Artificial Intelligence in Diagnosis of DFNA9

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Brief Title

Artificial Intelligence in Diagnosis of DFNA9

Official Title

Positive Predictive Value of Machine Learning Tools (Audiogene v4.0) for Diagnosing DFNA9 in a Large Series of p.Pro51Ser Variant Carriers in COCH.

Brief Summary

      To study the positive predictive value of Audiogene v.4.0 open source online machine learning
      tool in accurately predicting DFNA9 (DeaFNess autosomal dominant ninth) as top 3 gene loci in
      a large series of genetically confirmed c.151C>T,p.Pro51Ser (p.P51S) variant carriers in COCH
      (coagulation factor C Homology).
    

Detailed Description

      DFNA9 is an autosomal dominant hereditary adult-onset and progressive sensorineural hearing
      loss which is associated wit vestibular deterioration.

      Today, artificial intelligence plays an increasing role in diagnosis of Mendelian hearing
      losses and in fitting of cochlear implants. An application of this kind is the open source
      program, Audiogene v4.0, which was elaborated by the Center for Bioinformatics and
      Computational Biology, University of Iowa City, Iowa, USA. The shape of the audiogram
      (audioprofile) is easily recognizable in many autosomal dominantly inherited hearing losses.
      Machine learning based software tools, such as Audiogene v4.0, which was originally developed
      for prioritizing loci for the Sanger sequencing, could help the clinicians in early diagnosis
      of DFNA9. This tool only need subjects' age and hearing thresholds (decibel hearing loss (dB
      HL)) at frequency range of 0.125 - 8 kHz (kiloHerz), left, right or binaural average in order
      to predict top 3 gene loci according to the data entered in the program.

      Goal: to use auditory data of a large series of genetically confirmed p.P51S variant carriers
      causing DFNA9, which were previously collected for the genotype-phenotype correlation study
      which terminated recently.

      All individual left and right sided hearing thresholds (ranging from 0.125 to 8kHz, with the
      exception of 1.5 kHz) as well as binaural averaged thresholds were run through Audiogene
      v4.0.

      Descriptive statistics were assessed and statistical analysis was carried out to check for
      possible differences between age or hearing thresholds between the carrier group with
      accurate prediction against the carrier group with inaccurate prediction.
    


Study Type

Observational


Primary Outcome

hearing threshold


Condition

DFNA9

Intervention

Pure tone audiometry


Publications

* Includes publications given by the data provider as well as publications identified by National Clinical Trials Identifier (NCT ID) in Medline.

Recruitment Information


Recruitment Status

Diagnostic Test

Estimated Enrollment

111

Start Date

February 1, 2020

Completion Date

March 28, 2020

Primary Completion Date

March 28, 2020

Eligibility Criteria

        Inclusion Criteria:

          -  at least 18 years

          -  genetically confirmed c.151 C>T, p.Pro51Ser variant carrier in COCH gene

          -  not contra-indication for audiometric testing

        Exclusion Criteria:

          -  <18 years

          -  no carrier status for c.151C>T, p.Pro51Ser

          -  no auditory data available
      

Gender

All

Ages

18 Years - N/A

Accepts Healthy Volunteers

No

Contacts

Vincent Van Rompaey, MD,PhD, , 

Location Countries

Belgium

Location Countries

Belgium

Administrative Informations


NCT ID

NCT04331015

Organization ID

JessaH-5-ORL


Responsible Party

Sponsor

Study Sponsor

Jessa Hospital


Study Sponsor

Vincent Van Rompaey, MD,PhD, Study Director, University Hospital, Antwerp


Verification Date

April 2020