Pregnancy-induced hypertension (PIH) affects 5-10% of all pregnant women worldwide and is associated with chronic kidney disease (CKD) and/or gestational diabetes. In the United Kingdom (UK), about 16 out of every 100 pregnant women will develop gestational diabetes. Between 2015 and 2017, about 9.6 women per 100,000 died during pregnancy. In 2016, women aged 35 and over had a higher prevalence of CKD compared to men (17% vs 12%).
Research has reported that women with gestational diabetes have 6.1 higher rates of pre-eclampsia and up to nine-fold increased risk of CKD. Moreover, women who had pre-eclampsia have 4.9 higher risk of end-stage kidney disease and 3.6 times higher in women who had gestational hypertension.
The overall objective of this study is to use Hospital Episode Statistic (HES)-linked Clinical Practice Research Datalink (CPRD) data to conduct a descriptive cohort study to describe the associations between PIH (pre-eclampsia), gestational diabetes, and CKD in women aged 18 or older with a diagnosis of PIH (pre-eclampsia) in their first known pregnancy. We will investigate women’s risk of developing CKD when they experience PIH or gestational diabetes.
Means and standard deviations will be used to produce and describe changes, generalized linear models (GLM) will be used to describe participant’s baseline characteristics. Cox proportional hazards regression models will be used to investigate the associations between PIH (pre-eclampsia), gestational diabetes, and the risk of CKD. Baseline will start from 1st January 1998 and participants will be censored at the date of CKD diagnosis, death, or end of the study period, defined as the last date of follow-up or 31 December 2019, whichever comes first.
Kaplan-Meier curves will be fitted to compare the association between PIH (pre-eclampsia), gestational diabetes, and risk of CKD. PIH (pre-eclampsia) will be treated as time-varying during the follow-up time.
Chronic Kidney Disease. It will be the primary outcome, defined by recorded diagnoses of chronic kidney disease, as well as measures of the estimated glomerular filtration rate, using SNOMEDCT codes.
Deirdre Lane - Chief Investigator - University of Liverpool
Jose Ignacio Cuitun Coronado - Corresponding Applicant - University of Liverpool
Deirdre Lane - Collaborator - University of Liverpool
Gregory Lip - Collaborator - University of Liverpool
Pieta Schofield - Collaborator - University of Liverpool
Stephanie Harrison - Collaborator - University of Liverpool
Tariq Al Bahhawi - Collaborator - University of Liverpool