Intelligent Newborn Monitoring

  • Research type

    Research Study

  • Full title

    Intelligent Newborn Monitoring – A feasibility observational study to predict cardiorespiratory changes in neonatal patients

  • IRAS ID

    236429

  • Contact name

    Don Sharkey

  • Contact email

    don.sharkey@nottingham.ac.uk

  • Sponsor organisation

    University of Nottingham

  • Duration of Study in the UK

    2 years, 0 months, 0 days

  • Research summary

    There are over 60,000 babies born prematurely (before 37 weeks gestation) in the UK each year. Many are admitted to neonatal intensive care units (NICUs) and intensely monitored during their care. This monitoring includes routine observations such as their vital signs (heart rate, temperature, breathing rate) and the treatment they undergo such as amount of oxygen and ventilation they require.

    Very premature infants are prone to clinical deterioration which may take time to develop as the clinical signs become more obvious. This can delay treatment such as increased respiratory support or timely antibiotic treatment which may have an adverse effect on their short and long-term health. For example, premature babies with infections are twice as likely to have neurological problems as they grow up.

    Premature babies are often in hospital for many months. A baby born at 24 weeks gestation may stay in hospital for 4-6 months. During this time the clinical team collect a huge amount of patient data such as vital signs, blood tests and treatments. Experienced healthcare workers can use this information to identify patterns or behaviors in babies and so recognise when their clinical condition is deteriorating. However, this relies on experience and understanding the normal patterns for an individual baby.

    Our study will test if it is possible to train a computer to learn about an individual babies clinical course and identify when there is a change from the normal (well) pattern and hopefully identify the need to intervene sooner. This information could then guide treatment options and even automatically adjust treatments such as the ventilator settings. Early intervention could improve their short and long-term health. This pilot study will analyse routinely collected patient information, without changes to care, to then allow the computer systems to be trained.

  • REC name

    East Midlands - Nottingham 1 Research Ethics Committee

  • REC reference

    18/EM/0033

  • Date of REC Opinion

    4 Apr 2018

  • REC opinion

    Further Information Favourable Opinion