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

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.

Study Overview

• Status: Recruiting
• Conditions: Chronic Obstructive Pulmonary Disease (COPD); Acute Exacerbation of COPD
• Intervention / Treatment: Device: Wearable mobile device; Other: CAT Questionnaire; Other: DHRQ Questionnaire

Detailed Description

Chronic obstructive pulmonary disease (COPD) is a common and life-threatening lung condition responsible for approximately three million deaths worldwide each year. The disease poses a substantial burden not only on individuals but also on healthcare systems. In the European Union, COPD accounts for 56% of annual healthcare costs related to respiratory diseases, equating to 38.6 billion euros.

A significant portion of these costs arises from the worsening of disease symptoms urging frequent (re)hospitalizations. These hospitalizations are typically triggered by flare-ups, also known as acute exacerbations of COPD (AECOPD). Such flare-ups often have a multifactorial origin e.g. bacterial or viral airway infection) and demand timely medical intervention to mitigate their impact.

AECOPD adversely affects the patient's health status, accelerates the decline in lung function, worsens prognosis, and significantly diminishes quality of life. Therefore, early detection of exacerbations is essential to prevent further disease progression and reduce hospital admissions.

Mobile health (mHealth) presents a promising solution for monitoring COPD patients at home remotely. Currently, the health of COPD patients outside of the hospital remains largely unmonitored-a "black box." By using wearable mobile technology to measure multiple parameters (e.g. oxygen saturation, respiratory rate, etc), it may become possible to predict disease worsening early and enable timely intervention. Previous studies have highlighted that monitoring peripheral oxygen saturation (SpO2) and respiratory rate can be useful in predicting AECOPD, but predicting algorithms are still lacking.

In this clinical study, following parameters will be monitored: physical activity, continuous heart rate, respiratory rate & breaths per minute, SpO2, sleep patterns, and core body temperature using a wearable mobile device. These parameters will be tracked from when patients are admitted to the emergency room (ER) until three months after hospital discharge or until rehospitalization due to AECOPD. The data collected will be used to gain insight in the COPD progression following an AECOPD event and construct a prediction model capable of forecasting disease deterioration. This model could enable timely medical intervention in the future, potentially preventing hospitalizations and improving patient outcomes.

• Study Type: Interventional
• Enrollment (Estimated): 50
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Ruben Knevels, MSc; Phone Number: +3289804029; Email: ruben.knevels@zol.be

Study Locations

• Belgium
  • Limburg
    • Genk, Limburg, Belgium, 3600
      • Recruiting
      • Ziekenhuis Oost-Limburg
      • Contact: Future Health; Phone Number: +3289 80 40 10; Email: futurehealth@zol.be
      • Principal Investigator: David Ruttens, MD, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Provide signed and dated informed consent
• Adults older than 18 years of age
• Previously diagnosed with COPD
• Speak and understand the Dutch language
• Need for hospitalization

Exclusion Criteria:

• Previous diagnosis of asthma
• Not in the possession of a smartphone

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Supportive Care
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Patients admitted with an acute COPD exacerbation; Wearable mobile device

Device: Wearable mobile device; Patients admitted due to an acute COPD exacerbation will be asked to wear the wearable mobile device for a period of 3 months. An app linked to the device will be installed on their phone, and be used to send vital parameter data to the investigators.; Other: CAT Questionnaire; During the time of hospital admission and at the end of study, a COPD Assessment Test questionnaire will be taken.; Other: DHRQ Questionnaire; During the time of hospital admission, the patient will be asked to fill in the Digital Health Readiness Questionnaire

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Vital parameter stabilization	Number of days until stabilization of vital parameters measured with help of a remote monitoring system.	From enrollment to the end of treatment at 3 months
Compliance rate	Compliance rate to the remote monitoring system (expressed in %)	From enrollment to the end of treatment at 3 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in AECOPD symptoms	Change in AECOPD symptoms, as measured by the COPD Assessment Test questionnaire	From enrollment to the end of treatment at 3 months
Correlation remote monitoring and subjective questionnaire	The correlation between objectively measured remote monitoring data and a subjective questionnaire. As the questionnaire is mainly focused on COPD symptoms, the correlation will be made with the peripheral oxygen saturation data.	From enrollment to the end of treatment at 3 months

Collaborators and Investigators

• Sponsor: David Ruttens

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2025
• Primary Completion (Estimated): March 1, 2026
• Study Completion (Estimated): March 1, 2026

Study Registration Dates

• First Submitted: March 10, 2025
• First Submitted That Met QC Criteria: March 17, 2025
• First Posted (Actual): March 24, 2025

Study Record Updates

• Last Update Posted (Actual): March 4, 2026
• Last Update Submitted That Met QC Criteria: March 3, 2026
• Last Verified: June 1, 2025

More Information

Terms related to this study

• Keywords: COPD; Mobile Health; AECOPD; Remote Monitoring
• Additional Relevant MeSH Terms: Pathologic Processes; Chronic Disease; Disease Attributes; Respiratory Tract Diseases; Lung Diseases; Lung Diseases, Obstructive; Pathological Conditions, Signs and Symptoms; Pulmonary Disease, Chronic Obstructive
• Other Study ID Numbers: Z-2024106; B3712024000024 (Registry Identifier: Belgian registration)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Raw data regarding the vital parameter measurements will be shared with other researchers.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF; ANALYTIC_CODE; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No