Is Portable Sleep Monitoring With Concurrent Actigraphy Accurate in Diagnosing Sleep Apnea That Requires Treatment?

CHEST Journal ◽  
2013 ◽  
Vol 144 (4) ◽  
pp. 982A
Author(s):  
Swamy Nagubadi ◽  
Abhishek Vedavalli ◽  
Mamoun Abdoh ◽  
Venkat Rajasurya ◽  
Rohit Mehta ◽  
...  
Author(s):  
Mansi Gupta ◽  
Pranav Ish ◽  
Shibdas Chakrabarti ◽  
Manas Kamal Sen ◽  
Prabhakar Mishra ◽  
...  

Portable sleep monitoring (PSM) is a promising alternative diagnostic tool for Obstructive Sleep Apnea (OSA) especially in high burden resource limited settings. We aimed to determine the diagnostic accuracy and feasibility of PSM device-based studies in patients presenting for evaluation of OSA at a tertiary care hospital in North-India. PSM studies (using a Type-III PSM device) were compared for technical reliability and diagnostic accuracy with the standard laboratory-based Type-I polysomnography (PSG). Patients were also interviewed about their experience on undergoing an unsupervised PSM studies. Fifty patients (68% males) were enrolled in the study, of which only 30% patients expressed their concerns about undergoing unsupervised PSM studies which included safety issues, ease of use, diagnostic accuracy, etc. Technical acceptability criteria were easily met by the PSM studies with signal loss in 12% studies (complete data loss and inaccessible data in 6% studies), warranting repetition sleep studies in four patients. The overall sensitivity of PSM device (AHI ≥5) was 93.5% (area under curve; AUC: 0.87). The diagnostic accuracy was 68.5%, 80%, and 91.4% for mild, moderate, and severe cases of OSA, respectively. An overall strong correlation was observed between PSM-AHI (apnoea-hypopnoea index) and PSG (r>0.85, p≤0.001), especially in severe OSA. The observed sensitivity was >90% for AHI>20 (clinically significant OSA), with high specificity of 91% for severe OSA (AUC: 0.94, 0.97 for AHI>20, AHI>30 respectively). The overall Bland-Altman concordance analysis also demonstrated only a small dispersion for PSM studies with a Cronbach’s coefficient of 0.95. Therefore, there is good diagnostic accuracy as well as feasibility of home-based portable sleep studies in Indian patients. It can be promoted for widespread use in high burden countries like India for diagnosing and managing appropriately selected stable patients with high clinical probability of OSA, especially during the ongoing crises of COVID-19 pandemic.


Author(s):  
Rohit Mehta ◽  
Swamy Nagubadi ◽  
Umer Nagori ◽  
Boney Ninan ◽  
Reshma Mohiuddin ◽  
...  

SLEEP ◽  
2014 ◽  
Vol 37 (8) ◽  
pp. 1363-1373 ◽  
Author(s):  
Arnoldo Guerrero ◽  
Cristina Embid ◽  
Valentina Isetta ◽  
Ramón Farre ◽  
Joaquin Duran-Cantolla ◽  
...  

Respiration ◽  
1993 ◽  
Vol 60 (6) ◽  
pp. 332-337 ◽  
Author(s):  
Wataru Hida ◽  
Chiyohiko Shindoh ◽  
Hiroshi Miki ◽  
Yoshihiro Kikuchi ◽  
Shinichi Okabe ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2133 ◽  
Author(s):  
Dorien Huysmans ◽  
Pascal Borzée ◽  
Dries Testelmans ◽  
Bertien Buyse ◽  
Tim Willemen ◽  
...  

There exists a technological momentum towards the development of unobtrusive, simple, and reliable systems for long-term sleep monitoring. An off-the-shelf commercial pressure sensor meeting these requirements is the Emfit QS. First, the potential for sleep apnea screening was investigated by revealing clusters of contaminated and clean segments. A relationship between the irregularity of the data and the sleep apnea severity class was observed, which was valuable for screening (sensitivity 0.72, specificity 0.70), although the linear relation was limited ( R 2 of 0.16). Secondly, the study explored the suitability of this commercial sensor to be merged with gold standard polysomnography data for future sleep monitoring. As polysomnography (PSG) and Emfit signals originate from different types of sensor modalities, they cannot be regarded as strictly coupled. Therefore, an automated synchronization procedure based on artefact patterns was developed. Additionally, the optimal position of the Emfit for capturing respiratory and cardiac information similar to the PSG was identified, resulting in a position as close as possible to the thorax. The proposed approach demonstrated the potential for unobtrusive screening of sleep apnea patients at home. Furthermore, the synchronization framework enabled supervised analysis of the commercial Emfit sensor for future sleep monitoring, which can be extended to other multi-modal systems that record movements during sleep.


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