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OpenTrials
Completed

NCT Number: NCT05175690

Evaluation of the AudibleHealth Dx AI/ML-Based Dx SaMD Using FCV-SDS in the Diagnosis of COVID-19 Illness

The AudibleHealth Dx is a diagnostic software as a medical device (Dx SaMD) consisting of an ensemble of software subroutines that interacts with a proprietary database of Signal Data Signatures (SDS), using Artificial Intelligence/Machine Learning (AI/ML) to analyze forced cough vocalization signal data signatures (FCV-SDS) for diagnostic purposes.

This study will evaluate the performance of the AudibleHealth Dx in comparison to a standard of care Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test for the diagnosis of COVID-19. Bidirectional Sanger sequencing will be used to reduce the rate of false negative and false positive results.

A secondary purpose of the study will be usability testing of the device for participants and providers.

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Key information

Conditions

Covid19 COVID-19 Cardiomyopathy, Dilated, 1C Coronaviridae Infections Coronavirus Infections Infections Lung Diseases Nidovirales Infections Pneumonia Pneumonia, Viral RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Virus Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University of South Florida

Tampa, Florida, 33612, United States

About this study

The study is a prospective, multi-site, non-inferiority trial comparing the AudibleHealth Dx to Emergency Use Authorization (EUA) approved COVID-19 RT-PCR testing to demonstrate non-inferiority of the PPA and NPA when using this device to diagnose COVID-19 illness. The AudibleHealth Dx test, the "Xpert Xpress SARS-CoV-2 RT-PCR" (brand name) test, and bidirectional Sanger sequencing will be performed for each participant during a single encounter. Participants and staff will be blinded to AudibleHealth Dx results and the RT-PCR status at the time of testing. No one will know both results in real-time except for the Site Coordinators and unblinded statistician specifically authorized to have these results for enrollment, audit, data tracking, and data compiling purposes. Unblinding of the results will occur after the AudibleHealth Dx, RT-PCR, and variant sequencing results have been obtained. Results for the RT-PCR test will be received by the participant according to the clinical site's protocol. Variant sequencing results will be handled by each site according to their protocol.

Target enrollment for this trial will be 65 COVID-19 positive cases and 247 COVID-19 negative cases, presuming a prevalence of 0.17 for a total of 312 subjects meeting all inclusion criteria.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Male or Female, 18 years of age or older
  • Present for elective, outpatient COVID-19 RT-PCR testing
  • Meet the FDA EUA approved indications for use for the RT-PCR nasal swab test for COVID-19
  • Stated willingness to comply with all trial procedures and availability for the duration of the trial
  • Informed consent must be obtained prior to testing

Exclusion criteria

  • Less than 18 years of age
  • Unable to cough voluntarily
  • Present with acute traumatic injury to the head, neck, throat, chest, abdomen or trunk
  • Patent tracheostomy stoma
  • Recent chest/abdomen/trunk trauma or surgery, recent/persistent neurovascular injury or recent intracranial surgery
  • Medical history of cribriform plate injury or cribriform plate surgery, diaphragmatic hernia, external beam neck/throat/maxillofacial radiation, phrenic nerve injury/palsy, radical neck/throat/maxillofacial surgery, vocal cord trauma or nodules
  • Since persons with aphasia may have difficulty in producing an FCV-SDS in the time allotted by the app, this population also will be excluded from the current trial

Treatment and study plan

Diagnostic Software as Medical Device

Diagnostic Test

AudibleHealth Dx is an investigational Dx SaMD consisting of an ensemble of software subroutines that interacts with a proprietary database of signal data signatures (SDS) using Artificial Intelligence/Machine Learning (AI/ML) to analyze forced cough vocalization signal data signatures (FCV-SDS) for diagnostic purposes. The intended use for the AudibleHealth Dx AI/ML-based Dx SaMD using FCV-SDS is for the diagnosis of acute and chronic illnesses.

The AudibleHealth Dx is a cloud-based AI/ML (locked ML) diagnostic software as medical device (Dx SaMD) with a mobile app based graphical user interface (GUI) designed to operate with COTS Android Operating System (OS) and Apple OS based mobile devices. The AudibleHealth Dx system uses a forced cough vocalization (FCV) signal data signature (SDS) to diagnose COVID-19 illness in ambulatory adults. Results are sent to ordering physicians, State Health Departments, and participants using Health Level 7 (HL7) compliant communication protocols.

Other names: Dx SaMD, AudibleHealth Dx

Primary outcomes

  1. Non-inferiority of the positive percent agreement (PPA)

    Time frame: Participants will have a single encounter lasting less than one hour; anticipated study duration is 6 weeks. Target enrollment is 65 positive and 247 negative participants. (Interim analysis will be conducted at the halfway point.)

    To demonstrate non-inferiority of the positive percent agreement (PPA) of the AudibleHealth Dx when compared to EUA approved COVID-19 RT-PCR testing (specifically the Xpert Xpress SARS-CoV-2 RT-PCR test for the diagnosis of COVID-19 illness.)

  2. Non-inferiority of the negative percent agreement (NPA)

    Time frame: Participants will have a single encounter lasting less than one hour; anticipated study duration is 6 weeks. Target enrollment is 65 positive and 247 negative participants. (Interim analysis will be conducted at the halfway point.)

    To demonstrate non-inferiority of the negative percent agreement (NPA) of the AudibleHealth Dx when compared to EUA approved COVID-19 RT-PCR testing (specifically the Xpert Xpress SARS-CoV-2 RT-PCR test for the diagnosis of COVID-19 illness.)

Sponsors and collaborators

Lead sponsor

AudibleHealth AI, Inc.

Industry

Collaborators

  • Analytic Solutions Group
  • Medical & Regulatory Affairs Specialists, LLC
  • R. P. Chiacchierini Consulting, LLC
  • Renaissance Worldwide Solutions, LLC
  • University of South Florida

Registry information

Official study title

Evaluation of the Artificial Intelligence/Machine Learning-Based Diagnostic Software as a Medical Device Using Forced Cough Vocalization Signal Data Signatures in the Diagnosis of COVID-19 Illness

Important dates

Study start
2022
Primary completion
2022
Study completion
2022
First posted
Jan 4, 2022
Registry last updated
May 5, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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