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This study will find out if analysing heartbeat in babies with brain injury, based on standard clinical monitors, can inform treatment decisions and monitor stress levels in real time
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BACKGROUND
Hypoxic ischaemic encephalopathy (HIE) is the single most common cause of death and lifelong neurodisability in term babies. Although cooling treatment improves outcomes for these babies, early identification (within six hours of birth) of 'at risk infants' remains challenging. Consequently, not all babies who need treatment will receive it and other babies receive treatment unnecessarily. Furthermore, neuroprotection from cooling may be lost if baby remains stressed during treatment, but accurate methods of measuring stress in babies are lacking.
AIMS
Primary aim:
To examine the accuracy of heartbeat variability (HRV), within six hours of birth, to predict adverse neurodevelopmental outcome at 18 to 22 months in encephalopathic babies.
Secondary aims:
METHODS
A total 140 term babies with hypoxic ischaemic encephalopathy will be recruited. The investigators will collect continuous electrocardiography (ECG) data, hourly Neonatal Pain Agitation and Sedation Scale (NPASS) and 12 hourly salivary cortisol, for the first five days after birth. Various clinical interventions, and noise and light levels that the baby is exposed to, for the first 5 days after birth will be be recorded.
The investigators will analyse the raw ECG using Matlab® with in-house algorithms to quantify specific linear and non-linear measures of HRV. All recruited encephalopathic babies will have brain magnetic resonance (MR) imaging and spectroscopy using harmonised protocols and neurodevelopmental assessment, as a part of clinical care, or as a part of MR biomarker studies. This data will be collected and used for the Heartbeat study to examine the association between heart rate variability with brain injury and neurodevelopmental outcome.
In addition, the investigators will collect the ECG data from 100 healthy term babies for the first 24 hours after birth, to describe the trajectory of normal heartbeat variability in healthy term babies.
DATA ANALYSIS AND OUTCOME MEASURES
The prognostic accuracy (sensitivity, specificity, 95% confidence intervals) of early heartbeat variability using optimal cut-off values will be reported for the primary outcome. Logistic regression models adjusted for potential confounders will be used to report secondary outcomes.
POTENTIAL BENEFIT TO PATIENTS
Once the most accurate HRV indices and thresholds are identified, this data can be readily incorporated into a bed side real-time monitoring device. This device may have several clinical implications, including (i) improving access to treatment and the number of babies who benefit from being offered cooling; (ii) avoiding cooling therapy to low risk infants with hypoxic ischaemic encephalopathy (iii) maximising the therapeutic effect of cooling by reducing stress; (iv) enabling tailored neonatal nursing care based on real-time monitoring of neonatal stress and thus improving the long-term outcomes of babies with hypoxic ischaemic encephalopathy.
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Inclusion and exclusion criteria
HIE COHORT
Inclusion Criteria:
Exclusion Criteria:
HEALTHY COHORT
Inclusion criteria:
Exclusion criteria
210 participants in 2 patient groups
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Central trial contact
Ismita Chhetri, PhD; Sudhin S Thayyil
Data sourced from clinicaltrials.gov
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