Sleep Apnea
Conditions
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.
Interventions
DEVICEAirSense 10 AutoSet for Her
Positive airway pressure
Sponsors
ResMed
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Intervention model description
Cohort study
Eligibility
Sex/Gender
ALL
Age
18 Years to 99 Years
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) algorithm compared to polysomnography (PSG) scored AHI. | 1 night | Calculate accuracy of the device when scoring Apnoeas and Hypopneas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and Hypopneas (decrease of airflow by at least 30% for at least 10 seconds accompanied by a reduction of Oxygen Saturation of 4%) and calculate the apnea-hypopnea-index (AHI): (apneas + hypopneas)/hours of sleep. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| To evaluate the diagnostic accuracy of the AirSense 10 Obstructive Apnea-Index (OAI) detection compared to polysomnography (PSG) gold standard scored OAI. | 1 night | Calculate accuracy of the device when scoring obstructive apnoeas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and calculate the obstructive apnea-index (OAI): (apneas)/hours of sleep. |
| To evaluate the diagnostic accuracy of the AirSense 10 Central Apnea-Index (CAI) detection compared to polysomnography (PSG) gold standard scored CAI. | 1 night | Calculate accuracy of the device when scoring central apnoeas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and calculate the central apnea-index (CAI): (apneas)/hours of sleep. |
| To evaluate the diagnostic accuracy of the AirSense 10 Respiratory-Disturbance-Index (RDI) detection compared to polysomnography (PSG) gold standard scored RDI. | 1 night | Calculate accuracy of the device when scoring respiratory disturbances by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and hypopneas (at least 90% decrease of airflow for at least 10 seconds) with a 3%drop in Oxygen saturation from baseline Level, and RERAs (flow Limitation that does not Count as an hypopnea) and calculate the respiratory disturbance-index (RDI): (apneas + hypopneas + RERAs)/hours of sleep. |
| Evaluate the diagnostic accuracy of the AirSense 10 Respiratory Effort Related Arousals (RERA) detection compared to polysomnography (PSG) gold standard scored RERA. | 1 night | Calculate accuracy of the device when scoring RERAs by comparing to polysomnography scoring RERAs. Identify RERAs (flow Limitation that does not Count as an hypopnea) and calculate the RERA-Index: RERAs/hours of sleep. |
| 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. | 1 night | For secondary endpoint different cut-off values of AHI will be used to determine the accuracy at clinical relevant thresholds. To calculate device AHI accuracy compared to PSG AHI, receiver-operator-curves will be created and sensitivity and specificity calculated based on an AHI cut-off of 5, 15 or 30. |
| To evaluate the diagnostic accuracy of AirView RDI reporting compared to reporting via ResScan (SD card data). | 1 night | AirView is a cloud-based ResMed telemonitoring platform where sleep data can be transferred remotely, displayed and analysed. ResScan is an analysis and reporting software, where device data from the memory card is being uploaded. |
| Sensitivity, specificity and accuracy of the sleep state detection algorithm of the AirSense10 for Her | 1 night | Identify the sleep stage: Stage W (wakefulness), stage N1 (NREM1), stage N2 (NREM2), stage N3 (NREM3) and stage R (REM) |
| Sensitivity, specificity and accuracy of sleep efficiency as derived from the sleep state detection algorithm of the AirSense10 for Her | 1 night | Calculate sleep efficiency by dividing minutes of sleep by minutes of time in bed |
| To evaluate the diagnostic accuracy of AirView AHI reporting compared to reporting via ResScan (SD card data) | 1 night | AirView is a cloud-based ResMed telemonitoring platform where sleep data can be transferred remotely, displayed and analysed. ResScan is an analysis and reporting software, where device data from the memory card is being uploaded. |
Countries
Germany
Outcome results
None listed