NCT06890767: COPD-BREATHE

Remote Monitoring of COPD Patients Experiencing an Acute Exacerbation Through Health Evaluations Using Wearable Mobile Technology

Recruiting now NA Last updated 4 March 2026

What this trial tests

NA trial testing Wearable mobile device in Chronic Obstructive Pulmonary Disease (COPD) in 50 participants. Currently enrolling.

Timeline

1 March 2025

Primary endpoint
1 March 2026

1 March 2026

Quick facts

Lead sponsor	David Ruttens
Phase	NA
Status	Recruiting now
Study type	INTERVENTIONAL
Allocation	na
Design	single group
Masking	none
Primary purpose	supportive care
Enrollment	50
Start date	1 March 2025
Primary completion	1 March 2026
Estimated completion	1 March 2026
Sites	1 location across Belgium

Drugs / interventions tested

• Wearable mobile device
• CAT Questionnaire
• DHRQ Questionnaire

Conditions studied

• Chronic Obstructive Pulmonary Disease (COPD) — all drugs for Chronic Obstructive Pulmonary Disease (COPD) →
• Acute Exacerbation of COPD — all drugs for Acute Exacerbation of COPD →

Sponsor

David Ruttens

Who can join

18 and older, any sex, with Chronic Obstructive Pulmonary Disease (COPD) or Acute Exacerbation of COPD. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Chronic obstructive pulmonary disease (COPD) causes about 3 million deaths annually and significantly burdens healthcare systems, costing the EU 38.6 billion euros, largely due to frequent hospitalizations triggered by acute exacerbations (AECOPD). AECOPD worsens patient health, accelerates lung decline, and lowers quality of life, highlighting the need for early detection. Moreover, these AECOPD events happen in an out-hospital setting and are therefore, not preventable. A clear clinical and quality-of-life need arises to reduce AECOPD-related events and consequent hospitalizations.

Mobile health (mHealth) offers a solution by monitoring patients remotely using unobtrusive wearable devices. Parameters like peripheral oxygen saturation (SpO2) and respiratory rate can detect and predict exacerbations. However, no data at home is available of AECOPD events and robust predictive algorithms are lacking. This study aims to monitor vital parameters at home, tracking physical activity, pulse, respiratory rate, SpO2, sleep, and skin temperature from the moment of ER admission until three months post-discharge. Data will be used to gain insight in the COPD progression following an AECOPD event and to construct a predictive model, enabling timely intervention, reducing hospitalizations, and improving outcomes.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.