Clinical trial NCT03043703: AirSense 10 AHI Validation Study
Official title: Accuracy of Detection and Reporting of Sleep-disordered Breathing Metrics Determined by the ResMed AirSense 10 in AirView
Study type: INTERVENTIONAL
Overall status: WITHDRAWN
Phase: NA
Conditions: Sleep Apnea
Lead sponsor: ResMed
Sponsor class: INDUSTRY
First posted: 2017-02-06
Enrollment: 0
Sex: ALL
Minimum age (years): 18
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Cohort study
Primary purpose: DIAGNOSTIC

Brief summary: The AirSense 10 platform is able to detect respiratory events at night and report these data via telemonitoring. The accuracy of the AirSense 10 will be compared with scoring with polysomnography (PSG). 100 patients will be observed in a sleep facility under PSG and AirSense treatment.

Detailed description: Sleep disordered breathing is commonly assessed by calculating an Apnea-Hypopnea-Index AHI and a Hypopnea-Index HI to define how frequent breathing or breathing efforts stop during the night. The severity of sleep apnea (SA) is determined by the number of occurring apneas and hypopneas. The respiratory disturbance index (RDI) captures these events and is calculated comprising an AHI but also RERAs via the flow signal. Polysomnography (PSG) is being used in the sleep laboratory as the Gold standard method to document a patient's sleep behavior by tracking air flow, respiratory effort, blood oxygen and electrocardiac as well as electromyographic signals. This way a comprehensive sleep pattern analysis can be created and different forms of SA can be detected. However, the method is laborious and cost-intensive, so it could save time and costs to have events accurately scored by the device itself. Device data become important when tracking a patient's sleep night by night and not only once. Reliable sleep data can be a valuable tool for tailoring sleep therapy to specific patient's needs. Accurate device data also build the foundation for analysis of large amounts of data, which can help us understanding how sleep disorders develop.

Eligibility criteria: Inclusion Criteria:

1. Patients aged ≥18 years who are able to understand and follow the instructions of the study personnel
2. Patients with an indication for PAP therapy or currently adherent to PAP therapy (device usage ≥4 h/ night) for moderate to severe sleep apnoea and diagnostic AHI ˃15/h and/or a residual CAI ˃5/h
3. Patients with currently titrated fixed CPAP pressure ≥8 cmH2O; or 95th percentile APAP pressure ≥8 cmH2O; or ASV therapy with a 95th percentile IPAP of ≥8 cmH2O
4. Patients who are established PAP users (PAP use duration ≥6 weeks)
5. Dated and signed written informed consent

Exclusion Criteria:

1. Patients with moderate to severe obstructive airway disease and/or respiratory insufficiency
2. Patients with heart failure in NYHA class III or IV, unstable hypertension, paroxysmal/persistent atrial fibrillation, unstable angina pectoris, cardiac or cerebral ischemic events within the last 6 months before screening
3. Patients with current primary or secondary insomnia
4. Patients who are pregnant or breastfeeding
5. Patients who are physically unable to comply with the protocol

Primary outcomes:
measure: To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) algorithm compared to polysomnography (PSG) scored AHI.
timeFrame: 1 night
Secondary outcomes:
measure: To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) detection compared to polysomnography (PSG) gold standard scored AHI for clinical relevant threshold values.
timeFrame: 1 night
measure: To evaluate the diagnostic accuracy of the AirSense 10 Obstructive Apnea-Index (OAI) detection compared to polysomnography (PSG) gold standard scored OAI.
timeFrame: 1 night
measure: To evaluate the diagnostic accuracy of the AirSense 10 Central Apnea-Index (CAI) detection compared to polysomnography (PSG) gold standard scored CAI.
timeFrame: 1 night
measure: To evaluate the diagnostic accuracy of the AirSense 10 Respiratory-Disturbance-Index (RDI) detection compared to polysomnography (PSG) gold standard scored RDI.
timeFrame: 1 night
measure: Evaluate the diagnostic accuracy of the AirSense 10 Respiratory Effort Related Arousals (RERA) detection compared to polysomnography (PSG) gold standard scored RERA.
timeFrame: 1 night
measure: To evaluate the diagnostic accuracy of AirView AHI reporting compared to reporting via ResScan (SD card data)
timeFrame: 1 night
measure: To evaluate the diagnostic accuracy of AirView RDI reporting compared to reporting via ResScan (SD card data).
timeFrame: 1 night
measure: Sensitivity, specificity and accuracy of the sleep state detection algorithm of the AirSense10 for Her
timeFrame: 1 night
measure: Sensitivity, specificity and accuracy of sleep efficiency as derived from the sleep state detection algorithm of the AirSense10 for Her
timeFrame: 1 night
Other outcomes:
Locations:
city: Blaubeuren
country: Germany
facility: Schlaf- und Beatmungszentrum Blaubeuren
state: Baden-Wuerttemberg
city: Essen
country: Germany
facility: Ruhrlandklinik Essen
state: Nordrhein-Westfalen
Study officials:
affiliation: Lungenzentrum Ulm
name: Volker Toepfer, Dr
role: PRINCIPAL_INVESTIGATOR
References:
citation: Pepin JL, Guillot M, Tamisier R, Levy P. The upper airway resistance syndrome. Respiration. 2012;83(6):559-66. doi: 10.1159/000335839. Epub 2012 Mar 1.
citation: Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R, Parthasarathy S, Quan SF, Redline S, Strohl KP, Davidson Ward SL, Tangredi MM; American Academy of Sleep Medicine. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med. 2012 Oct 15;8(5):597-619. doi: 10.5664/jcsm.2172.