Epidemiology of Intrapartum-related Neonatal Encephalopathy: Exploring Prevalence and Predictors of Outcomes Globally

Complications around the time of birth leading to newborn brain injury, known as 'Intrapartum-related Neonatal Encephalopathy' (NE), is a leading cause of child death and disability worldwide. The global agenda focuses on the need for children not only to 'survive' but 'thrive'. Data is limited on the prevalence of adverse outcomes (death or disability) after NE particularly in low- and middle- income countries (LMICs). Challenges exist in identifying those most at risk of death or disability who may benefit from targeted interventions. Existing clinical risk scores (comprising a variety of neonatal clinical characteristics) have limited applicability in LMIC settings.

This PhD project aims to explore the prevalence, and predictors, of adverse outcomes (death and disability) after NE globally, and develop a novel score to predict risk of adverse outcomes applicable for use in LMICs.

The specific PhD objectives and methodologies are:

Objective 1: Systematic review and meta-analysis of published and unpublished global data to determine prevalence, and predictors, of adverse outcomes (death and disability =/+18 months) after NE.
i) Conduct a literature search using terms related to Neonatal Encephalopathy; limit publication date to 1 November 2012 onwards (since the last global systematic review by Lee et al 2013). Extract data on prevalence, and predictors, of adverse outcomes (death and disability =/+18 months) after NE. Stratify results by NE definition, country classification by income (as per World Bank), and cooling intervention status.
ii) Identify sources of unpublished data (including national networks, cooling cohorts/ registers) through the literature review and professional networking; contact investigators for relevant data on prevalence and predictors of adverse outcomes after NE.
iii) Combine comparable published and unpublished data in random-effects meta-analysis.

Objective 2: Develop a novel risk score to identify those at highest risk of adverse outcomes after NE, applicable for use in LMICs.
i) Derive the model from a sample of 240 Ugandan infants with NE (Baby BRAiN and ABAaNA studies, Uganda), and additional cohorts identified through objective 1. Identify potential candidate variables through literature review (objective 1) which will comprise maternal and neonatal sociodemographic/ clinical characteristics. Include variables in a complete multivariable model, progressively simplified using reverse stepwise selection.
ii) Internally validate the risk score using bootstrap resampling of the development sample.

Objective 3: Assess the feasibility and acceptability of the novel risk score amongst healthcare workers (HCWs) in LMIC contexts.
i) Create a novel web-based risk calculator using the R computer software, to enable entering of patient-specific data and calculation of individualised risk of adverse outcomes after NE.
ii) Train a sample of healthcare workers (e.g. from the ongoing NEST360 study in sub-Saharan Africa) to administer the score using the web-based calculator, in high-risk neonates. Utilise mixed qualitative and quantitative methods to evaluate feasibility and acceptability amongst HCWs.

Objective 4: Explore the additional value of brain imaging and novel biomarkers in predicting adverse outcomes after NE.
i) Utilising data from the baby BRAiN study, describe findings from cranial ultrasound including resistive indices (N=51), magnetic resonance imaging (N=27), and magnetic resonance spectroscopy (N=24), and evaluate associations with adverse outcomes after NE (N=40), using regression modelling.
ii) Utilising data from the ABAaNA study, evaluate associations between cranial ultrasound patterns of injury (N=184) and adverse outcomes after NE using regression modelling.
iii) Utilising stored serum samples from the baby BRAiNS and ABAaNA studies (N= 250), evaluate associations between early metabolomic and proteomic profiles (birth-day 2), and adverse outcomes