating from 13 pediatric sleep laboratories around the world were prospectively evaluated after developing and validating an automated neural network algorithm using an initial set of single-channel nSpO2 recordings from 589 patients referred for suspected OSA. MEASUREMENTS AND MAIN RESULTS: The automatically estimated apnea-hypopnea index (AHI) showed high agreement with AHI from conventional polysomnography (intraclass correlation coefficient, 0.785) when tested in 3,602 additional subjects. Further assessment on the widely used AHI cutoff points of 1, 5, and 10 events/h revealed an incremental diagnostic ability (75.2, 81.7, and 90.2% accuracy; 0.788, 0.854, and 0.913 area under the receiver operating characteristic curve, respectively). CONCLUSIONS: Neural network-based automated analyses of nSpO2 recordings provide accurate identification of OSA severity among habitually snoring children with a high pretest probability of OSA. Thus, nocturnal oximetry may enable a simple and effective diagnostic alternative to nocturnal polysomnography, leading to more timely interventions and potentially improved outcomes.
RATIONALE: The vast majority of children around the world undergoing adenotonsillectomy for obstructive sleep apnea-hypopnea syndrome (OSA) are not objectively diagnosed by nocturnal polysomnography because of access availability and cost issues. Automated analysis of nocturnal oximetry (nSpO2), which is readily and globally available, could potentially provide a reliable and convenient diagnostic approach for pediatric OSA. METHODS: Deidentified nSpO2 recordings from a total of 4,191 children originating from 13 pediatric sleep laboratories around the world were prospectively evaluated after developing and validating an automated neural network algorithm using an initial set of single-channel nSpO2 recordings from 589 patients referred for suspected OSA. MEASUREMENTS AND MAIN RESULTS: The automatically estimated apnea-hypopnea index (AHI) showed high agreement with AHI from conventional polysomnography (intraclass correlation coefficient, 0.785) when tested in 3,602 additional subjects. Further assessment on the widely used AHI cutoff points of 1, 5, and 10 events/h revealed an incremental diagnostic ability (75.2, 81.7, and 90.2% accuracy; 0.788, 0.854, and 0.913 area under the receiver operating characteristic curve, respectively). CONCLUSIONS: Neural network-based automated analyses of nSpO2 recordings provide accurate identification of OSA severity among habitually snoring children with a high pretest probability of OSA. Thus, nocturnal oximetry may enable a simple and effective diagnostic alternative to nocturnal polysomnography, leading to more timely interventions and potentially improved outcomes.
Authors: Carole L Marcus; Lee Jay Brooks; Kari A Draper; David Gozal; Ann Carol Halbower; Jacqueline Jones; Michael S Schechter; Sally Davidson Ward; Stephen Howard Sheldon; Richard N Shiffman; Christopher Lehmann; Karen Spruyt Journal: Pediatrics Date: 2012-08-27 Impact factor: 7.124
Authors: Scott J Hunter; David Gozal; Dale L Smith; Mona F Philby; Jaeson Kaylegian; Leila Kheirandish-Gozal Journal: Am J Respir Crit Care Med Date: 2016-09-15 Impact factor: 21.405
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
Authors: Daniel Álvarez; Gonzalo C Gutiérrez-Tobal; Fernando Vaquerizo-Villar; Fernando Moreno; Félix Del Campo; Roberto Hornero Journal: Adv Exp Med Biol Date: 2022 Impact factor: 3.650
Authors: Gonzalo C Gutiérrez-Tobal; Daniel Álvarez; Fernando Vaquerizo-Villar; Verónica Barroso-García; Javier Gómez-Pilar; Félix Del Campo; Roberto Hornero Journal: Adv Exp Med Biol Date: 2022 Impact factor: 3.650
Authors: Cathy A Goldstein; Richard B Berry; David T Kent; David A Kristo; Azizi A Seixas; Susan Redline; M Brandon Westover Journal: J Clin Sleep Med Date: 2020-04-15 Impact factor: 4.062
Authors: Andrea Crespo; Daniel Álvarez; Leila Kheirandish-Gozal; Gonzalo C Gutiérrez-Tobal; Ana Cerezo-Hernández; David Gozal; Roberto Hornero; Félix Del Campo Journal: Sleep Breath Date: 2018-02-16 Impact factor: 2.816