Trial Outcomes & Findings for Comparison of Breathing Event Detection by a Continuous Positive Airway Pressure Device to Clinical Polysomnography (NCT NCT00836758)

Results Overview

Apnea-hypopnea index (AHI) is the combined average number of apneas and hypopneas that occur per hour of sleep. The Apnea index (AI) is the average number of apneas that occur per hour of sleep. The Hypopnea index (HI) is the average number of hypopneas that occur per hour of sleep. The PSGs were manually scored to determine the apnea-hypopnea index. This value was then compared to the PAP device which utilized the AED algorithm to determine the apnea-hypopnea index.

Recruitment status

COMPLETED

Study phase

NA

Target enrollment

115 participants

Primary outcome timeframe

one night

Results posted on

2019-01-16

Participant Flow

A total of 148 (PSGs and overnights with PAP therapy), collected from 115 unique participants, were included in this analysis.

119 studies had a technically adequate recording and were collected from 90 patients (29 patients participated in two studies). These 119 studies were pooled with another 29 studies from another trial for a total of 148 studies. 4 patients participated in both trials and 3 of these patients contributed two recordings.

Unit of analysis: Overnight PSG and AED algorithms

Participant milestones

Participant milestones
Measure	All Participants Data was collected from participants that participated in a multi-center, randomized, double-blind trial comparing three modes of positive pressure delivery who had overnight PSGs.
Overall Study STARTED	115 148
Overall Study COMPLETED	115 148
Overall Study NOT COMPLETED	0 0

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Comparison of Breathing Event Detection by a Continuous Positive Airway Pressure Device to Clinical Polysomnography

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	CPAP Device n=115 Participants Breathing event detection (AED) by the continuous positive airway pressure (CPAP) device will be compared to breathing event detection by a simultaneous PSG (manual PSG scoring). Analysis with AED and manual PSG scoring: The CPAP device will be set-up at a sub-therapeutic pressure and will remain at this pressure for the entire night, if tolerated. Then the events will be analyzed with Automatic Event Detection (AED) and manual PSG scoring.
Age, Continuous	49.5 years STANDARD_DEVIATION 11.3 • n=5 Participants
Sex: Female, Male Female	31 Participants n=5 Participants
Sex: Female, Male Male	84 Participants n=5 Participants
Region of Enrollment United States	115 participants n=5 Participants
BMI	36.2 kg/m^2 STANDARD_DEVIATION 7.6 • n=5 Participants

PRIMARY outcome

Timeframe: one night

Apnea-hypopnea index (AHI) is the combined average number of apneas and hypopneas that occur per hour of sleep. The Apnea index (AI) is the average number of apneas that occur per hour of sleep. The Hypopnea index (HI) is the average number of hypopneas that occur per hour of sleep. The PSGs were manually scored to determine the apnea-hypopnea index. This value was then compared to the PAP device which utilized the AED algorithm to determine the apnea-hypopnea index.

Outcome measures

Outcome measures
Measure	Manual PSG Scoring n=148 Overnight PSG and AED algorithms The PSGs were manually scored with the aid of computer software by a PSG technologist at a central scoring facility. The technologist was blinded to the event signal during manual scoring (the event signal was not visible in the montages used for scoring). Sleep staging and respiratory events were scored using 2007 American Academy of Sleep Medicine (AASM) guidelines. The scoring of a hypopnea required that the event be associated with a ≥ 4% oxygen desaturation.	Automatic Event Detection n=148 Overnight PSG and AED algorithms The AED algorithm used the following criteria to identify respiratory events. An apnea was detected when there was an 80% or greater reduction in the airflow for 10 sec or longer in comparison with the average airflow over the previous 2 minutes. A hypopnea was detected when there was a device estimated 40% reduction in airflow for ≥ 10 sec but \< 60 sec compared with the average airflow over the previous 2 minutes. The hypopnea detection algorithm required the presence of two recovery breaths that nominally were at least 75% to 80% of the baseline airflow. The algorithm also looked for evidence of flow limitation to detect hypopneas. The algorithm monitored the flow signal for changes in peak flow, and the shape of the inspiratory airflow signal that would be associated with flow limited breathing.
Apnea-hypopnea Indices (AHI) as Determined by Polysomnography (PSG) vs Automatic Event Detection (AED ) Algorithm Apnea index	2.4 events per hour Standard Deviation 4.8	3.2 events per hour Standard Deviation 5.25
Apnea-hypopnea Indices (AHI) as Determined by Polysomnography (PSG) vs Automatic Event Detection (AED ) Algorithm Apnea-hypopnea index	5.6 events per hour Standard Deviation 8.0	5.8 events per hour Standard Deviation 6.3
Apnea-hypopnea Indices (AHI) as Determined by Polysomnography (PSG) vs Automatic Event Detection (AED ) Algorithm Hypopnea index	3.2 events per hour Standard Deviation 5.2	2.6 events per hour Standard Deviation 2.3

SECONDARY outcome

Timeframe: one night

Methodological comparisons utilizing ICC for detection of AHI, apnea index (AI) and hypopnea index (HI) were caculated between the values obtained by PSG and the REMstar Auto with A-Flex device.

Outcome measures

Outcome measures
Measure	Manual PSG Scoring n=148 Overnight PSG and AED algorithms The PSGs were manually scored with the aid of computer software by a PSG technologist at a central scoring facility. The technologist was blinded to the event signal during manual scoring (the event signal was not visible in the montages used for scoring). Sleep staging and respiratory events were scored using 2007 American Academy of Sleep Medicine (AASM) guidelines. The scoring of a hypopnea required that the event be associated with a ≥ 4% oxygen desaturation.	Automatic Event Detection The AED algorithm used the following criteria to identify respiratory events. An apnea was detected when there was an 80% or greater reduction in the airflow for 10 sec or longer in comparison with the average airflow over the previous 2 minutes. A hypopnea was detected when there was a device estimated 40% reduction in airflow for ≥ 10 sec but \< 60 sec compared with the average airflow over the previous 2 minutes. The hypopnea detection algorithm required the presence of two recovery breaths that nominally were at least 75% to 80% of the baseline airflow. The algorithm also looked for evidence of flow limitation to detect hypopneas. The algorithm monitored the flow signal for changes in peak flow, and the shape of the inspiratory airflow signal that would be associated with flow limited breathing.
Methodological Comparisons of AHI, Apnea Index (AI) and Hypopnea Index (HI) as Determined by Intra-class Correlation (ICC) Apnea-Hypopnea Index	0.789 coefficient	—
Methodological Comparisons of AHI, Apnea Index (AI) and Hypopnea Index (HI) as Determined by Intra-class Correlation (ICC) Apnea Index	0.825 coefficient	—
Methodological Comparisons of AHI, Apnea Index (AI) and Hypopnea Index (HI) as Determined by Intra-class Correlation (ICC) Hypopnea Index	0.350 coefficient	—

Adverse Events

CPAP Device

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Richard B. Berry, MD

University of Florida

Phone: 352-262-1575

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place