Cardiovascular disease (CVD, e.g. heart attack, stroke) is the leading cause of death in women. Yet women with CVD remain understudied, under-recognised, underdiagnosed and undertreated. Therefore, women have not experienced the same decline in CV rates that has occurred in men in recent decades.
General practitioners currently use CVD risk prediction tools that use traditional risk factors such as blood pressure and cholesterol. We propose that a CVD risk assessment tool which incorporates menstrual data could improve the prediction/prevention of CVD in women.
Recent research suggests that menstrual symptoms such as heavy periods may predict future CVD. Examination of our local electronic health records revealed that women having surgery for heavy menstrual bleeding (HMB) had a seven times greater risk of death from a heart attack than the general female population. Women undergoing hysterectomy for benign causes (e.g. HMB) also had increased CVD, even if the ovaries were not removed.(2).
There are many underlying causes of HMB. These may be non-structural (normal womb at scan) or structural (fibroids/adenomyosis) causes and may be influenced by genetics. However, the relationship between the symptom of HMB, its underlying cause and CVD risk has not been systematically evaluated.
This project will evaluate: (1) if there is an association between the symptom or underlying cause of HMB and future CVD by examining anonymised electronic health records and longitudinal population-based cohort studies of women across the life-course. This will determine if menstrual data would be useful in the prediction of future CVD. (2) if inclusion of relevant menstrual data (informed by our population data studies) and/or other female-specific risk factors (from published literature) in current CV risk prediction tools improves their prediction of CVD. We will use two independent population studies from the UK and Australia to validate our findings. (3) if adoption of a CV risk prediction tool that incorporates female-specific risk factors is feasible in clinical practice to improve the prevention of CVD. We will ask three general practices to use the new female-specific tool on pre-menopausal women. We will assess the number of women it is used in, how user friendly the tool is and also examine the anonymised electronic health records of those it is used in to determine the rate of prescription of CV preventative medicines (e.g. blood pressure medications, statins). These results will inform the design of a future, larger trial to assess the effectiveness of this new tool versus the currently used tools.
This project combines the expertise of gynaecologists, cardiologists and epidemiologists to analyse data from populations to inform clinical practice. We aim to inform the inclusion of relevant menstrual data in CVD risk assessment tools and inform future studies to evaluate their performance in the identification of pre-menopausal women at risk of CVD, allowing early implementation of effective preventative strategies to reduce CV disease and death in women.