Evaluation of the AudibleHealth Dx AI/ML-Based Dx SaMD Using FCV-SDS in the Diagnosis of COVID-19 Illness: Clinical Validation
Condition: 2019 Novel Coronavirus Disease; 2019 Novel Coronavirus Infection; 2019-nCoV Disease; COVID-19 Pandemic; COVID-19 Virus Disease; COVID-19 Virus Infection; Coronavirus Disease 2019; Coronavirus Disease-19; SARS-CoV-2 Infection
MeSH terms: Infections; Communicable Diseases; COVID-19; Virus Diseases; Coronavirus Infections
Study type: Observational

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

Detailed description: 
      The study is a prospective, multi-site, non-inferiority trial comparing the AudibleHealth Dx
      to FDA 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 and the
      "BioFire Respiratory 2.1 (RP2.1)" (brand name) test 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 the second RT-PCR results
      (if necessary for discordance) have been obtained. Results for the RT-PCR test will be
      received by the participant according to the clinical site's protocol.

      Target enrollment for this trial will be 65 COVID-19 positive cases and 152 COVID-19 negative
      cases, presuming a prevalence of 0.30 for a total of 217 subjects meeting all inclusion
      criteria.
    

Intervention name(s): Diagnostic Test: Diagnostic Software as Medical Device
Intervention type(s): Device
Intervention description(s): 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, specifically COVID-19 illness for this study.
Observational model: Case-Only
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        Adults seeking elective, outpatient COVID RT-PCR testing will be included.
      
Keywords: Delta; Omicron; FCV-SDS; Artificial Intelligence; Signal Data Signature; Forced Cough Vocalization; Dx SaMD; SaMD; Diagnostic Software as Medical Device; Software as Medical Device; AI/ML