Diagnostic Accuracy of SleepImage Technology for Detecting Respiratory Failure in Patients With Amyotrophic Lateral Sclerosis

Overview

The specific aim of this study is to try to discover the diagnostic accuracy of SleepImage technology for detecting respiratory failure in patients with MND. Importantly, this research project is not about NIV, it is about what method can most efficiently decide when to start NIV. To do this we'd like to collect data about you and your breathing from the SleepImage device when you come in for your routine overnight sleep study. We will compare this against the data that we would collect anyway.

In general, where lung mechanics are normal, oxygen (O2) levels are the reciprocal of carbon dioxide (CO2) levels. However, due to the sigmoid shape of the oxygen dissociation curve peripheral capillary measurement of O2 (SpO2) via pulse oximeter does not provide adequate warning of respiratory failure in ALS. Advancements in sleep diagnostic equipment has allowed for the SleepImage System in addition to measuring SpO2, to also use tonometry to assesses autonomic output during sleep. SleepImage is US Food and Drug Administration, FDA-cleared and European Union Medical Device Regulatory EU-MDR compliant (CE-marked medical device). Specifically, SleepImage determines sleep architecture based on the strength of synchronisation between signals from the cardiovascular system (pulse rate variability) and respiratory system (tidal volume variability), based on cardiopulmonary coupling (CPC) analysis. Three distinct patterns of CPC are detected; (1) stable sleep (high-frequency coupling, HFC;0.1-0.4Hz) including all electroencephalogram estimated NREM-3 and part of NREM-2 sleep, associated with periods of stable breathing, non-cyclic alternating pattern (CAP) on the EEG, increased delta power and blood pressure dipping, (2) unstable sleep (low-frequency coupling, LFC;0.01-0.1Hz) including all NREM-1 and portion of NREM-2 associated with sleep instability, characterized by variability in tidal volumes, blood pressure non-dipping and CAP on EEG, (3) Wake and rapid eye movement (REM) sleep (very low-frequency coupling characteristics, vLFC;0-0.01Hz). The device can identify potential sleep pathologies evidenced by activity in a subset of unstable sleep where two discernible bands emerge; (1) a broad-spectral-band e-LFC (eLFCBB), linked to sleep fragmentation and obstructive sleep apnoea and (2) a narrow-spectral-band e-LCC (eLFCNB) in the frequency range 0.0006 to 0.1Hz, indicative of putative central sleep apnoea, periodic breathing or complex sleep apnoea. These metrics are expressed as a percentage of analysis windows related to the total sleep period. Other SleepImage diagnostic parameters include the Sleep Quality Index (SQI) which is biomarker and objective score of overall sleep quality. SQI integrates sleep stability, fragmentation, sleep duration and sleep pathologies derived from CPC and is presented on a scale of 0-100, apnoea hypopnea index , hypoxic burden , sleep onset, sleep offset, sleep duration, total sleep time , wake after sleep onset and sleep efficiency. At a practical level, the SleepImage device is a single patient, multiple use device which can be posted to the patient's home. It thus permits a sleep study assessment on as frequent as a basis as the physician and patient wish within the home setting. The aim of this feasibility study is to review the efficacy of the SleepImage diagnostic equipment as a predictor of ventilatory impairment. This will be determined by a sleep quality index SQI of \<55 and Periodicity (eLFCNB) \>2 showing an association with ventilatory failure. The use of the SleepImage technology would not be to replace current diagnostic tests such as SNIP, VC, TcCO2 and blood gases, but instead used as an early screen tool. If a positive association can be made between SQI, Periodicity and ventilatory failure, then SleepImage technology could be used as a tool to expedite the process of hospital diagnostic tests to assess for ventilatory impairment. Furthermore, the SleepImage technology could be used once patients are established onto ventilation as a way of monitoring their ventilatory control on therapy.