The work, led by Dr Shishir Rao, Prof Kazem Rahimi and Mr Nouman Ahmed developed the model, called TRisk, which analyses a patient’s full medical history to estimate their likelihood of death within the next one to three years. By identifying patients at higher risk earlier, the system could help clinicians prioritise care, improve monitoring, and facilitate important discussions with patients and families. The findings have been published in npj Digital Medicine.
Addressing a major clinical challenge
Heart failure affects millions of people worldwide. It is a serious long-term condition where the heart does not pump blood as effectively as it should. While some people remain stable for years, others deteriorate more quickly.
Clinicians use risk scores to estimate a patient’s prognosis, but existing tools often rely on specialised tests such as heart imaging. These tests may not always be available and can be resource-intensive. Current models also struggle to account for the complex mix of other health conditions that many patients with heart failure have. Additionally, current models have focused on short- and long-term mortality prediction, unlike TRisk.
In fact, research shows that more than 40% of deaths in heart failure patients are linked to other medical problems rather than heart failure alone. The research team aimed to develop and test a system that could utilise routinely collected electronic health records (EHRs), including diagnoses, medications, and procedures, to deliver more accurate and practical mid-term risk predictions.
Read the full story on the Nuffield Department of Women's & Reproductive Health website.