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dc.contributor.author | Álvarez González, Daniel | |
dc.contributor.author | Alonso Álvarez, María Luz | |
dc.contributor.author | Gutiérrez Tobal, Gonzalo César | |
dc.contributor.author | Crespo Senado, Andrea | |
dc.contributor.author | Keirandish-Gozal, Leila | |
dc.contributor.author | Hornero Sánchez, Roberto | |
dc.contributor.author | Gozal, David | |
dc.contributor.author | Terán Santos, Joaquín | |
dc.contributor.author | Campo Matias, Félix del | |
dc.date.accessioned | 2017-08-30T10:33:50Z | |
dc.date.available | 2017-08-30T10:33:50Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Journal of Clinical Sleep Medicine, Mayo 2017, vol. 13, n. 5, p. 693-702 | es |
dc.identifier.uri | http://uvadoc.uva.es/handle/10324/25280 | |
dc.description | Producción Científica | es |
dc.description.abstract | Study Objectives: Nocturnal oximetry has emerged as a simple, readily available, and potentially useful diagnostic tool of childhood obstructive sleep apnea-hypopnea syndrome (OSAHS). However, at-home respiratory polygraphy (HRP) remains the preferred alternative to polysomnography (PSG) in unattended settings. The aim of this study was two-fold: (1) to design and assess a novel methodology for pediatric OSAHS screening based on automated analysis of at-home oxyhemoglobin saturation (SpO2), and (2) to compare its diagnostic performance with HRP. Methods: SpO2 recordings were parameterized by means of time, frequency, and conventional oximetric measures. Logistic regression (LR) models were optimized using genetic algorithms (GAs) for 3 cutoffs for OSAHS: 1, 3, and 5 events per hour (e/h). The diagnostic performance of LR models, manual obstructive apnea-hypopnea index (OAHI) from HRP, and the conventional oxygen desaturation index ≥3% (ODI3) were assessed. Results: For a cutoff of 1 e/h, the optimal LR model significantly outperformed both conventional HRP-derived ODI3 and OAHI: 85.5% Accuracy (HRP 74.6%; ODI3 65.9%) and 0.97 AUC (HRP 0.78; ODI3 0.75) were reached. For a cutoff of 3 e/h, the LR model achieved 83.4% Accuracy (HRP 85.0%; ODI3 74.5%) and 0.96 AUC (HRP 0.93; ODI3 0.85) whereas using a cutoff of 5 e/h, oximetry reached 82.8% Accuracy (HRP 85.1%; ODI3 76.7) and 0.97 AUC (HRP 0.95; ODI3 0.84). Conclusions: Automated analysis of at-home SpO2 recordings provide accurate detection of children with high pre-test probability of OSAHS. Thus, unsupervised nocturnal oximetry may enable a simple and effective alternative to HRP and PSG in unattended settings. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | eng | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.title | Automated screening of children with obstructive sleep apnea using nocturnal oximetry: An alternative to respiratory polygraphy in unattended settings | es |
dc.type | info:eu-repo/semantics/article | es |
dc.identifier.doi | 10.5664/jcsm.6586 | es |
dc.peerreviewed | SI | es |
dc.description.project | This research has been partially supported by the project 153/2015 of the Sociedad Española de Neumología y Cirugía Torácica (SEPAR), the project RTC-2015-3446-1 from the Ministerio de Economía y Competitividad and the European Regional Development Fund (FEDER), and the project VA037U16 from the Consejería de Educación de la Junta de Castilla y León and FEDER. L. Kheirandish-Gozal is supported by NIH grant 1R01HL130984-01. D. Álvarez was in receipt of a Juan de la Cierva grant from the Ministerio de Economía y Competitividad. | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International |
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