Mathematical Analysis of Signals and Clinical Parameters Provided by Non-invasive Home Ventilation Devices

NCT07267104 | Recruiting DMC

• 2 other identifiers: SAGE-NIVSEPAR PII-NIV
• Study Type: observational
• Target: 75
• Locations: 1 country
• Sites: 1

Brief Summary

This study will look at people with COPD who use a home breathing machine called non-invasive ventilation (NIV). NIV machines collect information about your breathing, such as air flow, pressure, and mask leaks. Researchers want to use a computer program, called artificial intelligence (AI), to study this information. The goal is to find early signs that your breathing may be getting worse. People with COPD who already use NIV at home may join this study. The study does not change your treatment. It only uses the breathing data already recorded by your NIV machine. The computer program will look for patterns in the data. These patterns may help doctors: Notice early warning signs of a COPD flare-up Find problems with how you and the machine work together Improve the way NIV is monitored at home The main goal is to create a tool that helps patients and doctors manage home NIV more easily and more safely.

Conditions

COPD (Chronic Obstructive Pulmonary Disease)

Keywords

COPD; Artificial Intelligent; exacerbations

Outcome Measures

Primary Outcomes (1)

• Mean expiratory constant time (seconds)

  Mean expiratory constant time based on signal reconstruction and development of metrics basics on the data of traces of the patient ventilator detailed registered. They are converted to an open format using the tool provided and then uploaded to the protected data cloud. Signal reconstruction: based on the matrix , a programme has already been developed in Matlab® to reconstruct the signal from the built-in software. The events (arrows) are exactly the same in the built-in software and in the metrics development program. Three channels are imported: leakage, pressure and flow. Individual metrics For the expiratory part, peak expiratory, distance to peak expiratory, time constant, trend changes (points with first derivative = 0), etc. All mathematical development is implemented in in Matlab to facilitate automation.

  the 10 days prior to the admission, which will be the reason for recruitment, and the 10 days that will act as a control

Secondary Outcomes (10)

• Mean respiratory rate (RR) rpm

  10 days prior to the admission, which will be the reason for recruitment, and the 10 days that will act as a control

• Mean inspiratory time (seconds)

  the 10 days prior to the admission, which will be the reason for recruitment, and the 10 days that will act as a control

• Mean Inspiratory time/ total time (s)

  10 days prior to the admission, which will be the reason for recruitment, and the 10 days that will act as a control

• exacerbation previous year (n)

  Baseline

• FEV1 (%)

  Baseline

Study Arms (1)

study cohort with COPD and NIV patients for at least 6 months

1. Inclusion criteria: * Age between 40 and 80 years. * COPD diagnosed by pulmonary function tests. * Home NIV therapy with good adherence (minimum daily compliance \> 5 hours) for at least 6 months. * Users of the ResMed LUMIS 150 ventilator. This is due to the presence of the decoding tool and a larger storage capacity (more than 100 nights) in the removable device of the ventilator. * Acute exacerbation requiring hospital admission or home care. 2. Exclusion criteria: * Lack of informed consent. * Previous clinical instability defined by the need for antibiotics and/or systemic corticosteroids in the two months prior to the inclusion exacerbation, excluding the 48 hours prior to admission, as this was considered part of the inclusion clinical picture. Ethical aspects: Patients will receive written information about the study and will also receive verbal explanations to clarify any doubts. Participation is voluntary and the patient may withdraw from the study at any time. No inv

Other: The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPD

Interventions

The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPD OTHER

Recruitment: * Collection of the clinical variables described in the previous section. * Download the data from the commercial ventilator mentioned in the 'Inclusion criteria' section. By default, the option 'all available detailed data' is selected in the menu corresponding to the built-in software. * Contact the coordinating centre to obtain an internal study code. * Send the contents of the folder corresponding to the recruited patient to the coordinating centre (using an encrypted system). Treatment and handling of data: * The clinical data collected after anonymisation will be stored on-line using the RedCap platform (https://www.project-redcap.org/). Data downloaded from the ventilator will be identified by a random code and stored on the encrypted Proton platform (https://proton.me/es-es) or similar. * Built-in software data: Once the file has been received, the 10 days prior to the admission, which will be the reason for recruitment

study cohort with COPD and NIV patients for at least 6 months

Eligibility Criteria

• Age: 40 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

COPD with chronic NIV in acute exacerbation

You may qualify if:

• Age between 40 and 80 years.
• COPD diagnosed by pulmonary function tests.
• Home NIV therapy with good adherence (minimum daily compliance \> 5 hours) for at least 6 months.
• Users of the ResMed LUMIS 150 ventilator. This is due to the presence of the decoding tool and a larger storage capacity (more than 100 nights) in the removable device of the ventilator.
• Acute exacerbation requiring hospital admission or home care.

You may not qualify if:

• Lack of informed consent.

Sponsors & Collaborators

• Corporacion Parc Tauli: lead

Study Sites (1)

Corporation Parc Tauli de Sabadell

Sabadell, Barcelona, Spain

RECRUITING

MeSH Terms

Conditions

Pulmonary Disease, Chronic Obstructive

Condition Hierarchy (Ancestors)

Lung Diseases, Obstructive; Lung Diseases; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Manel Lujan, Professor MD pHD

CONTACT

+34 937231010; mlujan@tauli.cat

Cristina Lalmolda Puyol, RT phD

CONTACT

+34 692186820; clalmolda@tauli.cat

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: NIV coordinator Neumology Service

Study Record Dates

• First Submitted: November 17, 2025
• First Posted: December 5, 2025
• Study Start: March 25, 2025
• Primary Completion: April 19, 2025
• Study Completion (Estimated): December 1, 2026
• Last Updated: December 5, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF, CSR
• Time Frame: Available since 2025, March to December 2026
• Access Criteria: Each PI of every center involve in the project

Locations

ES (1)