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Rose is a 17-years-old adolescent suffering from an Obesity-related Cardiovascular Disease. Her waist girth is 102 cm. She underwent the fasting measurement of systemic inflammation markers, the MRI evaluation of adiposity, the evaluation of cardiac morphology and haemodynamics by echocardiography, and a cardiopulmonary exercise test.

Her waist girth has significantly increased over the last 18 months demonstrating central fat dis-tribution. Her fasting glucose is elevated and her oral glucose tolerance is impaired. Rose is dylipidemic, with increased levels of inflammation markers. Echocardiog-raphy demonstrates left ventricular hypertrophy with normal systolic function and impaired cardiac relaxation.

The CMR evaluation and the applanation tonome-try show a significant amount of pericardial fat paired with the mild diffuse fibrosis of the cardiac muscle and a reduced arterial compliance with increased wall stress and impaired endothelial function. The cardio-pulmonary test reduced tolerance to physical activity, with increased oxygen consumption and an evident pathological blood pressure profile.

MD-Paedigree provides integrated information on car-diovascular structure and function, the quantitative assessment of fat distribution in the body, and meta-bolic and genetic data from laboratory tests. The electromechanical heart model allows understanding the mechanism of cardiac muscle and vascular dysfunction by integrating related information on systemic fibrosis, inflammation and cardiovascular mechanics. It also al-lows predicting the impact of selected therapies and weight loss for the specific cardiovascular function, fat distribution and exercise tolerance.

Rose’s treatment is personalised and tailored using integrated information on anthropometrics, demographic data, cardiac geometry and function, vascular compliance, genetic and metabolic profiles. MD-Paedigree’s accurate estimation of cardiovascular risk, prognosis of disease develop-ment and a successful therapy prediction (on previously observed cases clinical history in the digital repository) helps selecting the most effective treatment at the first disease evidence.

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