Owkin

SOLENOID - PredictorS Of cLinical outcomEs iN hypertrOphIc carDiomyopathy

The SOLENOID - PredictorS Of cLinical outcomEs iN hypertrOphIc carDiomyopathy - project is investigating how the disease Hypertrophic cardiomyopathy (HCM) progresses. HCM is the most common inherited heart disease, affecting about 1 in 500 people. It’s caused by genetic mutations that increase the heart muscle's thickness, leading to problems like arrhythmias, chest pain, and difficulty breathing. Some people develop more severe forms of the disease, while others have mild symptoms or no symptoms at all. HCM can lead to serious complications, such as life-threatening heart rhythm issues and heart failure. While treatment options like myosin inhibitors have proven effective in reducing HCM-related risks, a third of patients still experience disease progression. There is currently no reliable way to predict which patients are at risk of worsening symptoms. This project aims to use artificial intelligence (AI) and machine learning (ML) to develop models that can predict disease progression in HCM patients. By identifying those at higher risk, the project hopes to improve treatment plans and patient outcomes, reducing hospitalisations and the need for more invasive procedures.

This project seeks to develop predictive models using machine learning to identify patients at higher risk of disease progression, including hospitalisation, worsened symptoms, and the need for advanced treatments. By improving early risk assessment, the project will help clinicians provide more personalised care, potentially reducing hospital visits and improving the quality of life for HCM patients. These models will ultimately enable better management and targeted therapies, reducing long-term morbidity and mortality in people living with HCM.

01/09/2023

SDE022b

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