Dataset Information

Accuracy and usability of AcuPebble SA100 for automated diagnosis of obstructive sleep apnoea in the home environment setting: an evaluation study.

ABSTRACT:

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%)), 94.4% positive-predictive value (95% CI (84·78% to 98·11%)) and 95.83% negative-predictive value (95% CI (89·94% to 98·34%)). All patients used AcuPebble_SA100 correctly. Over 97% reported a strong preference for AcuPebble_SA100 over cardiorespiratory polygraphy.

Conclusions

These results validate the efficacy of AcuPebble_SA100 as an automated diagnosis alternative to cardiorespiratory polygraphy; also demonstrating that AcuPebble_SA100 can be used by patients without requiring human training/assistance. This opens the doors for more efficient patient pathways for OSA diagnosis.

Trial registration number

NCT03544086; ClinicalTrials.gov.

SUBMITTER: Devani N

PROVIDER: S-EPMC8693096 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The roles of central nervous mechanisms and cortical output in obstructive sleep apnoea remain unclear. We addressed corticomuscular coupling between cortical sensorimotor areas and lower facial motor units as a mechanistic pathway and as a possible surrogate marker of corticoperipheral motor control in obstructive sleep apnoea. In this exploratory cross-sectional retrospective study, we analysed EEG (C3 and C4 leads) and chin EMG from polysomnography recordings in 86 participants (22 females; age range: 26-81 years): 27 with mild (respiratory disturbance index = 5-15 events/h), 21 with moderate (15-30 events/h) and 23 with severe obstructive sleep apnoea (>30 events/h) and 15 control subjects (<5 events/h). By computing C3-/C4-EEG-chin EMG coherence of signal dynamics in time and frequency domains, we investigated corticomuscular coupling between cortical sensorimotor areas and lower facial motor units with increasing obstructive sleep apnoea severity during the entire sleeping time, during different sleep stages and during obstructive respiratory events, including 5 s before (stable breathing) and after events (breathing resumption). In addition, we studied a possible influence of body mass index and autonomic nervous system activation. We found that both average and respiratory event-specific corticomuscular coupling between cortical sensorimotor areas and lower facial motor units weakened significantly with increasing obstructive sleep apnoea severity, was strongest during N3 and weakened in N1, N2 and rapid eye movement stages (in decreasing order). Coupling increases significantly during the obstructive respiratory events compared with coupling just before and following them. Results were independent of body mass index or autonomic nervous system activation. We conclude that obstructive respiratory events in obstructive sleep apnoea are very strongly associated both quantitatively and temporally with the degree of disconnection within the cortical sensorimotor areas-lower facial motor units pathway. This quite coordinated activity pattern suggests a cortical sensorimotor area-driven obstructive respiratory event pattern generator and a central motor output disorder in obstructive sleep apnoea.