Trial Outcomes & Findings for Evaluation of an Algorithm to Detect Sleep and Wake in Continuous Positive Airway Pressure (CPAP) (NCT NCT01031914)

Results Overview

We tested the ability of the Sleep/Wake algorithm to identify sleep an wake periods with precision, as compared to standard polysonography (PSG) measures, which was used as the gold standard, i.e. we tested the accuracy of the algorithm. Accuracy was defined as the proportion of true results (both true positives and true negatives)in the population and it was assesed using as 2 X 2 table, i.e. accuracy = number of true positives + number of true negatives/ number of true positives + false positives + false negatives +true negatives. where True positive = the algorithm tested correctly identified sleep, False positive = the algorithm tested incorrectly identified sleep, True negative = the algorithm tested correctly rejected awake periods, and False negative = the algorithm tested incorrectly rejected awake periods.

Recruitment status

COMPLETED

Study phase

NA

Target enrollment

36 participants

Primary outcome timeframe

The performance of the algorithm will be evaluated in real time while the subject is wearing the device during the sleep study, an average of 08 hours.

Results posted on

2013-05-14

Participant Flow

Participants were recruited from the general population, the sleep clinic at Sleep HealthCenters, Only subjects who had a diagnostic polysomnography and who were CPAP for at least 2 weeks, were considered for inclusion. Informed consent were be obtained by an investigator or research coordinator and was required for enrollment into the study.

N/A All participants enrolled in the trial have completed the study

Participant milestones

Participant milestones
Measure	Paced Breathing Sleep/Wake Detection All subjects enrolled will have obstructive sleep apnea (OSA) and will be current CPAP users.
Overall Study STARTED	36
Overall Study COMPLETED	36
Overall Study NOT COMPLETED	0

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Evaluation of an Algorithm to Detect Sleep and Wake in Continuous Positive Airway Pressure (CPAP)

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	Paced Breathing Sleep/Wake Detection n=36 Participants All subjects enrolled will have OSA and will be current CPAP users.
Age, Categorical <=18 years	0 Participants n=93 Participants
Age, Categorical Between 18 and 65 years	35 Participants n=93 Participants
Age, Categorical >=65 years	1 Participants n=93 Participants
Age Continuous	48.1 years STANDARD_DEVIATION 11.9 • n=93 Participants
Sex: Female, Male Female	11 Participants n=93 Participants
Sex: Female, Male Male	25 Participants n=93 Participants
Region of Enrollment United States	36 participants n=93 Participants

PRIMARY outcome

Timeframe: The performance of the algorithm will be evaluated in real time while the subject is wearing the device during the sleep study, an average of 08 hours.

Population: All the participants completing the sleep study were included in the analysis

We tested the ability of the Sleep/Wake algorithm to identify sleep an wake periods with precision, as compared to standard polysonography (PSG) measures, which was used as the gold standard, i.e. we tested the accuracy of the algorithm. Accuracy was defined as the proportion of true results (both true positives and true negatives)in the population and it was assesed using as 2 X 2 table, i.e. accuracy = number of true positives + number of true negatives/ number of true positives + false positives + false negatives +true negatives. where True positive = the algorithm tested correctly identified sleep, False positive = the algorithm tested incorrectly identified sleep, True negative = the algorithm tested correctly rejected awake periods, and False negative = the algorithm tested incorrectly rejected awake periods.

Outcome measures

Outcome measures
Measure	Paced Breathing Sleep/Wake Detection n=36 Participants All subjects enrolled will have OSA and will be current CPAP users.
Sleep/Wake Algorithm	62 accuracy (%)

Adverse Events

Paced Breathing Sleep/Wake Detection

Serious events: 0 serious events

Other events: 10 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Other adverse events
Measure	Paced Breathing Sleep/Wake Detection n=36 participants at risk All subjects enrolled will have OSA and will be current CPAP users.
Nervous system disorders Central Sleep apnea	27.8% 10/36 • Number of events 10 • Adverse events were recorded through the duration of the sleep study, an average of 8 hours.

Additional Information

Dr. David P. White

Philips

Phone: 724 387 4554

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place