Validation of Breathing Event Detection of the REMstar Auto With Aflex Compared to Clinical Polysomnography
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Sleep Apnea
- Sponsor
- Philips Respironics
- Enrollment
- 115
- Locations
- 1
- Primary Endpoint
- Apnea-hypopnea Indices (AHI) as Determined by Polysomnography (PSG) vs Automatic Event Detection (AED ) Algorithm
- Status
- Completed
- Last Updated
- 7 years ago
Overview
Brief Summary
The study is to compare the performance of a CPAP (continuous positive airway pressure) device to a clinical polysomnography (PSG) in identifying breathing events in patients with obstructive sleep apnea.
Detailed Description
Purpose: The purpose of this study was to compare the AED algorithm used in a PAP device with manually scored events on PSG. The PAP device was modified to produce a square wave voltage output identifying when apneas, hypopneas, and snoring events were detected. Recording this event signal on the PSG performed with the patient using the PAP device allowed an event-by-event comparison between manually scored PSG events and AED events. In addition, the AHI, AI, and HI derived from the manually scored PSG were compared with the respective measures reported by the PAP device used during the PSG. Study Objectives: Compare automatic event detection (AED) of respiratory events using a positive airway pressure (PAP) device with manual scoring of polysomnography (PSG) during PAP treatment of obstructive sleep apnea (OSA). Design: Prospective PSGs of patients using a PAP device. Setting: Six academic and private sleep disorders centers. Interventions: A signal generated by the PAP device identifying the AED of respiratory events based on airflow was recorded during PSG.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Diagnosis of OSAHS with a baseline AHI ≥ 15 events/hr of sleep assessed January 01, 2007 or later
- •CPAP prescription of 8cm of H20 or higher
- •Able and willing to provide written informed consent
- •Native English speaker
Exclusion Criteria
- •Participation in another interventional research study within the last 30 days
- •Major medical or psychiatric condition that would interfere with the demands of the study and adherence to PAP. Examples include unstable cardiovascular disease (Class III / IV CHF), neuromuscular disease, cancer, and renal failure.
- •Chronic respiratory failure or insufficiency with suspected or known neuromuscular disease, moderate or severe continuous positive airway pressure (COPD) or other pulmonary disorders, or any condition with an elevation of arterial carbon dioxide levels (\> 45 mmHg) while awake, or subjects requiring continuous oxygen therapy.
- •Surgery of the upper airway, nose, sinus, or middle ear within the previous 90 days
- •Surgery at any time for the treatment of OSAHS such as uvulopalatopharyngoplasty (UPPP)
- •Presence of untreated or poorly managed,non-OSAHS related sleep disorders:
- •moderate to severe periodic limb movements(≥ 30/hr with symptoms or arousals)
- •arousals associated with periodic limb movements \> 10 per hour or
- •anyone experiencing chronic and severe insomnia.
- •Consumption of ethanol immediately prior to the research PSG
Outcomes
Primary Outcomes
Apnea-hypopnea Indices (AHI) as Determined by Polysomnography (PSG) vs Automatic Event Detection (AED ) Algorithm
Time Frame: 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.
Secondary Outcomes
- Methodological Comparisons of AHI, Apnea Index (AI) and Hypopnea Index (HI) as Determined by Intra-class Correlation (ICC)(one night)