Clinical trial NCT03526133: Validation of Sleep Apnea Diagnosis Device
Official title: Validation of a Wireless Wearable Sensor Using Mobile Technology and Cloud Computing for the Diagnosis of Sleep Apnea
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Sleep Apnea
Keywords: sleep apnea
polygraph
home sleep apnea test (HSAT)
apnea hypopnea index (AHI)
oxygen desaturation index (ODI)
portable monitor
sleep actimetry
snoring
Lead sponsor: University of Sao Paulo General Hospital
Sponsor class: OTHER
Collaborators: name: Biologix Sistemas Ltda
First posted: 2018-05-16
Enrollment: 300
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Consecutive patients referred to a university-based tertiary sleep referral centre.

Brief summary: Obstructive sleep apnea (OSA) is common and largely underdiagnosed disease. The standard method for the diagnosis of OSA is a complete night polysomnography (PSG). Simple methods for OSA diagnosis are necessary. The overnight oximetry with the oxygen desaturation index (ODI) has been largely investigated as a diagnostic test for OSA but its accuracy remains undefined. The aim of our study is to evaluate if an wireless polygraph (Oxistar) is accurate to diagnosis OSA in patients referred to a Sleep Lab.

Detailed description: Consecutive patients referred to the sleep laboratory with suspected diagnosis of OSA underwent in-laboratory polysomnography (PSG) and simultaneously wireless polygraph. The PSG oximeter and the wireless polygraph were worn on different fingers of the same hand. All sleep studies were reviewed by one blind investigator according the 2017 American Academy of Sleep Medicine recommendations. The number of desaturations from wireless polygraph at the 3 predefined threshold levels (of ODI-2%, ODI-3%, or ODI-4%) was derived automatically using proprietary algorithm. Moderate to severe OSA was defined as AHI ≥ 15 events/h. The diagnostic accuracy of ODI-2%, 3%, and 4% for the diagnosis of moderate-severe OSA were calculated for cut-off values from 1 to 20 desaturation events/h. The sleep actimetry was compared with the sleep stages from PSG, most of the statistical metrics applied for diagnosis were used to evaluate the applicability of this proposed method. Finally, the snoring events computed by the smartphone application were compared with the events heard by a specialist and the statistical comparison metrics were evaluated.

Eligibility criteria: Inclusion Criteria:

* referred by medical staff for an overnight assessment for suspected sleep apnea

Exclusion Criteria:

* polysomnography for the CPAP titration

Primary outcomes:
measure: Sensitivity
timeFrame: Night during the polysomnography exam
measure: Specificity
timeFrame: Night during the polysomnography exam
measure: Area under the curve (AUC)
timeFrame: Night during the polysomnography exam
measure: Bland-Altman Graph
timeFrame: Night during the polysomnography exam
measure: Interclass Correlation Coefficient (ICC)
timeFrame: Night during the polysomnography exam
Secondary outcomes:
measure: Sleep Actigraphy
timeFrame: Night during the polysomnography exam
measure: Number of snoring events per hour of register (snoring/h)
timeFrame: Night during the polysomnography exam
Other outcomes:
Locations:
city: Sao Paulo
country: Brazil
facility: Incor - Heart Institute, Sleep Laboratory
Study officials:
affiliation: Associate Professor
name: Geraldo Lorenzi-Filho, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Pinheiro GDL, Cruz AF, Domingues DM, Genta PR, Drager LF, Strollo PJ, Lorenzi-Filho G. Validation of an Overnight Wireless High-Resolution Oximeter plus Cloud-Based Algorithm for the Diagnosis of Obstructive Sleep Apnea. Clinics (Sao Paulo). 2020 Nov 27;75:e2414. doi: 10.6061/clinics/2020/e2414. eCollection 2020.