Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry
Sudden cardiac death (SCD) is one of the most frequent causes of death in adult patients with congenital heart disease (ACHD). Despite the rare frequency of its occurrence, the incident appears often when unexpected, and many affected patients had not been identified priorly. Data on predictors for...
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| Aineistotyyppi: | Artikkeli |
| Kieli: | English |
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Elsevier
2022-09-01
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| Sarja: | International Journal of Cardiology Congenital Heart Disease |
| Aiheet: | |
| Linkit: | http://www.sciencedirect.com/science/article/pii/S2666668522000799 |
| _version_ | 1828746188186189824 |
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| author | Alicia Jeanette Fischer Ulrike MM. Bauer Michael Frey Jens Beudt Helmut Baumgartner Gerhard-Paul Diller |
| author_facet | Alicia Jeanette Fischer Ulrike MM. Bauer Michael Frey Jens Beudt Helmut Baumgartner Gerhard-Paul Diller |
| author_sort | Alicia Jeanette Fischer |
| collection | DOAJ |
| description | Sudden cardiac death (SCD) is one of the most frequent causes of death in adult patients with congenital heart disease (ACHD). Despite the rare frequency of its occurrence, the incident appears often when unexpected, and many affected patients had not been identified priorly. Data on predictors for SCD are limited since the total number of ACHD is low. As the cohort is heterogeneous, it is difficult to define uniform risk factors that apply to all ACHD. Complexity of the congenital heart disease appears to play a role, but other factors may also be relevant and have not been sufficiently identified yet. In current guidelines, recommendations are primarily based on data of patients without congenital heart disease.With the ATROPOS registry, we are aiming to identify reliable risk factors for SCD. The registry enables physicians globally to include patients with congenital heart disease who died of or survived SCD. After acquisition, the data will be compared to an age and complexity of disease matched cohort to perform a case-control analysis. Subsequently, a further analysis will be performed using deep learning algorithms with artificial intelligence to amplify the gathered information and find reliable risk factors. |
| first_indexed | 2024-04-14T04:18:49Z |
| format | Article |
| id | doaj.art-a88a674feeb64b13bb5cee4f9ef0e7ce |
| institution | Directory Open Access Journal |
| issn | 2666-6685 |
| language | English |
| last_indexed | 2024-04-14T04:18:49Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Cardiology Congenital Heart Disease |
| spelling | doaj.art-a88a674feeb64b13bb5cee4f9ef0e7ce2022-12-22T02:12:36ZengElsevierInternational Journal of Cardiology Congenital Heart Disease2666-66852022-09-019100396Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registryAlicia Jeanette Fischer0Ulrike MM. Bauer1Michael Frey2Jens Beudt3Helmut Baumgartner4Gerhard-Paul Diller5Department of Cardiology III - Adult Congenital and Valvular Heart Disease, University Hospital Muenster, Germany; Corresponding author. Department of Cardiology III Adult Congenital and Valvular Heart Disease University Hospital Muenster Albert-Schweitzer-Str. 33, 48149, Münster, Germany.National Register for Congenital Heart Defects, Berlin, Germany; DZHK (German Centre for Cardiovascular Research), Berlin, GermanyNational Register for Congenital Heart Defects, Berlin, GermanyNational Register for Congenital Heart Defects, Berlin, Germany; DZHK (German Centre for Cardiovascular Research), Berlin, GermanyDepartment of Cardiology III - Adult Congenital and Valvular Heart Disease, University Hospital Muenster, GermanyDepartment of Cardiology III - Adult Congenital and Valvular Heart Disease, University Hospital Muenster, Germany; National Register for Congenital Heart Defects, Berlin, GermanySudden cardiac death (SCD) is one of the most frequent causes of death in adult patients with congenital heart disease (ACHD). Despite the rare frequency of its occurrence, the incident appears often when unexpected, and many affected patients had not been identified priorly. Data on predictors for SCD are limited since the total number of ACHD is low. As the cohort is heterogeneous, it is difficult to define uniform risk factors that apply to all ACHD. Complexity of the congenital heart disease appears to play a role, but other factors may also be relevant and have not been sufficiently identified yet. In current guidelines, recommendations are primarily based on data of patients without congenital heart disease.With the ATROPOS registry, we are aiming to identify reliable risk factors for SCD. The registry enables physicians globally to include patients with congenital heart disease who died of or survived SCD. After acquisition, the data will be compared to an age and complexity of disease matched cohort to perform a case-control analysis. Subsequently, a further analysis will be performed using deep learning algorithms with artificial intelligence to amplify the gathered information and find reliable risk factors.http://www.sciencedirect.com/science/article/pii/S2666668522000799Sudden cardiac deathCongenital heart diseasePredictorsDeep learning algorithms |
| spellingShingle | Alicia Jeanette Fischer Ulrike MM. Bauer Michael Frey Jens Beudt Helmut Baumgartner Gerhard-Paul Diller Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry International Journal of Cardiology Congenital Heart Disease Sudden cardiac death Congenital heart disease Predictors Deep learning algorithms |
| title | Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry |
| title_full | Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry |
| title_fullStr | Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry |
| title_full_unstemmed | Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry |
| title_short | Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry |
| title_sort | sudden cardiac death in adults with congenital heart disease lessons to learn from the atropos registry |
| topic | Sudden cardiac death Congenital heart disease Predictors Deep learning algorithms |
| url | http://www.sciencedirect.com/science/article/pii/S2666668522000799 |
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