The goal of SMASH-HCM is to develop a digital twin or virtual model of the heart and vascular system with sympathetic nerve control that integrates multi-scale and multi-organ spatiotemporal biophysical data from a multitude of sources. SMASH-HCM's digital twin powered platform will dramatically improve hypertrophic cardiomyopathy (HCM) patient stratification and disease management through stepwise deep phenotyping integrated in clinical and patient-guided workflows.
The aim of this SMASH-HCM study is with available well-characterized clinical data and existing iPSC derived cardiomyocyte data from HCM patients to find better predictors of worse outcomes i.e. potentially lethal arrhythmias, heart failure, sudden cardiac arrest in HCM patients. Additionally with artificial intelligence (AI) to find markers of good outcome so that we could focus more on those who would potentially benefit more from the intense follow up. Additionally our aim is to create a digital twin by collecting all possible clinical data from the HCM patients and also from currently healthy mutation carriers to be able to predicts the clinical out in more personal way and also toddling treatment strategies in more personal manner.
Study Type
OBSERVATIONAL
Enrollment
2,500
Tampere university
Tampere, Finland
Clinical characteristics of patients with severe arrhythmias, heart failure, sudden death or implantation of ICD for Digital Twin creation
The presence of arrhythmias will be obtained from 24 h Holter recordings, stress exercise test, monitor recording if in the hospital and if found in clinical patient records. Heart failure data if obtained from ultrasound records, clinical observations and elevated natriuretic peptide levels in the serum. Data about sudden deaths are obtained from patient records. Requirements of ICD implantations are obtained from patient records
Time frame: from patient records until the end of 2026
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