Effective Prediction of Outcome after Congenital Heart Surgery (EPOCH Study)

Project summary

Due to advances in cardiology and cardio-thoracic surgery, life expectancy of patients with congenital heart disease (CHD) has increased significantly during the past decades. At present it is estimated that there are between 1.9 and 3.9 million patients with CHD in Europe and this number is increasing at a rate of 5% per year. It is predicted that within a decade 1 in 150 adults will be living with the diagnosis of CHD. However, 75% percent 

of these adult patients have undergone palliative or corrective heart surgery at a young age and are at high risk of developing significant complications in adulthood. Therefore, existence of accurate risk prediction models is imperative in order to further improve the outcome of these patients and their quality of life. Current risk prediction models are not suitable for adequately predicting the outcome of patients with CHD disease after cardiac surgery. This is mainly due to the fact that they do not adequately correlate longitudinally collected data with patient’s outcome and because these models are never updated once they are built while the patient population with CHD is continuously changing. The proposed project aims to develop dynamic risk prediction models for clinical outcomes in patients with CHD by developing new statistical strategies that combine observed clinical outcome (e.g. valve failure, congestive heart failure, pulmonary hypertension, reoperation, quality of life, death) with repeatedly collected data during the follow-up of these patients (e.g. biomarkers, echocardiographic data, MRI data, ECG’s).  

This project will not only enable clinicians to accurately predict the risk of certain events for the individual patient in an objective manner but will also help them and the patients in choosing the optimal treatment strategy.