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Routine full blood counts in pregnancy to improve maternal and child health (Prof. Nathalie Conrad)

PROJECT TITLE

Routine full blood counts in pregnancy to improve maternal and child health.

SUPERVISORS

  • Prof. Nathalie Conrad

DESCRIPTION OF PROJECT

Full blood count (FBC) testing is commonly performed in pregnancy to screen for anaemia, infections, and haematological disorders. Despite its common use, interpretation relies on broad pregnancy reference intervals that do not account for individual characteristics or predict future health.

The availability of linked electronic health records for millions of pregnancies provides an opportunity to redefine how routine FBCs are interpreted, enabling more personalised assessment of maternal physiology, early identification of women at risk of adverse outcomes, and discovery of novel biomarkers of placental and fetal health.

This project will evaluate the clinical utility of routine full blood counts (FBCs) during pregnancy using population-scale linked electronic health records with the aim to:

  • Develop personalised pregnancy-specific reference intervals for routine FBC parameters according to gestational age, maternal characteristics, and pregnancy factors.
  • Determine whether routine first-trimester FBCs can improve the prediction of adverse maternal outcomes, including pregnancy complications and long-term cardiovascular disease.
  • Identify novel associations between first-trimester FBC profiles and placental function, fetal growth, neonatal outcomes, and longer-term child health to uncover previously unrecognised biological pathways and opportunities for early intervention.

This project is expected to refine the interpretation of routine full blood counts during pregnancy by developing personalised reference intervals, identifying novel haematological markers of maternal and offspring health, and improving early risk stratification for adverse pregnancy and long-term cardiovascular outcomes.

The analysis will use large-scale linked electronic health record data from sources such as CPRD, alongside cohort data from UK and international biobanks. The project will require skills in epidemiology and biostatistics, including survival analysis, risk prediction modelling, and model validation, as well as experience working with large-scale biomedical datasets. 

TRAINING OPPORTUNITIES

The DPhil student will receive advanced training in epidemiological methods, data processing and data analysis for large-scale biomedical datasets, and biostatistics.

Further to that, the DPhil student will receive training in systematic literature reviews, scientific writing, presentation skills, and will work with a strong inter-disciplinary team of epidemiologists, cardiologists, and statisticians to conduct high-quality research.

Funding Information

The position is not currently funded, however, we will assist the DPhil candidate in securing funding. 

HOW TO APPLY

To apply for this research degree, please click here.