Early identification of heart failure deterioration through respiratory monitoring with adaptive servo-ventilation.

Cardiac decompensation is associated with worse prognosis in patients with heart failure. Reliable methods to predict cardiac decompensation events are not yet available. Sleep-disordered breathing (SDB) is a frequent comorbidity in heart failure, and it has been shown to correlate with heart failure severity. This prospective observational trial investigated SDB characteristics in patients with heart failure with the aim to identify patterns that may predict early cardiac decompensation. Patients with heart failure with diagnosed SDB and hospitalised for cardiac decompensation were prospectively enrolled and treated with adaptive servo-ventilation (ASV). SDB characteristics, daily body weight and clinical cardiac decompensation events were collected over a 1-year follow-up. Clinical events were categorised by an independent clinical event committee. A total of 43 patients were enrolled (81% male, mean [SD] age 71 [11] years, body mass index 30 kg/m2 , 95% New York Heart Association function class III or IV, mean [SD] left ventricular ejection fraction 37% [11%], median apnea-hypopnoea index [AHI] of 37 events/h). A total of 48 cardiac decompensation events were recorded during the 1-year study period. Respiratory rate was found to be significantly lower in patients with cardiac decompensation. The AHI and applied inspiratory pressure ASV-device support were significantly increased 10 days before a clinical cardiac decompensation event. Device usage was also found to be significantly decreased 2 nights before cardiac decompensation. Device-derived respiratory data in ASV therapy devices for SDB may therefore serve as a monitoring tool to predict early clinical cardiac decompensation events. Prediction and avoidance of cardiac decompensation, in turn, may attenuate serious health consequences in patients with heart failure.

A Wearable Ballistocardiography Device for Estimating Heart Rate During Positive Airway Pressure Therapy: Investigational Study Among the General Population.

BACKGROUND: Obstructive sleep apnea (OSA) is a condition in which a person's airway is obstructed during sleep, thus disturbing their sleep. People with OSA are at a higher risk of developing heart problems. OSA is commonly treated with a positive airway pressure (PAP) therapy device, which is used during sleep. The PAP therapy setup provides a good opportunity to monitor the heart health of people with OSA, but no simple, low-cost method is available for the PAP therapy device to monitor heart rate (HR). OBJECTIVE: This study aims to develop a simple, low-cost device to monitor the HR of people with OSA during PAP therapy. This device was then tested on a small group of participants to investigate the feasibility of the device. METHODS: A low-cost and simple device to monitor HR was created by attaching a gyroscope to a PAP mask, thus integrating HR monitoring into PAP therapy. The gyroscope signals were then analyzed to detect heartbeats, and a Kalman filter was used to produce a more accurate and consistent HR signal. In this study, 19 participants wore the modified PAP mask while the mask was connected to a PAP device. Participants lay in 3 common sleeping positions and then underwent 2 different PAP therapy modes to determine if these affected the accuracy of the HR estimation. RESULTS: Before the PAP device was turned on, the median HR error was <5 beats per minute, although the HR estimation error increased when participants lay on their side compared with when participants lay on their back. Using the different PAP therapy modes did not significantly increase the HR error. CONCLUSIONS: These results show that monitoring HR from gyroscope signals in a PAP mask is possible during PAP therapy for different sleeping positions and PAP therapy modes, suggesting that long-term HR monitoring of OSA during PAP therapy may be possible.

A Modified Mask for Continuous Cardiac Monitoring during Positive Airway Pressure Therapy.

A Positive Airway Pressure mask was modified to be able to measure the heart rate of the wearer during Positive Airway Pressure (PAP) therapy. The mask was modified by attaching sensors to measure Electrocardiography (ECG) and Photoplethysmography (PPG) signals, from which a heart rate was extracted. The ECG signal was recorded using stainless steel electrodes positioned on the wearer's head and neck. The PPG signal was measured from the wearer's forehead using a reflectance pulse oximeter attached to the mask. The modified device was tested on 19 healthy participants (mean age30.5 ± 9 years) in a simulated sleeping environment. For both the ECG and PPG signals, the device was able to correctly identify more than 95% of heartbeats for the majority of the participants. However, it was found that by combining the ECG and PPG heartbeat data, the percentage of heartbeats that could be detected was increased to 99%. The results showed that it may be possible to use this device to monitor sleep apnoea patients during PAP therapy in their homes.

Validation of automatic CPAP leak algorithm.

Obstructive Sleep Apnoea (OSA) is a prevalent disease. Reliable estimation of respiratory parameters by devices used to treat OSA is important for therapy initiation and maintenance. This is achieved by estimating patient flow in the presence of inadvertent leak from the total flow measured by the device. A method of validating the patient flow estimation of an Automatic Continuous Positive Airway Pressure (APAP) device is described. Novel techniques of a multi-composite simulant head and recorded patient flows are used. The APAP device tested was shown to reliably estimate patient flow across a range of therapy pressures, leak conditions and breath types.