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A Pilot Study for the Collection Of Vocalized, Individual Digital Cough Sound Recordings to Screen for COVID-19 (COVID-Cough)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04864535
Recruitment Status : Active, not recruiting
First Posted : April 29, 2021
Last Update Posted : March 30, 2023
Sponsor:
Collaborators:
Strategy Health LLC
Ascada Health PC DBA
Information provided by (Responsible Party):
ResApp Health Limited

Brief Summary:
Decentralized clinical study designed to collect cough sounds and self-reported symptoms alongside a COVID-19 realtime quantitative polymerase chain reaction (rt-qPCR) test. The aim of the data collection is to develop a safe and effective cough based digital screening tool for COVID-19.

Condition or disease Intervention/treatment
Covid19 Diagnostic Test: Recordings of cough sounds from adults

Show Show detailed description

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Study Type : Observational
Estimated Enrollment : 1500 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: A Pilot Study for the Collection Of Vocalized, Individual Digital Cough Sound Recordings to Screen for COVID-19
Actual Study Start Date : May 12, 2021
Estimated Primary Completion Date : April 30, 2023
Estimated Study Completion Date : May 31, 2023

Resource links provided by the National Library of Medicine



Intervention Details:
  • Diagnostic Test: Recordings of cough sounds from adults
    Smartphone recordings of the cough sounds of participants who enrol in the study and obtain a COVID-19 rt-qPCR result.


Primary Outcome Measures :
  1. Collection of cough sound recordings and self-reported symptoms from a minimum of 100 COVID-19 positive participants as identified by rt-qPCR. [ Time Frame: 3 months ]
    Cough sound recordings and symptoms from COVID-positive patients

  2. Development of an algorithm that uses a combination of cough sounds and self-reported symptoms that is capable of distinguishing between COVID-19 positive and COVID-19 negative participants. [ Time Frame: 3 months ]
    Cough sound algorithm that distinguishes with COVID-19 positive and negative cough sounds.


Secondary Outcome Measures :
  1. Development of an algorithm that uses cough sounds that is capable of distinguishing between COVID-19 positive and COVID-19 negative participants. [ Time Frame: 3 months ]
    Algorithm for software application to distinguish between COVID-19 positive and negative coughs


Other Outcome Measures:
  1. Development of an algorithm that uses a combination of cough sounds and patient-reported symptoms that is capable of predicting rt-qPCR Ct value for a participant. [ Time Frame: 3 months ]
    Algorithm could predict similar result to a rt-qPCR Ct value



Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


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Ages Eligible for Study:   21 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population

A minimum of 100 participants who test positive for COVID-19 on rt-qPCR will be recruited. Based on average COVID-19 incidence rates in high incidence US geographies (~8-12%), this study will enrol a cohort of up to 1500 participants on a rolling basis, to allow for sufficient cough recordings from COVID-19 positive participants to be collected for analysis.

Participants will be aged 21 years and older and will not be excluded based on gender, demographic group, or geographic location within the US.

Criteria

Inclusion Criteria:

  • be aged 21 years and older;
  • be a resident of the USA;
  • have a personal (i.e., not shared) iPhone 6s or newer running iOS 14 or later;
  • be able to read and understand English;
  • be able to provide informed consent;
  • be able to provide at least 5 coughs (voluntary and/or spontaneous);
  • if enrolling online in Arm 1, the participant must be unvaccinated against COVID-19 (have not received one or more doses of a COVID-19 vaccine at any time before study enrolment)

Exclusion Criteria:

  • have one or more medical contraindication to voluntary cough, including the following:

    • Severe respiratory distress;
    • History of pneumothorax;
    • Eye, chest, or abdominal surgery within 3 months of enrolling for the study; or
    • Hemoptysis (coughing up of blood) within 1 month of enrolling for the study;

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04864535


Locations
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United States, New York
Strategy Health LLC
New York, New York, United States, 10024
Sponsors and Collaborators
ResApp Health Limited
Strategy Health LLC
Ascada Health PC DBA
Investigators
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Principal Investigator: Shrawan Patel, MBBS BSc Strategy Health LLC
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Responsible Party: ResApp Health Limited
ClinicalTrials.gov Identifier: NCT04864535    
Other Study ID Numbers: 21001
First Posted: April 29, 2021    Key Record Dates
Last Update Posted: March 30, 2023
Last Verified: February 2023
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by ResApp Health Limited:
COVID-19
Cough
Additional relevant MeSH terms:
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COVID-19
Pneumonia, Viral
Pneumonia
Respiratory Tract Infections
Infections
Virus Diseases
Coronavirus Infections
Coronaviridae Infections
Nidovirales Infections
RNA Virus Infections
Lung Diseases
Respiratory Tract Diseases