Nocturnal oximetry-based evaluation of habitually snoring children
Autor: | Gonzalo C. Gutiérrez-Tobal, Christian F. Poets, Yamei Zhang, John Schuen, Roberto Hornero, Athanasios G. Kaditis, Annelies Van Eyck, Oscar Sans Capdevila, Daniel Álvarez, Rosario Ferreira, Ehab Dayyat, Félix del Campo, Zhifei Xu, Andrea Crespo Sedano, Katalina Bertran, Joaquín Terán-Santos, Leila Kheirandish-Gozal, Narong Simakajornboon, Yu-Shu Huang, Mona F. Philby, Magnus von Lukowicz, Pablo E. Brockmann, David Gozal, María Luz Alonso-Álvarez, Maximiliano Tamae Kakazu, Fernando Vaquerizo-Villar, Albert M. Li, Zarmina Ehsan, Stijn Verhulst |
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Přispěvatelé: | Repositório da Universidade de Lisboa |
Jazyk: | angličtina |
Rok vydání: | 2017 |
Předmět: |
Pulmonary and Respiratory Medicine
Male medicine.medical_specialty childhood obstructive sleep apnea–hypopnea syndrome Adolescent Intraclass correlation automated pattern recognition blood oxygen saturation Polysomnography Nocturnal Critical Care and Intensive Care Medicine Severity of Illness Index 03 medical and health sciences 0302 clinical medicine stomatognathic system Surveys and Questionnaires medicine Humans Blood oxygen saturation Oximetry Prospective Studies nocturnal oximetry Child neural network Sleep Apnea Obstructive medicine.diagnostic_test Nocturnal polysomnography business.industry Snoring Editorials Reproducibility of Results Automated pattern recognition Neural network nervous system diseases respiratory tract diseases 030228 respiratory system Nocturnal oximetry Childhood obstructive sleep apnea-hypopnea syndrome Child Preschool Physical therapy Female Human medicine business 030217 neurology & neurosurgery Algorithms |
Zdroj: | UVaDOC. Repositorio Documental de la Universidad de Valladolid instname American journal of respiratory and critical care medicine AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE r-FSJD: Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu Fundació Sant Joan de Déu r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu |
ISSN: | 1073-449X |
Popis: | Copyright © 2017 by the American Thoracic Society 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. |
Databáze: | OpenAIRE |
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