Gestational Age Assessment Tool

NCT ID: NCT02534194

Last Updated: 2018-05-14

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 150 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2015-08-31
• Study Completion Date: 2018-05-11

Brief Summary

In the UK and worldwide many babies are born without carers knowing their gestation as the mothers will not have had good antenatal care. It is possible to estimate gestation but this requires a detailed clinical exam. The investigators wish to improve this by using software analysis to pick out features of the baby (face and foot) to try and estimate the gestation of the baby once it is born. The investigators will also look explore if the software can distinguish the normal face or a baby in discomfort.

Good estimation of gestation can result in more targeted management of the baby. The investigators will capture the images of newborn babies, from a variety of gestations, and use this dataset to teach the software to estimate gestational age and level of discomfort.

Detailed Description

Clinical techniques for the calculation of gestation include fetal ultrasound and clinical assessment tools, such as the Ballard Score, following birth. These techniques are rarely available (ultrasound which is expensive and requires trained users) or require significant training (Ballard) which makes them unsuitable for large scale assessment in many low-middle income (LMI) countries. In the UK, the gestational age of babies of mothers with no antenatal care requires a detailed clinical examination which can lack accuracy. Clinical assessment of postnatal gestational age utilises anatomical characteristics of the face, ear and foot during newborn development. There is an element of subjectiveness which reduces the precision of such an assessment which is only reduced with significant training and experience. Simpler techniques of postnatal gestational age assessment such as anthropometric measures are time consuming and lack the accuracy required. Emerging evidence suggests that gestational age can be calculated postnatally by measuring the newborn foot length and comparing to population appropriate charts. However, when used on their own, the specificity and sensitivity are still below acceptable limits to allow universal adoption.

New software-based analytical techniques now make it possible to perform fully automatic recognition of facial actions and dimensions. The investigators have developed techniques that allow live video facial feature identification and measurement using advanced analytical techniques of muscle actions. These techniques have been used for facial expression analysis as well as automated facial feature localization. The investigators propose that the same analysis could be used to create a unique gestational age assessment tool using a simple brief video clip of the newborns' face and foot.

Accurate assessment of gestational age, especially in LMI countries, could ensure high risk newborns receive appropriate low cost interventions to reduce morbidity and mortality. In the UK this could allow better estimation of babies born to mothers with no antenatal care where the gestational age is unclear. We propose a smartphone based, ethnic appropriate, combined face and foot video analysis tool to accurately determine gestational age of the newborn. Such a system could adapted to incorporate pain assessment tools to help inform treatment options and study new therapies.

Conditions

Immature Newborn; Premature Birth

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Newborn Infant

Newborn babies (within 7 days of birth) born between 23-42 weeks.

Image acquisition

Intervention Type: OTHER

Images of baby's face (including ear) and feet

Interventions

Image acquisition

Images of baby's face (including ear) and feet

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Where the baby's gestational age is known (based on antenatal care)
• With written informed parental consent.

Exclusion Criteria

• No parental consent
• Babies undergoing palliative care

• Maximum Eligible Age: 6 Months
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Bill and Melinda Gates Foundation

OTHER

Sponsor Role: collaborator

University of Nottingham

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Don Sharkey, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Nottingham

Locations

Nottingham University Hospitals NHS Trust

Nottingham, Nottinghamshire, United Kingdom

Countries

United Kingdom

Other Identifiers

15020

Identifier Type: -

Identifier Source: org_study_id