342 research outputs found
Automated screening of children with obstructive sleep apnea using nocturnal oximetry: An alternative to respiratory polygraphy in unattended settings
Producción CientíficaStudy 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.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
Oximetry use in obstructive sleep apnea
Producción CientíficaIntroduction. Overnight oximetry has been proposed as an accessible, simple, and reliable technique for obstructive sleep apnea syndrome (OSAS) diagnosis. From visual inspection to advanced signal processing, several studies have demonstrated the usefulness of oximetry as a screening tool. However, there is still controversy regarding the general application of oximetry as a single screening methodology for OSAS.
Areas covered. Currently, high-resolution portable devices combined with pattern recognition-based applications are able to achieve high performance in the detection this disease. In this review, recent studies involving automated analysis of oximetry by means of advanced signal processing and machine learning algorithms are analyzed. Advantages and limitations are highlighted and novel research lines aimed at improving the screening ability of oximetry are proposed.
Expert commentary. Oximetry is a cost-effective tool for OSAS screening in patients showing high pretest probability for the disease. Nevertheless, exhaustive analyses are still needed to further assess unattended oximetry monitoring as a single diagnostic test for sleep apnea, particularly in the pediatric population and in especial groups with significant comorbidities. In the following years, communication technologies and big data analysis will overcome current limitations of simplified sleep testing approaches, changing the detection and management of OSAS.This research has been partially supported by the projects DPI2017-84280-R and RTC-2015-3446-1 from Ministerio de Economía, Industria y Competitividad and European Regional Development Fund (FEDER), the project 66/2016 of the Sociedad Española de Neumología y Cirugía Torácica (SEPAR), and the project VA037U16 from the Consejería de Educación de la Junta de Castilla y León and FEDER. D. Álvarez was in receipt of a Juan de la Cierva grant IJCI-2014-22664 from the Ministerio de Economía y Competitividad
Nocturnal Oximetry-based Evaluation of Habitually Snoring Children
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: DeidentifiednSpO2 recordings froma total of 4,191 children
originating from13 pediatric sleep laboratories around the worldwere
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.Supported in part by project VA037 U16 from the Consejer´ıa de Educacio´ n de la Junta de Castilla y Leo´ n and the European Regional Development Fund (FEDER), project RTC-2015-3446-1 from the Ministerio de Econom´ıa y Competitividad and FEDER, and project 153/2015 of the Sociedad Espan˜ ola de Neumolog´ıa y Cirug´ıa Tora´ cica (SEPAR). L.K.-G. is supported by NIH grant 1R01HL130984. M.F.P. was supported by a Fellowship Educational grant award from the Kingdom of Saudi Arabia. D.´A. was in receipt of a Juan de la Cierva grant from the Ministerio de Econom´ıa y Competitividad. The funders played no role in the study design, data collection, data analysis, interpretation, and writing of the manuscript
Nocturnal Oximetry-based Evaluation of Habitually Snoring Children
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: DeidentifiednSpO2 recordings froma total of 4,191 children
originating from13 pediatric sleep laboratories around the worldwere
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.Supported in part by project VA037 U16 from the Consejer´ıa de Educacio´ n de la Junta de Castilla y Leo´ n and the European Regional Development Fund (FEDER), project RTC-2015-3446-1 from the Ministerio de Econom´ıa y Competitividad and FEDER, and project 153/2015 of the Sociedad Espan˜ ola de Neumolog´ıa y Cirug´ıa Tora´ cica (SEPAR). L.K.-G. is supported by NIH grant 1R01HL130984. M.F.P. was supported by a Fellowship Educational grant award from the Kingdom of Saudi Arabia. D.´A. was in receipt of a Juan de la Cierva grant from the Ministerio de Econom´ıa y Competitividad. The funders played no role in the study design, data collection, data analysis, interpretation, and writing of the manuscript
Automated Analysis of Nocturnal Oximetry as Screening Tool for Childhood Obstructive Sleep Apnea-Hypopnea Syndrome
Producción CientíficaChildhood obstructive sleep apnea-hypopnea
syndrome (OSAHS) is a highly prevalent condition that
negatively affects health, performance and quality of life of
infants and young children. Early detection and treatment
improves neuropsychological and cognitive deficits linked with
the disease. The aim of this study was to assess the performance
of automated analysis of blood oxygen saturation (SpO2)
recordings as a screening tool for OSAHS. As an initial step,
statistical, spectral and nonlinear features were estimated to
compose an initial feature set. Then, fast correlation-based
filter (FCBF) was applied to search for the optimum subset.
Finally, the discrimination power (OSAHS negative vs. OSAHS
positive) of three pattern recognition algorithms was assessed:
linear discriminant analysis (LDA), quadratic discriminant
analysis (QDA) and logistic regression (LR). Three clinical cutoff
points commonly used in the literature for positive diagnosis
of the disease were applied: apnea-hypopnea index (AHI) of 1,
3 and 5 events per hour (e/h). Our methodology reached 88.6%
accuracy (71.4% sensitivity and 100.0% specificity, 100.0%
positive predictive value, and 84.0% negative predictive value)
in an independent test set using QDA for a clinical cut-off point
of 5 e/h. These results suggest that SpO2 nocturnal recordings
may be used to develop a reliable and efficient screening tool
for childhood OSAHSJunta de Castilla y León (project VA059U13
Statistical and Nonlinear Analysis of Oximetry from Respiratory Polygraphy to Assist in the Diagnosis of Sleep Apnea in Children
Producción CientíficaObstructive Sleep Apnea-Hypopnea Syndrome
(OSAHS) is a sleep related breathing disorder that has
important consequences in the health and development of
infants and young children. To enhance the early detection of
OSAHS, we propose a methodology based on automated
analysis of nocturnal blood oxygen saturation (SpO2) from
respiratory polygraphy (RP) at home. A database composed of
50 SpO2 recordings was analyzed. Three signal processing
stages were carried out: (i) feature extraction, where statistical
features and nonlinear measures were computed and combined
with conventional oximetric indexes, (ii) feature selection using
genetic algorithms (GAs), and (iii) feature classification through
logistic regression (LR). Leave-one-out cross-validation (loo-cv)
was applied to assess diagnostic performance. The proposed
method reached 80.8% sensitivity, 79.2% specificity, 80.0%
accuracy and 0.93 area under the ROC curve (AROC), which
improved the performance of single conventional indexes. Our
results suggest that automated analysis of SpO2 recordings from
at-home RP provides essential and complementary information
to assist in OSAHS diagnosis in children.Ministerio de Economía y Competitividad (TEC2011-22987)Fundación General CSIC (Proyecto Cero 2011 sobre Envejecimiento)Obra social de la Caixa y CSICJunta de Castilla y León (VA059U13
Multiscale entropy analysis of unattended oximetric recordings to assist in the screening of paediatric sleep apnoea at home
Producción CientíficaUntreated 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.Sociedad Española de Neumología y Cirugía Torácica (SEPAR) project 153/2015Junta de Castilla y León (Consejería de Educación) y el Fondo Europeo de Desarrollo Regional (FEDER), projects (RTC-2015-3446-1) y (TEC2014-53196-R)Ministerio de Economía y Competitividad (MINECO) y FEDER, y el proyecto POCTEP 0378_AD_EEGWA_2_P de la Comisión Europea. L.National Institutes of Health (NIH) grant 1R01HL130984-01Ministerio de Asuntos Económicos y Transformación Digital, grant IJCI-2014-2266
Diseño y evaluación de metodologías de análisis automático de la oximetría nocturna como método simplificado de detección del síndrome de apnea-hipopnea obstructiva del sueño en niños. Validación en el hospital y en el domicilio.
El síndrome de apnea-hipopnea obstructiva del sueño (SAHOS) es una enfermedad
de alta prevalencia en la población infantil, con una importante morbilidad y elevado
impacto sociosanitario, en la que la detección precoz es esencial para iniciar un adecuado
tratamiento, el cual debe ser siempre individualizado. El SAHOS es una alteración
fisiopatológica compleja y multifactorial, en la que no sólo influye una susceptibilidad
genética e individual (factores anatómicos y dinámicos), sino también de estilo de vida. Los
factores de riesgo más frecuentes son la hipertrofia adenoamigdalar y la obesidad. Los
síntomas en los niños son escasos, son principalmente nocturnos y requieren un alto nivel
de sospecha. El SAHOS no diagnosticado o no tratado se relaciona con diferentes
consecuencias metabólicas, cardiovasculares, neurocognitivas, inflamatorias, conductuales
y falta de desarrollo estaturoponderal, lo que conduce a un empeoramiento del estado de
salud en términos generales y disminución de calidad de vida.Departamento de Anatomía y RadiologíaDoctorado en Investigación en Ciencias de la Salu
Primary care strategies for the screening of obstructive sleep apnea in children: An integrative review
Obstructive sleep apnea (OSA) is a sleep related breathing abnormality that involves snoring and intermittent breathing pauses. In children, OSA is linked to cardiovascular, metabolic, behavioural, neurocognitive, and academic consequences (Blechner & Williamson, 2016; Tan, Gozal, & Kheirandish-Gozal, 2016). The most common causes of childhood OSA are adenotonsillar hypertrophy and obesity. With the increasing prevalence of childhood obesity, screening for OSA in the primary care setting is essential for early recognition. This integrative review is guided by the research question: what strategies can NPs, as primary care providers, implement to improve screening for OSA in children between the ages of 2-8 years to determine need for referral? A comprehensive literature search was conducted, and 11 pertinent articles were identified to address the research question. During analysis, three major themes to improve childhood OSA screening emerged: 1) use of validated pediatric OSA screening questionnaires; 2) use of subjective and objective variable screening tools; and 3) the feasibility of home based nocturnal oximetry for children with suspected OSA. Synthesis of the literature provides tools primary care providers can use to screen children for OSA, as well as multiple subjective and objective clinical features of childhood OSA. A gap in pediatric sleep services is recognized, which places emphasis on the need for improved childhood OSA screening in the primary care setting. Further research is needed to validate the use of home-based nocturnal oximetry sleep studies for children with suspected OSA. This paper is concluded with additional recommendations for practice, education, and public health to improve childhood OSA screening and achieve early recognition.obstructive sleep apneasnoringintermittent breathingcardiovascularobesit
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