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NCT07502677

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

Recruiting now Last updated 31 March 2026
What this trial tests

trial testing SleepImage in Amyotrophic Lateral Sclerosis in 15 participants. Currently enrolling.

Timeline
24 March 2026
Primary endpoint
1 September 2026
24 March 2027

Quick facts

Lead sponsorRoyal Brompton & Harefield NHS Foundation Trust
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment15
Start date24 March 2026
Primary completion1 September 2026
Estimated completion24 March 2027
Sites1 location across United Kingdom

Drugs / interventions tested

Conditions studied

Sponsor

Royal Brompton & Harefield NHS Foundation Trust

Who can join

18 and older, any sex, with Amyotrophic Lateral Sclerosis. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Amyotrophic Lateral Sclerosis

Currently open trials in the same condition.

Other Royal Brompton & Harefield NHS Foundation Trust trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07502677.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing