ClinicalTrials.gg
Not yet recruitingNCT07799896COPD-AIRUpdated Sep 2, 2026

The Impact of Indoor Environmental Quality on Symptoms in Patients With Chronic Obstructive Pulmonary Disease

An interventional study of Wearable mobile device and Indoor environmental quality sensor in COPD (Chronic Obstructive Pulmonary Disease) and Acute Exacerbation of COPD, sponsored by Ziekenhuis Oost-Limburg. Not yet recruiting at 1 site in Belgium. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-09-02.

Sponsored by Ziekenhuis Oost-Limburg · Not applicable, Interventional, and Supportive care

Phase
Not applicable
Study type
Interventional
Enrollment
15
Allocation
Not applicable
Ages
18 Years and older
Sex
All
01

Study summary

This prospective, monocenter pilot study will investigate the relationship between indoor environmental quality (including air quality, lighting, noise, and thermal conditions), wearable-derived health insights, and patient-reported symptoms in patients recovering at home after hospitalization for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Participants will undergo continuous monitoring of indoor environmental conditions and health parameters using a Garmin Venu 4 smartwatch, together with validated questionnaires assessing COPD symptoms, sleep quality, and daytime sleepiness during one month. The study will assess the feasibility and potential added value of high-resolution home monitoring and explore whether environmental and wearable-derived measures are associated with symptom burden and early signs of clinical deterioration following hospital discharge.

The investigators hypothesize that continuous in-home monitoring of indoor environmental quality is feasible and provides clinically relevant insights into symptom burden in recently hospitalized COPD patients. The primary objective is to determine the correlation between indoor environmental quality (IEQ) variables and symptom burden in COPD patients following hospitalization for AECOPD.

Read the detailed description

Patients hospitalized for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) remain highly vulnerable after discharge, with persistent symptom burden and an increased risk of early recurrent exacerbations. During this post-hospitalization period, patients spend most of their time indoors, making indoor environmental quality (IEQ, including air quality, lighting, noise and thermal aspects) a potentially important and modifiable determinant of recovery. For example, exposure to particulate matter (PM) has been associated with airway inflammation, symptom worsening, and increased exacerbation risk in COPD. However, evidence on continuously measured IEQ at home and its relationship with symptoms after hospitalization for acute exacerbation of COPD remains limited.

Recent advances in wearable technology allow continuous monitoring of health insights in real-world settings. Prior studies have demonstrated the feasibility of wearable devices in patients with COPD and suggest that changes in activity, heart rate, and sleep may precede clinical deterioration or exacerbations. Integrating continuous IEQ monitoring with wearable-derived health insights (i.e., from a Garmin Venu 4 watch) and validated patient-reported outcomes, such as the widely used COPD Assessment Test (CAT), Pittsburgh Sleep Quality Index (PSQI), Karolinska Sleepiness Scale (KSS), Sleep Quality Scale (SQS), may improve understanding of symptom dynamics, uncover risk factors, and identify early indicators of worsening disease. This prospective monocenter pilot study aims to explore these relationships and to assess the feasibility and added value of high-resolution IEQ monitoring in the home setting of recently hospitalized COPD patients.

02

Conditions studied

  • COPD (Chronic Obstructive Pulmonary Disease)
  • Acute Exacerbation of COPD

Keywords

  • Mobile health
  • COPD
  • Remote monitoring
  • AECOPD
  • Air quality
  • Environmental quality
  • Indoor air quality
03

In context

Pulmonary Disease, Chronic Obstructive

5,520 studies on the registry are indexed under Pulmonary Disease, Chronic Obstructive; 856 are open to participants now.

This study's planned enrollment of 15 is below the median of 62 across 3,839 interventional studies indexed under Pulmonary Disease, Chronic Obstructive.

Browse Pulmonary Disease, Chronic Obstructive studies →

Lead sponsor

Ziekenhuis Oost-Limburg is the lead sponsor of 69 studies on the registry; 16 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Provide signed and dated
  • Adults older than 18 years of age
  • Previously diagnosed with according to GOLD guidelines
  • Hospitalization due to AECOPD
  • Spend >50% of time indoor at home
  • Speak and understand the Dutch language

Exclusion criteria

Exclusion Criteria:

  • Previous diagnosis of asthma
  • (History of) chronic macrolide use (> 3 months)
  • Living in institution or residential care center
  • Estimated of less than 6 months
  • Not in the possession of a smartphone
Terms in these criteria, in plain language(3)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

COPD

Chronic obstructive pulmonary disease: long-term lung disease that makes it hard to breathe out, including emphysema and chronic bronchitis.

Life expectancy

The study doctor’s estimate of how long someone is likely to live. Criteria use it so that people can stay in the study long enough for it to answer its question.

05

Study design

Phase
Not applicable
Primary purpose
Supportive care
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
15 participants (estimated)

Study arms

  • Experimental
    Patients admitted with an acute COPD exacerbation

    Wearable mobile device (Garmin Venu) \& Indoor environmental quality sensor

    Device: Wearable mobile device · Device: Indoor environmental quality sensor · Other: CAT Questionnaire · Other: PSQI Questionnaire · Other: KSS Questionnaire · Other: SQS Questionnaire · Other: PROMs Questionnaire · Other: eHLQ Questionnaire · Other: Housing Questionnaire

Interventions

  • DeviceWearable mobile device

    Patients admitted due to an acute COPD exacerbation will be asked to wear the wearable mobile device for a period of one month after hospital discharge. An app linked to the device will be installed on their phone, and used to send health insights to the investigators.

    Also known as: Garmin Venu

  • DeviceIndoor environmental quality sensor

    When the participants are discharged home, an indoor environmental quality sensor will be installed in the patient's home. One sensor will be installed in the bedroom, one in the living room or kitchen (wherever the patient spends the most time). Data from these sensors will be sent to the hub (placed central between the sensors) and thereafter, to the investigators. The sensors measure particulate matter concentrations, CO2 concentrations, VOC concentrations, temperature, relative humidity, ambient light, and ambient noise.

  • OtherCAT Questionnaire

    A COPD Assessment Test questionnaire will be taken during the hospitalization (start of the study), and weekly after discharge.

  • OtherPSQI Questionnaire

    A Pittsburgh Sleep Quality Index questionnaire will be taken 4 weeks after hospital discharge (end of the study).

  • OtherKSS Questionnaire

    A Karolinska Sleepiness Scale questionnaire will be taken daily after discharge.

  • OtherSQS Questionnaire

    A sleep quality scale questionnaire will be taken daily after discharge.

  • OtherPROMs Questionnaire

    A PROMs questionnaire will be taken daily after discharge.

  • OthereHLQ Questionnaire

    An eHealth literacy questionnaire will be taken during the hospitalization (start of the study), and 4 weeks after hospital discharge (end of the study).

  • OtherHousing Questionnaire

    A housing questionnaire will be taken during the hospitalization (start of the study).

06

What researchers measure

Primary outcomes

  1. Weekly score of COPD symptom burden assessed using the COPD Assessment Test (CAT)

    COPD symptom burden will be assessed using the COPD Assessment Test (CAT). The CAT is an 8-item questionnaire with a total score ranging from 0 to 40 points, with higher scores indicating greater COPD symptom burden and a greater impact of COPD on daily life.

    Time frame: Baseline and weekly during the 1-month follow-up

  2. Weekly mean PM0.5 concentration

    Indoor PM0.5 concentration (µg/m³) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean PM0.5 concentration.

    Time frame: Weekly during the 1-month follow-up

  3. Weekly mean PM2.5 concentration

    Indoor PM2.5 concentration (µg/m³) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean PM2.5 concentration.

    Time frame: Weekly during the 1-month follow-up

  4. Weekly mean PM4 concentration

    Indoor PM4 concentration (µg/m³) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean PM4 concentration.

    Time frame: Weekly during the 1-month follow-up

  5. Weekly mean PM10 concentration

    Indoor PM10 concentration (µg/m³) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean PM10 concentration.

    Time frame: Weekly during the 1-month follow-up

  6. Weekly mean CO2 concentration

    Indoor CO2 concentration (ppm) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean CO2 concentration.

    Time frame: Weekly during the 1-month follow-up

  7. Weekly mean VOC concentration

    Indoor volatile organic compound (VOC) concentration (ppb) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean VOC concentration.

    Time frame: Weekly during the 1-month follow-up

  8. Weekly mean temperature

    Indoor temperature concentration (°C) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean temperature.

    Time frame: Weekly during the 1-month follow-up

  9. Weekly mean relative humidity

    Indoor relative humidity (%) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week will be aggregated to calculate a weekly mean relative humidity.

    Time frame: Weekly during the 1-month follow-up

  10. Weekly mean ambient light - day

    Indoor ambient light (lux) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week during day-time hours will be aggregated to calculate a weekly mean ambient light - day.

    Time frame: Weekly during the 1-month follow-up

  11. Weekly mean ambient light - night

    Indoor ambient light (lux) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week during night-time hours will be aggregated to calculate a weekly mean ambient light - night.

    Time frame: Weekly during the 1-month follow-up

  12. Weekly mean ambient noise - night

    Indoor ambient noise (dB) will be measured at 15-minute intervals in the participant's home during the 1-month follow-up. The measurements collected during each week during night-time hours will be aggregated to calculate a weekly mean ambient noise - night.

    Time frame: Weekly during the 1-month follow-up

  13. Weekly overall proportion of time with at least one IEQ threshold violated

    Overall proportion of monitoring time per week during which at least one predefined indoor environmental quality (IEQ) threshold is violated. IEQ variables will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, the IEQ variables will be compared with their respective predefined thresholds. The proportion of monitoring time points at which at least one IEQ threshold is violated will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

Secondary outcomes

  1. Feasibility - Measurement completeness

    Proportion of expected IEQ measurements successfully recorded.

    Time frame: During follow-up (1 month)

  2. Feasibility - Valid monitoring time

    Duration of valid monitoring time per participant.

    Time frame: During follow-up (1 month)

  3. Daily perceived change in health status

    Patient-reported change in overall health status compared with the previous day, assessed using a single question: "How is your health today compared with yesterday?" Participants will select one of three response options: better, about the same, or worse.

    Time frame: Daily during follow-up (1 month)

  4. Feasibility - Frequency of data gaps

    Frequency of gaps in monitoring data.

    Time frame: During follow-up (1 month)

  5. Feasibility - Duration of data gaps

    Duration of gaps in monitoring data.

    Time frame: During follow-up (1 month)

  6. Wearable-derived health insights - Heart rate

    Heart rate (BPM) measured using the wearable.

    Time frame: Continuous monitoring during follow-up (1 month)

  7. Wearable-derived health insights - Respiratory rate

    Respiratory rate (BPM) measured using the wearable.

    Time frame: Continuous monitoring during follow-up (1 month)

  8. Wearable-derived health insights - Oxygen saturation

    Oxygen saturation (%) measured using the wearable.

    Time frame: Continuous monitoring during follow-up (1 month)

  9. Wearable-derived health insights - Skin temperature

    Nightly deviation in skin temperature (°C) compared with the previous night, measured using the wearable.

    Time frame: Continuous monitoring during follow-up (1 month)

  10. Sleep quality - PSQI

    Pittsburgh Sleep Quality Index (PSQI) assessing subjective sleep quality over the preceding month. The PSQI total score ranges from 0 to 21 points, with higher scores indicating poorer sleep quality.

    Time frame: End of study (one month)

  11. Sleepiness - KSS

    Karolinska Sleepiness Scale (KSS) assessing subjective sleepiness at a specific time point. The KSS score ranges from 1 to 9 points, with higher scores indicating greater subjective sleepiness.

    Time frame: Daily during the 1-month follow-up

  12. Sleep quality - SQS

    Single-item Sleep Quality Scale (SQS) assessing perceived sleep quality of the previous night. The SQS score ranges from 0 to 10 points, with higher scores indicating better perceived sleep quality.

    Time frame: Daily during the 1-month follow-up

  13. Wearable-derived sleep metrics - Sleep duration

    Nightly sleep duration (hours) measured using the wearable.

    Time frame: Nightly during the 1-month follow-up

  14. Wearable-derived sleep metrics - Sleep score

    Nightly sleep score measured using the wearable. Score from 0-100, with a higher score indicating better quality of sleep.

    Time frame: Nightly during the 1-month follow-up

  15. Wearable-derived sleep metrics - Time in sleep cycle

    Nightly time spent in REM, deep, and light sleep (hours).

    Time frame: Nightly during the 1-month follow-up

  16. Wearable-derived physical activity - Daily step count

    Daily step count (number) measured by the wearable.

    Time frame: Daily during the 1-month follow-up

  17. Wearable-derived physical activity - Activity minutes

    Daily activity minutes (minutes) measured by the wearable.

    Time frame: Daily during the 1-month follow-up

  18. Concentration of outside air quality

    Concentration of outside air quality measure (PM, expressed in µg/m³) based on the participant's residential area.

    Time frame: During follow-up (1 month)

  19. COPD exacerbations

    Occurrence of a COPD exacerbation during the follow-up period.

    Time frame: During follow-up (1 month)

  20. eHealth literacy

    eHealth Literacy Questionnaire (eHLQ) domain scores describing participants' strengths and needs related to eHealth literacy. The eHLQ consists of 35 items across 7 domains. Each domain is scored from 1 to 4 points, with higher scores indicating a greater level of the characteristic assessed by the respective domain.

    Time frame: Baseline and end of study (one month)

  21. Change in eHealth literacy

    Change in eHealth literacy from baseline to the end of the 1-month follow-up, assessed using the eHealth Literacy Questionnaire (eHLQ). The eHLQ consists of 35 items across 7 domains. Each domain is scored from 1 to 4 points. Higher scores indicate a greater level of the characteristic assessed by the respective domain. Change in each domain score from baseline to 1 month will be calculated.

    Time frame: Baseline and end of study (one month)

  22. Housing characteristics

    Sociodemographic characteristics, housing characteristics, and indoor environmental factors assessed using the Housing Conditions Questionnaire.

    Time frame: Baseline

  23. Weekly overall proportion of time with PM0.5 threshold exceeded

    Overall proportion of monitoring time per week during which PM0.5 threshold is exceeded. PM0.5 will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, PM0.5 will be compared with its respective predefined threshold. The proportion of monitoring time points at which PM0.5 is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  24. Weekly overall proportion of time with PM1 threshold exceeded

    Overall proportion of monitoring time per week during which PM1 threshold is exceeded. PM1 will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, PM1 will be compared with its respective predefined threshold. The proportion of monitoring time points at which PM1 is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  25. Weekly overall proportion of time with PM2.5 threshold exceeded

    Overall proportion of monitoring time per week during which PM2.5 threshold is exceeded. PM2.5 will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, PM2.5 will be compared with its respective predefined threshold. The proportion of monitoring time points at which PM2.5 is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  26. Weekly overall proportion of time with PM4 threshold exceeded

    Overall proportion of monitoring time per week during which PM4 threshold is exceeded. PM4 will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, PM4 will be compared with its respective predefined threshold. The proportion of monitoring time points at which PM4 is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  27. Weekly overall proportion of time with PM10 threshold exceeded

    Overall proportion of monitoring time per week during which PM10 threshold is exceeded. PM10 will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, PM10 will be compared with its respective predefined threshold. The proportion of monitoring time points at which PM10 is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  28. Weekly overall proportion of time with CO2 threshold exceeded

    Overall proportion of monitoring time per week during which the CO2 threshold is exceeded. CO2 will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, CO2 will be compared with its respective predefined threshold. The proportion of monitoring time points at which CO2 is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  29. Weekly overall proportion of time with VOC threshold exceeded

    Overall proportion of monitoring time per week during which the VOC threshold is exceeded. VOC will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, VOC will be compared with its respective predefined threshold. The proportion of monitoring time points at which VOC is exceeded will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  30. Weekly overall proportion of time with temperature threshold violated

    Overall proportion of monitoring time per week during which the temperature threshold is violated. The temperature will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, the temperature will be compared with its respective predefined threshold. The proportion of monitoring time points at which the temperature is violated will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  31. Weekly overall proportion of time with the relative humidity threshold violated

    Overall proportion of monitoring time per week during which the relative humidity threshold is violated. The relative humidity will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, the relative humidity will be compared with its respective predefined threshold. The proportion of monitoring time points at which the relative humidity is violated will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  32. Weekly overall proportion of time with ambient light (day) threshold violated

    Overall proportion of monitoring time per week during which the ambient light threshold is violated during the day-time hours. The ambient light will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, ambient light will be compared with its respective predefined threshold. The proportion of monitoring time points at which ambient light is violated during the day-time hours will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  33. Weekly overall proportion of time with ambient light (night) threshold violated

    Overall proportion of monitoring time per week during which the ambient light threshold is violated during the night-time hours. The ambient light will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, ambient light will be compared with its respective predefined threshold. The proportion of monitoring time points at which ambient light is violated during the night-time hours will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

  34. Weekly overall proportion of time with the ambient noise (night) threshold exceeded

    Overall proportion of monitoring time per week during which the ambient noise threshold is exceeded during night-time hours. The ambient noise will be monitored at predefined measurement intervals during the 1-month follow-up. For each measurement time point, the ambient noise will be compared with its respective predefined threshold. The proportion of monitoring time points at which ambient noise is exceeded during night-time hours will be calculated for each week.

    Time frame: Weekly during the 1-month follow-up

07

Study locations

1 site
08

References and documents

Publications

  • O'Connor L, Wang B, Ye Z, Behar S, Tarrant S, Stamegna P, Pretz C, Dunkel L, Savage B, Scornavacca T, Shirshac J, Wilkie T, Toomey S, Mullen M, Fisher K, Tigas E, Wong S, McManus DD, Alper E, Martinez F, Walkey A, Lindenauer PK, Dickson E, Broach JP, Kheterpal V, Soni A. Evaluation of an integrated digital and mobile intervention to improve outcomes for patients with moderate to severe COPD. NPJ Digit Med. 2025 Jul 17;8(1):451. doi: 10.1038/s41746-025-01871-0. PubMed 40676130 ↗
  • Shah AJ, Althobiani MA, Saigal A, Ogbonnaya CE, Hurst JR, Mandal S. Wearable technology interventions in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. NPJ Digit Med. 2023 Nov 27;6(1):222. doi: 10.1038/s41746-023-00962-0. PubMed 38012218 ↗
  • Hansel NN, McCormack MC, Belli AJ, Matsui EC, Peng RD, Aloe C, Paulin L, Williams DL, Diette GB, Breysse PN. In-home air pollution is linked to respiratory morbidity in former smokers with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2013 May 15;187(10):1085-90. doi: 10.1164/rccm.201211-1987OC. PubMed 23525930 ↗

Individual participant data

Plan to share: Yes

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 2, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07799896
Lead sponsor
Ziekenhuis Oost-Limburg
Collaborators
Maastricht University, University of Liege, Hasselt University, KU Leuven
Responsible party
Sponsor
First posted
Sep 2, 2026
Start date
Oct 1, 2026 (estimated)
Primary completion
Oct 2027 (estimated)
Completion
Oct 2027 (estimated)
Last update
Sep 2, 2026

Study contacts

Ruben Knevels, MsC
Contact
ruben.knevels@zol.be
+3289804029
Femke Wouters, PhD
Contact
femke.wouters@zol.be
David Ruttens, MD, PhD
principal investigator · Ziekenhuis Oost-Limburg

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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