Imperial College London
Alternate

Dr Syed Anas Imtiaz

Faculty of Engineering, Department of Electrical and Electronic Engineering

Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 6297anas.imtiaz Website

 
 
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Location

 

907Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Devani:2021:10.1136/bmjopen-2020-046803,
author = {Devani, N and Pramono, RXA and Imtiaz, SA and Bowyer, S and Rodriguez-Villegas, E and Mandal, S},
doi = {10.1136/bmjopen-2020-046803},
journal = {BMJ Open},
pages = {1--10},
title = {Accuracy and usability of AcuPebble SA100 for automated diagnosis of obstructive sleep apnoea in the home environment setting: an evaluation study},
url = {http://dx.doi.org/10.1136/bmjopen-2020-046803},
volume = {11},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Objectives Obstructive sleep apnoea (OSA) is a heavily underdiagnosed condition, which can lead to significant multimorbidity. Underdiagnosis is often secondary to limitations in existing diagnostic methods. We conducted a diagnostic accuracy and usability study, to evaluate the efficacy of a novel, low-cost, small, wearable medical device, AcuPebble_SA100, for automated diagnosis of OSA in the home environment.Settings Patients were recruited to a standard OSA diagnostic pathway in an UK hospital. They were trained on the use of type-III-cardiorespiratory polygraphy, which they took to use at home. They were also given AcuPebble_SA100; but they were not trained on how to use it.Participants 182 consecutive patients had been referred for OSA diagnosis in which 150 successfully completed the study.Primary outcome measures Efficacy of AcuPebble_SA100 for automated diagnosis of moderate–severe-OSA against cardiorespiratory polygraphy (sensitivity/specificity/likelihood ratios/predictive values) and validation of usability by patients themselves in their home environment.Results After returning the systems, two expert clinicians, blinded to AcuPebble_SA100’s output, manually scored the cardiorespiratory polygraphy signals to reach a diagnosis. AcuPebble_SA100 generated automated diagnosis corresponding to four, typically followed, diagnostic criteria: Apnoea Hypopnoea Index (AHI) using 3% as criteria for oxygen desaturation; Oxygen Desaturation Index (ODI) for 3% and 4% desaturation criteria and AHI using 4% as desaturation criteria. In all cases, AcuPebble_SA100 matched the experts’ diagnosis with positive and negative likelihood ratios over 10 and below 0.1, respectively. Comparing against the current American Academy of Sleep Medicine’s AHI-based criteria demonstrated 95.33% accuracy (95% CI (90·62% to 98·10%)), 96.84% specificity (95% CI (91·05% to 99·34%)), 92.73% sensitivity (95% CI (82·41% to 97·98
AU  - Devani,N
AU  - Pramono,RXA
AU  - Imtiaz,SA
AU  - Bowyer,S
AU  - Rodriguez-Villegas,E
AU  - Mandal,S
DO  - 10.1136/bmjopen-2020-046803
EP  - 10
PY  - 2021///
SN  - 2044-6055
SP  - 1
TI  - Accuracy and usability of AcuPebble SA100 for automated diagnosis of obstructive sleep apnoea in the home environment setting: an evaluation study
T2  - BMJ Open
UR  - http://dx.doi.org/10.1136/bmjopen-2020-046803
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000733431100015&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://bmjopen.bmj.com/content/11/12/e046803
UR  - http://hdl.handle.net/10044/1/94118
VL  - 11
ER  -
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