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NCT Number: NCT07502677

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

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.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Royal Brompton Hospital

London, sw3 6np, United Kingdom

Location status: Recruiting

Location contact

Lucy Redmond, Physiotherapy

CONTACT

[email protected]

07752472282

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients aged 18 and over with a Neurologist confirmed diagnosis of ALS

Exclusion criteria

  • Patients with known respiratory disease
  • Unstable cardiac disease, stable hypertension or ischaemic heart disease
  • Current NIV use
  • Inability to give consent (expected ~15% due to frontotemporal dementia)

Treatment and study plan

SleepImage

Device

SleepImage Device

Primary outcomes

  1. SQI & e-LFCNB>2

    Time frame: 12 hours

    We hypothesise that a SQI <55 and Periodicity e-LFCNB>2 has a positive association with an accepted indication for NIV initiation in ALS defined as:

    • Daytime Carbon Dioxide >6.0kPa and a rise of >1kPa from baseline in a time course consistent with REM sleep
    • Bicarbonate levels >32mmol/L
    • SNIP <40cmH20 in patients with non-bulbar disease
    • Supine fall in VC of 20% from erect in patient able to undertake the manoeuvre

Secondary outcomes

  1. Hypoxic burden, T90, Pulse rate variability

    Time frame: 12 hours

    The secondary endpoints of the study are to evaluate additional outputs generated by the SleepImage device and determine their association with the same established clinical criteria for NIV initiation in ALS. Specifically, the secondary analyses will focus on:

    • Hypoxic burden
    • SpO₂ time below 90% (T90).
    • Pulse rate variability

Study contacts

Contact information is provided by the study sponsor or research team.

Lucy Redmond

CONTACT

[email protected]

Professor Michael Polkey

CONTACT

[email protected]

020 7352 8121

Sponsors and collaborators

Lead sponsor

Royal Brompton & Harefield NHS Foundation Trust

Other

Registry information

Important dates

Study start
2026
Primary completion
2026
Study completion
2027
First posted
Mar 31, 2026
Registry last updated
Mar 31, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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