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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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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

Conditions
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COVID19

Intervention / Treatment
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* Diagnostic Test: Diagnostic Software as Medical Device


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Trial Population<br>The trial population will be enrolled from adults presenting for elective, outpatient COVID-19 testing at a single center, potentially with multiple testing locations (subject to local needs at the time of the trial). The investigational device will be provided to Participants via a cell phone preloaded with Common off-the-shelf original equipment manufacturer (COTS OEM) software and the investigational Dx SaMD. The investigational device will be evaluated during a single encounter in which an FCV-SDS will be collected. No follow-up visits or participant contacts will be involved in this trial. | Diagnostic Test: Diagnostic Software as Medical Device<br>* 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.<br>* Other names: AudibleHealth Dx;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Non-inferiority of the positive percent agreement (PPA) | 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.) | 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.) | 
| Non-inferiority of the negative percent agreement (NPA) | 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.) | 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.) | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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FCV, 2019 Novel Coronavirus Disease, 2019 Novel Coronavirus Infection, 2019-nCoV Disease, 2019-nCoV Infection, COVID-19 Pandemic, COVID-19 Pandemics, COVID-19 Virus Disease, COVID-19 Virus Infection, Coronavirus Disease 2019, Coronavirus Disease-19, SARS Coronavirus 2 Infection, SARS-CoV-2 Infection, Severe Acute Respiratory Syndrome Coronavirus 2 Infection, SARS-CoV-2, Software as Medical Device, Diagnostic Software as Medical Device, SaMD, Dx SaMD, Forced Cough Vocalization, Signal Data Signature, SDS, FCV-SDS, Delta, Omicron, Artificial Intelligence, Machine Learning, AI, ML, AI/ML, Classifier, Convolutional Neural Network, CNN, Recurrent Neural Network, RNN, Oracle, Ensemble