From Bench to Bedside: A Machine Learning Tool for the De... | NCT07428694

Studies
From Bench to Bedside: A Machine Learning Tool for the Detection of Inspiratory Leak

NCT07428694

Sponsor

University of Oslo

Status

Recruiting

Last Update Posted

Feb 24, 2026Actual

Enrollment

20Estimated

Phase

Not provided

Conditions

Chronic Respiratory Failure

Interventions

Not provided

Countries

Norway

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Feb 2026

Overall Recruitment Status or Expanded Access Status

Recruiting

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Oct 1, 2025Actual

Primary Completion Date

Oct 1, 2026Estimated

Completion Date

Oct 1, 2026Estimated

First Submitted Date

Feb 17, 2026

First Submission Date that Met QC Criteria

Feb 17, 2026

First Posted Date

Feb 24, 2026Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Feb 17, 2026

Last Update Posted Date

Feb 24, 2026Actual

Name	Class
Oslo University Hospital	OTHER

Oversight Module

Has Data Monitoring Committee (DMC)

Yes

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

Study of the applicability of machine learning tools in detecting inspiratory leakage in longterm non-invasive ventilation. The study was conducted in two stages. Firstly the ML model was trained on both bench model created scenarios and then ten patients. And secondly the success of the model was assessed in a proof of concept pilot study of ten patients.

Detailed Description

Not provided

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

20Estimated

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Correct interpretation of inspiratory leak by machine learning tool	Measured in comparison with god standard method of polygraphy	one year

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

elective hospitalisation for control of non-invasive ventilation
use of ResMedLumis 100/150 ventilator
treatment for >3 months

Exclusion Criteria:

current exacerbation

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

Not provided

Standard Ages

AdultOlder Adult

Study Population

Patients undergoing treatment with Lumis 100/150 for type 2 chronic resiratory failure

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Not provided

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Oslo University Hospital	Recruiting	Oslo			Norway