Monitoring Coughs for the Early Detection of Worsening COPD

NCT07212439 | Recruiting

• 1 other identifier: Hyfe-EPOC
• Study Type: observational
• Target: 50
• Locations: 1 country
• Sites: 3

Brief Summary

This study is for adults with COPD. Flare-ups of COPD, also known as exacerbations, can be serious and lead to hospital stays. The purpose of this research is to see if continuously and automatically monitoring a person's coughs can help predict these flare-ups early, before they become severe. Participants will use the Hyfe cough monitoring system, which includes a watch-like device worn on the wrist and a smartphone application. The system privately counts the number of coughs without recording any audio. Participants will also answer a short, weekly questionnaire about their COPD symptoms. This is an observational study, which means it will not change the regular medical care a participant receives. The participants and their care providers will not see the cough counts. The doctor will continue to manage their COPD as usual.

Conditions

Chronic Obstructive Pulmonary Disease (COPD)

Keywords

COPD; COPD Exacerbation; Cough; Cough Monitoring; Hyfe; Early Detection; Wearable Device; Artificial Intelligence; Observational Study

Outcome Measures

Primary Outcomes (1)

• Predictive accuracy of Hyfe cough monitoring for COPD exacerbations

  (a) Positive predictive value (PPV) by time to exacerbation vs standard of care (SoC) (b) False positive and false negative rates by time to exacerbation vs SoC

  Up to 1 year

Secondary Outcomes (4)

• Predictive accuracy: continuous vs. nighttime-only cough monitoring

  Up to 1 year

• Predictive accuracy: cough data vs. combined cough and symptom data

  Up to 1 year

• Estimated potential cost savings

  Up to 1 year

• Usability and acceptability of the Hyfe monitoring system

  Up to 1 year

Study Arms (2)

Inpatients

This cohort consists of patients with a confirmed COPD diagnosis who are currently hospitalized due to a severe COPD exacerbation.

Outpatients

This cohort includes outpatients with a COPD diagnosis who are being seen for routine follow-up. To be included, these patients must have a history of at least one exacerbation in the past 12 months.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study will enroll adult participants with a confirmed diagnosis of COPD. The population is composed of two distinct groups: inpatients who are currently hospitalized for a moderate/severe COPD exacerbation, and outpatients attending routine follow-up who are selected to enrich the sample with individuals who experience frequent exacerbations.

You may qualify if:

• Must be 18 years of age or older.
• Must have an existing diagnosis of COPD.
• For the inpatient cohort, participants must be currently assessed as having a moderate/severe exacerbation.
• For the outpatient cohort, participants must have had at least one exacerbation of any severity in the last 12 months.
• For the outpatient cohort, at least one month must have passed since the last exacerbation.

You may not qualify if:

• Individuals who are unable to provide informed consent.
• Individuals who are unable to adhere to study procedures.
• For the inpatient cohort, individuals requiring invasive or non-invasive ventilation.
• Individuals who live with a person who has a chronic cough.

Sponsors & Collaborators

• Clinica Universidad de Navarra, Universidad de Navarra: lead
• Hyfe Inc: collaborator

Study Sites (3)

Clinica San Miguel

Pamplona, Navarre, 31006, Spain

RECRUITING

Clínica Universidad de Navarra, Universidad de Navarra

Pamplona, Navarre, 31008, Spain

RECRUITING

Servicio Navarro de Salud

Pamplona, Navarre, 31008, Spain

RECRUITING

Related Publications (10)

• Mackay AJ, Donaldson GC, Patel AR, Jones PW, Hurst JR, Wedzicha JA. Usefulness of the Chronic Obstructive Pulmonary Disease Assessment Test to evaluate severity of COPD exacerbations. Am J Respir Crit Care Med. 2012 Jun 1;185(11):1218-24. doi: 10.1164/rccm.201110-1843OC. Epub 2012 Jan 26.

  PMID: 22281834 BACKGROUND

• Folch Ayora A, Macia-Soler L, Orts-Cortes MI, Hernandez C, Seijas-Babot N. Comparative analysis of the psychometric parameters of two quality-of-life questionnaires, the SGRQ and CAT, in the assessment of patients with COPD exacerbations during hospitalization: A multicenter study. Chron Respir Dis. 2018 Nov;15(4):374-383. doi: 10.1177/1479972318761645. Epub 2018 Mar 12.

  PMID: 29529879 BACKGROUND

• Jones PW, Brusselle G, Dal Negro RW, Ferrer M, Kardos P, Levy ML, Perez T, Soler Cataluna JJ, van der Molen T, Adamek L, Banik N. Properties of the COPD assessment test in a cross-sectional European study. Eur Respir J. 2011 Jul;38(1):29-35. doi: 10.1183/09031936.00177210. Epub 2011 May 12.

  PMID: 21565915 BACKGROUND

• Kim V, Aaron SD. What is a COPD exacerbation? Current definitions, pitfalls, challenges and opportunities for improvement. Eur Respir J. 2018 Nov 15;52(5):1801261. doi: 10.1183/13993003.01261-2018. Print 2018 Nov.

  PMID: 30237306 BACKGROUND

• Gabaldon-Figueira JC, Keen E, Rudd M, Orrilo V, Blavia I, Chaccour J, Galvosas M, Small P, Grandjean Lapierre S, Chaccour C. Longitudinal passive cough monitoring and its implications for detecting changes in clinical status. ERJ Open Res. 2022 May 16;8(2):00001-2022. doi: 10.1183/23120541.00001-2022. eCollection 2022 Apr.

  PMID: 35586452 BACKGROUND

• Gabaldon-Figueira JC, Keen E, Gimenez G, Orrillo V, Blavia I, Dore DH, Armendariz N, Chaccour J, Fernandez-Montero A, Bartolome J, Umashankar N, Small P, Grandjean Lapierre S, Chaccour C. Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence. ERJ Open Res. 2022 May 30;8(2):00053-2022. doi: 10.1183/23120541.00053-2022. eCollection 2022 Apr.

  PMID: 35651361 BACKGROUND

• Chung KF, Chaccour C, Jover L, Galvosas M, Song WJ, Rudd M, Small P. Longitudinal Cough Frequency Monitoring in Persistent Coughers: Daily Variability and Predictability. Lung. 2024 Oct;202(5):561-568. doi: 10.1007/s00408-024-00734-x. Epub 2024 Jul 31.

  PMID: 39085518 BACKGROUND

• Chaccour C, Sanchez-Olivieri I, Siegel S, Megson G, Winthrop KL, Botella JB, de-Torres JP, Jover L, Brew J, Kafentzis G, Galvosas M, Rudd M, Small P. Validation and accuracy of the Hyfe cough monitoring system: a multicenter clinical study. Sci Rep. 2025 Jan 6;15(1):880. doi: 10.1038/s41598-025-85341-3.

  PMID: 39762316 BACKGROUND

• den Brinker AC, Thackray-Nocera S, Crooks MG, Morice AH. Improved Precision of COPD Exacerbation Detection in Night-Time Cough Monitoring. J Pers Med. 2025 Aug 2;15(8):349. doi: 10.3390/jpm15080349.

  PMID: 40863411 BACKGROUND

• Morice AH, den Brinker AC, Crooks M, Thackray-Nocera S, Ouweltjes O, Rietman R. Can Passive Cough Monitoring Predict COPD Exacerbations? COPD. 2025 Apr 4;22(1):2487909. doi: 10.1080/15412555.2025.2487909. Epub 2025 Apr 14.

  PMID: 40223505 BACKGROUND

MeSH Terms

Conditions

Pulmonary Disease, Chronic Obstructive; Cough

Condition Hierarchy (Ancestors)

Lung Diseases, Obstructive; Lung Diseases; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Respiration Disorders; Signs and Symptoms, Respiratory; Signs and Symptoms

Central Study Contacts

Carlos J. Chaccour, MD, PhD

CONTACT

+34 666 293 112; cchaccour@unav.es

Fhabián S. Carrión-Nessi, MD, MSc

CONTACT

+58 424 958 80 43; fhabiancarrion@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Year
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 30, 2025
• First Posted: October 8, 2025
• Study Start: October 29, 2025
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): September 1, 2026
• Last Updated: January 2, 2026

Record last verified: 2025-09

Data Sharing

• IPD Sharing: Will not share

Locations

ES (3)