Evaluating Face-Recognition Technology in Syndrome Diagnosis

NCT04709965 | Completed

• 1 other identifier: R04765
• Study Type: interventional
• Target: 111
• Locations: 1 country
• Sites: 1

Brief Summary

Birth defects are relatively common, occurring in 1 in 40 live born babies. They can be single, or multiple. They may occur as part of multiple malformation syndromes, often in association with growth disturbance or intellectual disability. Over 7000 rare syndromes have been identified. Thus, though they are rare they are collectively important. Understanding how a multiple malformation syndrome came about, defining what investigations and health surveillance is needed for affected children and identifying whether there is a treatment is very important for parents and professionals caring for affected children and also for genetic counselling of their extended families, since the majority will have a genetic basis. Diagnosis of these rare disorders is therefore important,but as many syndromes are rare this can be extremely difficult and requires specialist knowledge, many investigations and many hospital appointments. This study aims to determine whether using face-recognition software can improve diagnosis of rare syndromes when used in addition to current routine practice.

Conditions

Multiple Anomalies; Dysmorphic Features; Inborn Errors of Metabolism

Outcome Measures

Primary Outcomes (2)

• Number of diagnoses

  The number of diagnoses of rare syndrome disorders made, measured after standard practice

  through study completion, an average of 2 years

• Number of diagnoses

  The number of diagnoses of rare syndrome disorders made, Measured after use of the Face2Gene app

  through study completion, an average of 2 years

Secondary Outcomes (3)

• Patient satisfaction

  6 months after recruitment.

• Professional satisfaction

  24 months

• Number of syndromes

  24 months

Study Arms (2)

Main Study

OTHER

Patients attending routine genetic clinic/paediatric clinic appointments for diagnosis of a multiple anomaly syndrome where distinctive facial features form part of their presenting pattern.

Diagnostic Test: Face2Gene

Faces Sub Study

OTHER

Patients eligible to be recruited to the Faces Sub Study will have biochemically or genetically confirmed diagnosis of inborn disorder of metabolism where no well described dysmorphic facial features are known to be associated with disorder.

Diagnostic Test: Face2Gene

Interventions

Face2Gene DIAGNOSTIC_TEST

This study investigates whether a new diagnostic intervention (Face2Gene facial recognition software) is better than using standard approach to diagnosis.

Faces Sub Study; Main Study

Eligibility Criteria

• Age: 8 Months+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• \- Patients attending routine genetic clinic/paediatric clinic appointments for diagnosis of a multiple anomaly syndrome where distinctive facial features form part of their presenting pattern.
• OR:
• \- Biochemically or genetically confirmed diagnosis of inborn disorder of metabolism where no well described dysmorphic facial features are known to be associated with disorder

You may not qualify if:

• Patients under 8 months of age where face-recognition technology has not been shown to be effective.
• Patients who decline clinical photography as part of standard care.
• Patients who do not wish to consent to participation in the study even though they consent to photos being taken for standard care.

Sponsors & Collaborators

• Manchester University NHS Foundation Trust: lead
• FDNA Inc.: collaborator

Study Sites (1)

Manchester University NHS Foundation Trust

Manchester, Greater Manchester, M13 9WL, United Kingdom

Location

MeSH Terms

Conditions

Abnormalities, Multiple; Metabolism, Inborn Errors

Condition Hierarchy (Ancestors)

Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Genetic Diseases, Inborn; Metabolic Diseases; Nutritional and Metabolic Diseases

Study Officials

• Sofia Douzgou, MD PhD FRCP

  Manchester University NHS Foundation Trust

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER GOV
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 3, 2020
• First Posted: January 14, 2021
• Study Start: January 30, 2018
• Primary Completion: November 25, 2020
• Study Completion: November 25, 2020
• Last Updated: January 14, 2021

Record last verified: 2021-01

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)