Artificial Intelligence in Diagnosis of DFNA9

NCT ID: NCT04331015

Last Updated: 2020-04-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

111 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-02-01

Study Completion Date

2020-03-28

Brief Summary

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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

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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.

Conditions

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DFNA9 Sensorineural Hearing Loss

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Interventions

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Pure tone audiometry

pure tone audiometry

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Jessa Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Vincent Van Rompaey, MD,PhD

Role: STUDY_DIRECTOR

University Hospital, Antwerp

Locations

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Jessa Hospital

Hasselt, Limburg, Belgium

Site Status

University of Antwerp

Antwerp, , Belgium

Site Status

Countries

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Belgium

References

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Taylor KR, Deluca AP, Shearer AE, Hildebrand MS, Black-Ziegelbein EA, Anand VN, Sloan CM, Eppsteiner RW, Scheetz TE, Huygen PL, Smith RJ, Braun TA, Casavant TL. AudioGene: predicting hearing loss genotypes from phenotypes to guide genetic screening. Hum Mutat. 2013 Apr;34(4):539-45. doi: 10.1002/humu.22268. Epub 2013 Feb 19.

Reference Type RESULT
PMID: 23280582 (View on PubMed)

Related Links

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Other Identifiers

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JessaH-5-ORL

Identifier Type: -

Identifier Source: org_study_id

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