TY - JOUR
T1 - Assessment of sleep-disordered breathing using a non-contact bio-motion sensor
AU - Zaffaroni, Alberto
AU - Kent, Brian
AU - O'Hare, Emer
AU - Heneghan, Conor
AU - Boyle, Patricia
AU - O'Connell, Geraldine
AU - Pallin, Michael
AU - De Chazal, Philip
AU - McNicholas, Walter T.
PY - 2013
Y1 - 2013
N2 - Obstructive sleep apnoea is a highly prevalent but under-diagnosed disorder. The gold standard for diagnosis of obstructive sleep apnoea is inpatient polysomnography. This is resource intensive and inconvenient for the patient, and the development of ambulatory diagnostic modalities has been identified as a key research priority. SleepMinder (BiancaMed, NovaUCD, Ireland) is a novel, non-contact, bedside sensor, which uses radio-waves to measure respiration and movement. Previous studies have shown it to be effective in measuring sleep and respiration. We sought to assess its utility in the diagnosis of obstructive sleep apnoea. SleepMinder and polysomnographic assessment of sleep-disordered breathing were performed simultaneously on consecutive subjects recruited prospectively from our sleep clinic. We assessed the diagnostic accuracy of SleepMinder in identifying obstructive sleep apnoea, and how SleepMinder assessment of the apnoea-hypopnoea index correlated with polysomnography. Seventy-four subjects were recruited. The apnoea-hypopnoea index as measured by SleepMinder correlated strongly with polysomnographic measurement (r = 0.90; P ≤ 0.0001). When a diagnostic threshold of moderate-severe (apnoea-hypopnoea index ≥ 15 events h-1) obstructive sleep apnoea was used, SleepMinder displayed a sensitivity of 90%, a specificity of 92% and an accuracy of 91% in the diagnosis of sleep-disordered breathing. The area under the curve for the receiver operator characteristic was 0.97. SleepMinder correctly classified obstructive sleep apnoea severity in the majority of cases, with only one case different from equivalent polysomnography by more than one diagnostic class. We conclude that in an unselected clinical population undergoing investigation for suspected obstructive sleep apnoea, SleepMinder measurement of sleep-disordered breathing correlates significantly with polysomnography.
AB - Obstructive sleep apnoea is a highly prevalent but under-diagnosed disorder. The gold standard for diagnosis of obstructive sleep apnoea is inpatient polysomnography. This is resource intensive and inconvenient for the patient, and the development of ambulatory diagnostic modalities has been identified as a key research priority. SleepMinder (BiancaMed, NovaUCD, Ireland) is a novel, non-contact, bedside sensor, which uses radio-waves to measure respiration and movement. Previous studies have shown it to be effective in measuring sleep and respiration. We sought to assess its utility in the diagnosis of obstructive sleep apnoea. SleepMinder and polysomnographic assessment of sleep-disordered breathing were performed simultaneously on consecutive subjects recruited prospectively from our sleep clinic. We assessed the diagnostic accuracy of SleepMinder in identifying obstructive sleep apnoea, and how SleepMinder assessment of the apnoea-hypopnoea index correlated with polysomnography. Seventy-four subjects were recruited. The apnoea-hypopnoea index as measured by SleepMinder correlated strongly with polysomnographic measurement (r = 0.90; P ≤ 0.0001). When a diagnostic threshold of moderate-severe (apnoea-hypopnoea index ≥ 15 events h-1) obstructive sleep apnoea was used, SleepMinder displayed a sensitivity of 90%, a specificity of 92% and an accuracy of 91% in the diagnosis of sleep-disordered breathing. The area under the curve for the receiver operator characteristic was 0.97. SleepMinder correctly classified obstructive sleep apnoea severity in the majority of cases, with only one case different from equivalent polysomnography by more than one diagnostic class. We conclude that in an unselected clinical population undergoing investigation for suspected obstructive sleep apnoea, SleepMinder measurement of sleep-disordered breathing correlates significantly with polysomnography.
UR - http://handle.uws.edu.au:8081/1959.7/538827
U2 - 10.1111/j.1365-2869.2012.01056.x
DO - 10.1111/j.1365-2869.2012.01056.x
M3 - Article
SN - 0962-1105
VL - 22
SP - 231
EP - 236
JO - Journal of Sleep Research
JF - Journal of Sleep Research
IS - 2
ER -