Validating a postpartum venous thromboembolism risk prediction model using QResearch
What is the aim of the study and why is it important?
Having a blood clot develop in a vein, known as a venous thromboembolism (VTE), can happen more often in young women after giving birth. Although it is rare, it is very serious and is a leading cause of maternal deaths in high-income countries, so prevention is important.
We aim to validate a risk prediction algorithm that will help to identify women at high risk of having a VTE for the first time during the six weeks after giving birth. This could be used as a tool to focus preventative treatment medications for use in women who need them most and ultimately reduce the number of women who have VTEs after pregnancy.
How is the research being done?
The recommendations for which women should receive medications that prevent VTE (thromboprophylaxis) after delivery (postpartum) are largely inconsistent. In the UK, there is a scoring system used by adding up certain risk factors (e.g. caesarean section delivery, above average weight) that categorises postpartum women into low, intermediate, or high risk to help decide whether they should be given thromboprophylaxis and the duration. This broad categorisation may result in treating more women than necessary which can increase the cost and risks of potential side-effects such as bleeding.
Our research team have developed a prediction tool that estimates the probability that a woman will develop a first VTE post-delivery; this is more sophisticated than the existing scoring system and would mean that more women with VTE will be correctly identified whilst fewer women without VTE will receive prophylaxis unnecessarily. We used the UK Clinical Practice Research Database to create the tool and we tested it using the Swedish Inpatient and Birth Registry but we now need to ensure it is also valid in the United Kingdom and are using the QResearch database linked to Hospital Episode Statistics to test it.
Location of research
Date on which research approved
Project reference ID
Generic ethics approval reference
Are all data accessed are in anonymised form?
Brief summary of the dataset to be released (including any sensitive data)
Women with a recorded pregnancy on hospital records linked to GP records between 2004 and 2016. GP and hospital data included medical conditions and risk factors for thrombosis
University of Nottingham
Joe West, Lu Ban, Matthew Grainge, Laila Tata: University of Nottingham Alyshah Abdul Sultan: Keele University