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

NCT ID: NCT06890767

Last Updated: 2025-06-29

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

20 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-03-01

Study Completion Date

2026-03-01

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Chronic Obstructive Pulmonary Disease (COPD) Acute Exacerbation of COPD

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

NONE

Study Groups

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Patients admitted with an acute COPD exacerbation

Wearable mobile device

Group Type EXPERIMENTAL

Wearable mobile device

Intervention Type 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.

CAT Questionnaire

Intervention Type OTHER

During the time of hospital admission and at the end of study, a COPD Assessment Test questionnaire will be taken.

DHRQ Questionnaire

Intervention Type OTHER

During the time of hospital admission, the patient will be asked to fill in the Digital Health Readiness Questionnaire

Interventions

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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.

Intervention Type DEVICE

CAT Questionnaire

During the time of hospital admission and at the end of study, a COPD Assessment Test questionnaire will be taken.

Intervention Type OTHER

DHRQ Questionnaire

During the time of hospital admission, the patient will be asked to fill in the Digital Health Readiness Questionnaire

Intervention Type OTHER

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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David Ruttens

OTHER

Sponsor Role lead

Responsible Party

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David Ruttens

Prof. Dr.

Responsibility Role SPONSOR_INVESTIGATOR

Locations

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Ziekenhuis Oost-Limburg

Genk, Limburg, Belgium

Site Status RECRUITING

Countries

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Belgium

Central Contacts

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Ruben Knevels, MSc

Role: CONTACT

+3289804029

Facility Contacts

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Future Health

Role: primary

+3289 80 40 10

Other Identifiers

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B3712024000024

Identifier Type: REGISTRY

Identifier Source: secondary_id

Z-2024106

Identifier Type: -

Identifier Source: org_study_id

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