Predicting Infant Extubation Using Diaphragm Surface Electromyography
Research type
Research Study
Full title
Predicting Infant Extubation Using Diaphragm Surface Electromyography
IRAS ID
205807
Contact name
Anne Greenough
Contact email
Duration of Study in the UK
1 years, 0 months, 1 days
Research summary
A significant proportion of babies admitted to the neonatal unit require support by a ventilator for their breathing problems. A prolonged period of time spent on a ventilator may lead to complications, but taking a baby off a ventilator too early can also lead to issues – currently, around 25% will need to go back onto a ventilator within 48 hours. This involves invasive procedures such as reintubation, which carry risks for the baby. Correctly identifying the time at which babies are ready to come off the ventilator is key to improving care.
There have been several previous studies of ways to predict when babies might be ready to come off a ventilator, but none have been better than the clinical information (for example postnatal age, level of ventilator support, etc) and judgement currently used in routine care. Measurement of the electrical activity of the diaphragm muscle, (measured by sensors on a special feeding tube inserted through the mouth or nose into the stomach) has shown promise in older children and adults. A new, less invasive way of detecting this activity has become available using sensors that are placed on the infant's chest. We will use this to see if measurement of the electrical signal to the diaphragm muscle can improve our prediction of when infants are ready to be taken off the breathing machine, and therefore avoid both unnecessarily prolonged ventilation or the need for reintubation in this vulnerable population.
REC name
London - Camden & Kings Cross Research Ethics Committee
REC reference
16/LO/1281
Date of REC Opinion
16 Aug 2016
REC opinion
Further Information Favourable Opinion