It is difficult to study the effects of drugs and vaccines during pregnancy in the traditional clinical trial setting due to the potential risks for the mother and unborn child. Existing patient anonymised clinical care records represent an opportunity to answer important questions about exposures during pregnancy and potentially associated outcomes (for example an early pregnancy loss). To facilitate this, a register of pregnancies identified in the anonymised CPRD primary care database, which includes information on the start of each pregnancy and its outcomes, has been created. However, there are a significant number of pregnancies in the Register for which no outcome has been identified. These pregnancies are of limited use for research. If we do not know whether the pregnancy resulted in live birth, still birth or early pregnancy loss, or the true timing of the pregnancy is unknown, it makes studying drug exposure difficult. This study intends to investigate potential reasons why these pregnancies without outcome may be occurring in the register. This information will be used to improve the method by which the Register is created. Improvements to the Register will make this valuable resource more useful and enable researchers to investigate important public health concerns.
The Pregnancy Register algorithm generates a list of all pregnancies identified in CPRD GOLD. A record in the register represents a pregnancy episode and includes information on pregnancy start and outcome. However, there are approximately one million pregnancies where no outcome has been identified. Scenarios have been identified based on the algorithm's logic and how the data is structured which may explain this. The scenarios describe four problems; (i) real pregnancies where the outcome was not recorded in CPRD GOLD, (ii) ongoing pregnancies at the end of available follow-up, (iii) the patient may not have been pregnant, or (iv) the pregnancy episode may be made up of records which are really part of another pregnancy. Analysis will use an algorithmic approach to query CPRD GOLD and linked datasets to look for supporting evidence for each of these scenarios. Evidence will then be used to improve the Pregnancy Register algorithm to reduce the occurrence of pregnancies without outcome and increase the usefulness of this resource.
All end of pregnancy outcomes including live deliveries, stillbirths, early pregnancy losses (spontaneous and induced); Evidence of pregnancy, as defined by Read and Gemscript and ICD codes.
Jennifer Campbell - Chief Investigator - CPRD
Jennifer Campbell - Corresponding Applicant - CPRD
Caroline Minassian - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Rachael Williams - Collaborator - CPRD
Sara Thomas - Collaborator - Not from an Organisation