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| Name | Class |
|---|---|
| University of Bologna | OTHER |
| Universita Degli Studi di Firenze | UNKNOWN |
| Rennes University Hospital | OTHER |
| University of Milan |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| HCM patients from Florence Italy, Rennes, France, and Tampere Finland | HCM patients in follow up |
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| Measure | Description | Time Frame |
|---|---|---|
| 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 | from patient records until the end of 2026 |
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| Measure | Description | Time Frame |
|---|---|---|
| Other clinical characteristics of patients with severe outcomes due to HCM compared to those with mild disease for the creation of SMASH-HCM algorithm. | All cardiac medication will be recorded and the reason this has changed during the analysis timepoints. Incidence of other diseases will be included in the analysis e.g. stroke, myocardial infarction, atrial fibrillation, depression, changes in vascular status (mainly blood pressure) The number of hospital visits is recorded and the reason for those |
Inclusion Criteria:
Exclusion Criteria:
-
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HCM patients followed in the clinical sites in this study: Florence Italy, Rennes France and Tampere Finland
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| Name | Affiliation | Role |
|---|---|---|
| Jari Hyttinen, Professor | Professor | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Tampere university | Tampere | Finland |
Clinical data (ECG, ultra sound, cardiac MR, cardiac biomarkers, gene mutations, additional diseases) found in patient files will be shared with this study consortium with different AI groups specializing in each specific clinical record.
1.1.2025-31.12.2028
The databank is simply a file-sharing app using Nextcloud, with user access controls and monitoring
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| ID | Term |
|---|---|
| D002312 | Cardiomyopathy, Hypertrophic |
| ID | Term |
|---|---|
| D009202 | Cardiomyopathies |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D001020 | Aortic Stenosis, Subvalvular |
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| OTHER |
| University College Dublin | OTHER |
| Universitätsklinikum Hamburg-Eppendorf | OTHER |
| Medtronic Bakken Research | INDUSTRY |
| Pharmatics Limited | UNKNOWN |
| University of Oxford | OTHER |
| University of Rennes 2 | OTHER |
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| January 2024 to December 2026 |
| D001024 |
| Aortic Valve Stenosis |
| D000082862 | Aortic Valve Disease |
| D006349 | Heart Valve Diseases |