Neonatal brain injury has a heterogenous aetiology with a high economic and social burden. Neonatal encephalopathy describes the babies who require resuscitation at birth and have an abnormal neurological examination. It remains difficult to predict their developmental outcome. Enhanced inflammatory responses are seen in affected infants and correlate with outcomes. Multiorgan dysfunction is common with renal, hepatic, cardiac and haematological abnormalities.

The NIMBUS programme is funded by the HRB. Its primary research objectives are as follows:

Aim 1: Multiorgan dysfunction in Neonatal Encephalopathy

To standardise clinical multiorgan data collection and investigation in Neonatal encephalopathy in order to improve clinical outcomes and increase parent information. Organ-specific measurement of function will be established using a multidisciplinary expert group.

Aim 2: Inflammatory response in NE

To quantify inflammatory responses as biomarkers and also targets for disease modification.

To understand the detailed inflammatory response in infants with NE in order to develop translational therapies to improve neurological outcome as adjuncts to hypothermia.

Aim 3: Clinical and Biomarker Prognostic Indicators

To evaluate the associations between multiorgan outcome and neurological dysfunction.

To identify important variables that will eventually inform a bedside scoring system to estimate prognosis in the first days of life in an infant with NE. Inflammatory and organ-specific biomarkers may increase the predictive value of the clinical score to create an algorithm of prognostic outcome.

More information about NIMBUS

Please click here to see a list of the NIMBUS collaborative partners.

To learn more about NIMBUS research please read our following publications:

Coagulation Profiles Are Associated with Early Clinical Outcomes in Neonatal Encephalopathy.  Sweetman D, Kelly LA, Zareen Z, Nolan B, Murphy J, Boylan G, Donoghue V, Molloy EJ.

Neonatal Encephalopathy: Need for Recognition of Multiple Etiologies for Optimal Management.  Aslam S, Strickland T, Molloy EJ.

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