RT info:eu-repo/semantics/article
T1 Multiscale entropy analysis of unattended oximetric recordings to assist in the screening of paediatric sleep apnoea at home
A1 Crespo Sedano, Andrea
A1 Álvarez González, Daniel
A1 Gutiérrez Tobal, Gonzalo César
A1 Vaquerizo Villar, Fernando
A1 Barroso García, Verónica
A1 Alonso Álvarez, María Luz
A1 Terán Santos, Joaquín
A1 Hornero Sánchez, Roberto
A1 Campo Matias, Félix del
K1 Paediatric obstructive sleep apnoea syndrome
K1 Unattended oximetry
K1 Automated pattern recognition
K1 33 Ciencias Tecnológicas
K1 32 Ciencias Médicas
K1 Multiscale entropy
AB Untreated paediatric obstructive sleep apnoea syndrome (OSAS) can severely affect the development and quality of life of children. In-hospital polysomnography (PSG) is the gold standard for a definitive diagnosis though it is relatively unavailable and particularly intrusive. Nocturnal portable oximetry has emerged as a reliable technique for OSAS screening. Nevertheless, additional evidences are demanded. Our study is aimed at assessing the usefulness of multiscale entropy (MSE) to characterise oximetric recordings. We hypothesise that MSE could provide relevant information of blood oxygen saturation (SpO2) dynamics in the detection of childhood OSAS. In order to achieve this goal, a dataset composed of unattended SpO2 recordings from 50 children showing clinical suspicion of OSAS was analysed. SpO2 was parameterised by means of MSE and conventional oximetric indices. An optimum feature subset composed of five MSE-derived features and four conventional clinical indices were obtained using automated bidirectional stepwise feature selection. Logistic regression (LR) was used for classification. Our optimum LR model reached 83.5% accuracy (84.5% sensitivity and 83.0% specificity). Our results suggest that MSE provides relevant information from oximetry that is complementary to conventional approaches. Therefore, MSE may be useful to improve the diagnostic ability of unattended oximetry as a simplified screening test for childhood OSAS.
PB MDPI
YR 2017
FD 2017
LK https://uvadoc.uva.es/handle/10324/56708
UL https://uvadoc.uva.es/handle/10324/56708
LA eng
NO Entropy, 2017, vol. 19, n. 6, p. 284
NO Producción Científica
DS UVaDOC
RD 22-nov-2024