COPD (Chronic Obstructive Pulmonary Disease)SAGE-NIVNCT07267104
Mathematical Analysis of Signals and Clinical Parameters Provided by Non-invasive Home Ventilation Devices
An observational study of COPD (Chronic Obstructive Pulmonary Disease), run by Corporacion Parc Tauli at 1 site in Spain.
Trial 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. Read more about this study
- Who is it for?
- Ages 40 to 80 years
- Conditions the study is for
- COPD (Chronic Obstructive Pulmonary Disease)
- What is being tested?
- The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPD
- How many people
- 75 participants
- Where
- 1 siteSpain
- Study dates
- 25 Mar 2025to Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: COPD with chronic NIV in acute exacerbation
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Spain1 site, 1 recruiting
- Recruiting
Corporation Parc Tauli de Sabadell
Sabadell, Barcelona
Manel Luján Dr Luján, Professor MD pHD, +34 937231010, mlujan@tauli.cat
About this study
Official title: SAGE-NIV: Surveillance and Artificial Intelligence Guidance for Exacerbations in COPD Patients With Home Non-Invasive Ventilation
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.
Read more
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.
Read the detailed description
This study proposes the development of an artificial intelligence (AI) system to monitor and analyse detailed non-invasive mechanical ventilation (NIV) data in COPD patients, with the aim of predicting clinical exacerbations and improving home management.
Analysis of data from home NIV devices allows assessment of patient compliance, detection of leaks and asynchronies, and monitoring of upper airway events. However, the potential of these data to improve ventilation management in COPD patients has been limited, in part due to the lack of tools to process and interpret the detailed records. Transforming these data into an open format opens up the possibility of applying artificial intelligence to analyse large amounts of information and develop predictive models.
The multi-centre, observational, longitudinal study design will include COPD patients on NIV therapy who meet adherence criteria. Detailed leak, pressure and flow time data, previously decrypted and converted into a data format readable by analysis software, will be analysed. The identified metrics will be evaluated by machine learning algorithms using techniques such as random forest and neural networks.
Expected outcomes include the development of an automated predictive model to enable early detection of exacerbations and improved patient-ventilator synchronisation, moving towards more efficient and personalised telemonitoring in home NIV management.
- Being tested
- The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPD
- Keywords
- COPD, Artificial Intelligent, exacerbations
- Medical subject headings
- Pulmonary Disease, Chronic Obstructive
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPDOther
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 group | Role | What they receive |
|---|---|---|
| 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 Receives: Other: The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPD |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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
RR based on the same signal reconstruction based on the matrix with a programme has already been developed in Matlab® to reconstruct the signal from the built-in software ventilator Some of the metrics to be defined are: for inspiration, peak flow, distance to peak flow, number of peaks, inspiratory time constant, etc. 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 Matlab to facilitate automation.
Measured: 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)
Mean inspiratory time (seconds) obtained by the same signal reconstruction. based on the same signal reconstruction based on the matrix with a programme has already been developed in Matlab® to reconstruct the signal from the built-in software ventilator Some of the metrics to be defined are: for inspiration, peak flow, distance to peak flow, number of peaks, inspiratory time constant, etc. 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 Matlab to facilitate automation.
Measured: 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)
Mean of this realtion based on the same signal reconstruction based on the matrix with a programme has already been developed in Matlab® to reconstruct the signal from the built-in software ventilator Some of the metrics to be defined are: for inspiration, peak flow, distance to peak flow, number of peaks, inspiratory time constant, etc. 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 Matlab to facilitate automation.
Measured: 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)
Specified if the patient had an exacerbation or more the previous year, review of clinical history form previous year
Measured: Baseline
FEV1 (%)
FEV1 (%), of the last spirometry, last spirometry previous acute exacerbation
Measured: Baseline
FVC %
FVC% of last spirometry, FVC% of last spirometry previous of acute exacerbation
Measured: Baseline
FEV1/FVC %
FEV1/FVC % OF LAST SPIROMETRY, previous of acute exacerbation
Measured: Baseline
Date of exacerbation (dd/mm/yyyy)
date of admission
Measured: Baseline
Age (years)
age in the admission
Measured: Baseline
Gender (male / female)
gender of the patient
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Dec 2025
- Study start25 Mar 2025
- Primary completion19 Apr 2025
- Study completionDec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for COPD (Chronic Obstructive Pulmonary Disease)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 75 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Corporacion Parc Tauli
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Cristina Lalmolda-Puyol, Corporacion Parc Tauli
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07267104
- Sponsor's protocol ID
- SAGE-NIV
- Other IDs
- SEPAR PII-NIV
- Acronym
- SAGE-NIV
- Status last verified
- Nov 2025
- First submitted
- 17 Nov 2025
- Last updated
- 5 Dec 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Redcap and drive account
Study at a glance
From the registry record, last updated by the sponsor on 5 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- SAGE-NIV: Surveillance and Artificial Intelligence Guidance for Exacerbations in COPD Patients With Home Non-Invasive Ventilation
- ClinicalTrials.gov ID
- NCT07267104
- Acronym / sponsor ID
- SAGE-NIV / SAGE-NIV
- Keywords
- COPD, Artificial Intelligent, exacerbations
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 75 participants (estimated)
- Lead sponsor
- Corporacion Parc TauliUniversity, hospital or other
- Study start
- 25 Mar 2025 (actual)
- Primary completion
- 19 Apr 2025 (actual)
- Study completion
- Dec 2026 (estimated)
- First posted
- 5 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This study proposes the development of an artificial intelligence (AI) system to monitor and analyse detailed non-invasive mechanical ventilation (NIV) data in COPD patients, with the aim of predicting clinical exacerbations and improving home management.
Analysis of data from home NIV devices allows assessment of patient compliance, detection of leaks and asynchronies, and monitoring of upper airway events. However, the potential of these data to improve ventilation management in COPD patients has been limited, in part due to the lack of tools to process and interpret the detailed records. Transforming these data into an open format opens up the possibility of applying artificial intelligence to analyse large amounts of information and develop predictive models.
The multi-centre, observational, longitudinal study design will include COPD patients on NIV therapy who meet adherence criteria. Detailed leak, pressure and flow time data, previously decrypted and converted into a data format readable by analysis software, will be analysed. The identified metrics will be evaluated by machine learning algorithms using techniques such as random forest and neural networks.
Expected outcomes include the development of an automated predictive model to enable early detection of exacerbations and improved patient-ventilator synchronisation, moving towards more efficient and personalised telemonitoring in home NIV management.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| study cohort with COPD and NIV patients for at least 6 months | – | Other: The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPD1. 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 |
Who may qualify
- Ages
- 40 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- COPD with chronic NIV in acute exacerbation
Key inclusion criteria (5 listed)
- 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.
Key exclusion criteria (2 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| The intervention involves download data of ventilator with clinical dates of the patient and model ventilator and parameters in acute exacebartion fo COPDRecruitment: * 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 | Other | study cohort with COPD and NIV patients for at least 6 months |
Primary outcome
Mean expiratory constant time (seconds)
Time frame: 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 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.
10 secondary outcomes
Mean respiratory rate (RR) rpm
Time frame: 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)
Time frame: 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)
Time frame: 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)
Time frame: Baseline
FEV1 (%)
Time frame: Baseline
FVC %
Time frame: Baseline
FEV1/FVC %
Time frame: Baseline
Date of exacerbation (dd/mm/yyyy)
Time frame: Baseline
Age (years)
Time frame: Baseline
Gender (male / female)
Time frame: Baseline
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Dec 2025.
- Individual participant dataSharing planned: Yes. Redcap and drive account
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of COPD (Chronic Obstructive Pulmonary Disease), run by Corporacion Parc Tauli at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 5 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Manel Lujan, Professor MD pHD (+34 937231010, mlujan@tauli.cat), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Mean expiratory constant time (seconds) (time frame: the 10 days prior to the admission, which will be the reason for recruitment, and the 10 days that will act as a control). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Dec 2025; AzTrials last refreshed its copy on 7 Nov 2026.