Defining obstructive sleep apnoea syndrome: a failure of semantic rules

Breathe, Год журнала: 2021, Номер 17(3), С. 210082 - 210082

Опубликована: Сен. 1, 2021

Obstructive sleep apnoea syndrome (OSAS) is one of the most ubiquitous medical conditions in industrialised society. Since recognition that symptoms excessive daytime somnolence, problems with concentration, mood and cognitive impairment, as well cardiometabolic abnormalities can arise a consequence obstructed breathing during sleep, it has been subject to variation its definition. Over past five decades, attempts have made standardise definitions scoring criteria used for apnoeas hypopnoea, which are hallmarks obstructive (OSA). However, applying these clinical research practice resulted over- under-estimation severity prevalence OSAS. Furthermore, may eventually become redundant context rapid technological advances measurement other signal acquisition. Increased efforts towards precision medicine led focus on pathophysiology sleep. same degree effort not focused how why latter does or result diurnal symptoms, integral definition This review focuses OSAS adults discusses some difficulties current possible reasons behind them.

Язык: Английский

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Deep Learning for Diagnosis and Classification of Obstructive Sleep Apnea: A Nasal Airflow-Based Multi-Resolution Residual Network

Nature and Science of Sleep, Год журнала: 2021, Номер Volume 13, С. 361 - 373

Опубликована: Март 1, 2021

This study evaluated a novel approach for diagnosis and classification of obstructive sleep apnea (OSA), called Obstructive Sleep Apnea Smart System (OSASS), using residual networks single-channel nasal pressure airflow signals.Data were collected from the center First Affiliated Hospital, Sun Yat-sen University, Integrative Department Guangdong Province Traditional Chinese Medical Hospital. We developed new model multi-resolution network (Mr-ResNet) based on to detect signals recorded by polysomnography (PSG) automatically. The performance was assessed its sensitivity, specificity, accuracy, F1-score. built OSASS Mr-ResNet estimate apnea‒hypopnea index (AHI) classify severity OSA, compared agreement between output registered polysomnographic technologist (RPSGT) score, two technologists.In primary test set, F1-score 90.8%, 90.5%, 91.2%, respectively. In independent Spearman correlation AHI RPSGT score determined technologists 0.94 (p < 0.001) 0.96 0.001), Cohen's Kappa scores technologists' 0.81 0.84, respectively.Our results indicated that can automatically diagnose OSA airflow, which is consistent with findings. Thus, holds promise clinical application.

Язык: Английский

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A comparison of 2 visual methods for classifying obstructive vs central hypopneas

Journal of Clinical Sleep Medicine, Год журнала: 2021, Номер 17(6), С. 1157 - 1165

Опубликована: Фев. 16, 2021

Rules for classifying apneas as obstructive, central, or mixed are well established. Although hypopneas given equal weight when calculating the apnea-hypopnea index, classification is not standardized. Visual methods have been proposed by American Academy of Sleep Medicine and Randerath et al (Sleep. 2013;36[3]:363-368) but never compared. We evaluated clinical suitability 2 visual central obstructive.Fifty hypopnea-containing polysomnographic segments were selected from patients with clear obstructive physiology to serve standard hypopneas. These 100 deidentified, randomized, scored groups. assigned 1 group use criteria other algorithm. After a washout period, re-randomized using alternative method. determined accuracy (agreement standard), interrater (Fleiss's κ), intrarater agreement (Cohen's κ) obtained scores.Accuracy was similar: 67% vs 69.3% Medicine, respectively. Cohen's κ 0.01-0.75, showing that some raters similarly methods, while others them markedly differently. Fleiss's algorithm 0.32 (95% confidence interval, 0.29-0.36) 0.27 0.23-0.30).More work needed discover noninvasive way accurately characterize Studies like ours may lay foundation discovering full spectrum physiologic consequences sleep apnea apnea.

Язык: Английский

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Comparison of deep transfer learning models to detect obstructive sleep apnea with single-channel electrocardiogram

Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 201 - 216

Опубликована: Авг. 30, 2024

Язык: Английский

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Transitional Care of Sleep-Disordered Breathing: Management

Sleep Medicine, Год журнала: 2023, Номер unknown, С. 97 - 112

Опубликована: Янв. 1, 2023

Язык: Английский

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