scholarly journals Home-based Screening for Obstructive Sleep Apnea in Children

2020 ◽  
Vol 5 (1) ◽  
pp. 38
Author(s):  
Dylan Bertoni ◽  
Amal Isaiah ◽  
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Author(s):  
Ingo Fietze ◽  
Sebastian Herberger ◽  
Gina Wewer ◽  
Holger Woehrle ◽  
Katharina Lederer ◽  
...  

Abstract Purpose Diagnosis and treatment of obstructive sleep apnea are traditionally performed in sleep laboratories with polysomnography (PSG) and are associated with significant waiting times for patients and high cost. We investigated if initiation of auto-titrating CPAP (APAP) treatment at home in patients with obstructive sleep apnea (OSA) and subsequent telemonitoring by a homecare provider would be non-inferior to in-lab management with diagnostic PSG, subsequent in-lab APAP initiation, and standard follow-up regarding compliance and disease-specific quality of life. Methods This randomized, open-label, single-center study was conducted in Germany. Screening occurred between December 2013 and November 2015. Eligible patients with moderate-to-severe OSA documented by polygraphy (PG) were randomized to home management or standard care. All patients were managed by certified sleep physicians. The home management group received APAP therapy at home, followed by telemonitoring. The control group received a diagnostic PSG, followed by therapy initiation in the sleep laboratory. The primary endpoint was therapy compliance, measured as average APAP usage after 6 months. Results The intention-to-treat population (ITT) included 224 patients (110 home therapy, 114 controls); the per-protocol population (PP) included 182 patients with 6-month device usage data (89 home therapy, 93 controls). In the PP analysis, mean APAP usage at 6 months was not different in the home therapy and control groups (4.38 ± 2.04 vs. 4.32 ± 2.28, p = 0.845). The pre-specified non-inferiority margin (NIM) of 0.3 h/day was not achieved (p = 0.130); statistical significance was achieved in a post hoc analysis when NIM was set at 0.5 h/day (p < 0.05). Time to APAP initiation was significantly shorter in the home therapy group (7.6 ± 7.2 vs. 46.1 ± 23.8 days; p < 0.0001). Conclusion Use of a home-based telemonitoring strategy for initiation of APAP in selected patients with OSA managed by sleep physicians is feasible, appears to be non-inferior to standard sleep laboratory procedures, and facilitates faster access to therapy.


2014 ◽  
Vol 10 (08) ◽  
pp. 879-885 ◽  
Author(s):  
Natasha Garg ◽  
Andrew J. Rolle ◽  
Todd A. Lee ◽  
Bharati Prasad

CHEST Journal ◽  
2010 ◽  
Vol 138 (2) ◽  
pp. 257-263 ◽  
Author(s):  
Robert P. Skomro ◽  
John Gjevre ◽  
John Reid ◽  
Brian McNab ◽  
Sunita Ghosh ◽  
...  

2021 ◽  
Vol 12 (06) ◽  
pp. 47-63
Author(s):  
Hosna Ghandeharioun

Obstructive sleep apnea (OSA) is one of the most widespread respiratory diseases today. Complete or relative breathing cessations due to upper airway subsidence during sleep is OSA. It has confirmed potential influence on Covid-19 hospitalization and mortality, and is strongly associated with major comorbidities of severe Covid-19 infection. Un-diagnosed OSA may also lead to a variety of severe physical and mental side-effects. To score OSA severity, nocturnal sleep monitoring is performed under defined protocols and standards called polysomnography (PSG). This method is time-consuming, expensive, and requiring professional sleep technicians. Automatic home-based detection of OSA is welcome and in great demand. It is a fast and effective way for referring OSA suspects to sleep clinics for further monitoring. On-line OSA detection also can be a part of a closed-loop automatic control of the OSA therapeutic/assistive devices. In this paper, several solutions for online OSA detection are introduced and tested on 155 subjects of three different databases. The best combinational solution uses mutual information (MI) analysis for selecting out of ECG and SpO2-based features. Several methods of supervised and unsupervised machine learning are employed to detect apnoeic episodes. To achieve the best performance, the most successful classifiers in four different ternary combination methods are used. The proposed configurations exploit limited use of biological signals, have online working scheme, and exhibit uniform and acceptable performance (over 85%) in all the employed databases. The benefits have not been gathered all together in the previous published methods.


Author(s):  
Jean-Benoit Martinot ◽  
Sébastien Bailly ◽  
Lorent Hostaux ◽  
Renaud Tamisier ◽  
Nhat-Nam Le-Dong ◽  
...  

2014 ◽  
Vol 18 (4) ◽  
pp. 817-823 ◽  
Author(s):  
Wish Banhiran ◽  
Wattanachai Chotinaiwattarakul ◽  
Cheerasook Chongkolwatana ◽  
Choakchai Metheetrairut

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