Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities
The main purpose of prognostic risk prediction models is to identify individuals who are at risk of disease, to enable early intervention. Current prognostic cardiovascular risk prediction models, such as the Systematic COronary Risk Evaluation (SCORE2) and the SCORE2-Older Persons (SCORE2-OP) model...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2023-11-01
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| Series: | Open Heart |
| Online Access: | https://openheart.bmj.com/content/10/2/e002395.full |
| _version_ | 1797367031114235904 |
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| author | Tibor V Varga |
| author_facet | Tibor V Varga |
| author_sort | Tibor V Varga |
| collection | DOAJ |
| description | The main purpose of prognostic risk prediction models is to identify individuals who are at risk of disease, to enable early intervention. Current prognostic cardiovascular risk prediction models, such as the Systematic COronary Risk Evaluation (SCORE2) and the SCORE2-Older Persons (SCORE2-OP) models, which represent the clinically used gold standard in assessing patient risk for major cardiovascular events in the European Union (EU), generally overlook socioeconomic determinants, leading to disparities in risk prediction and resource allocation. A central recommendation of this article is the explicit inclusion of individual-level socioeconomic determinants of cardiovascular disease in risk prediction models. The question of whether prognostic risk prediction models can promote health equity remains to be answered through experimental research, potential clinical implementation and public health analysis. This paper introduces four distinct fairness concepts in cardiovascular disease prediction and their potential to narrow existing disparities in cardiometabolic health. |
| first_indexed | 2024-03-08T17:12:07Z |
| format | Article |
| id | doaj.art-aec5445aaf994503b8de4ee10ac07dd4 |
| institution | Directory Open Access Journal |
| issn | 2053-3624 |
| language | English |
| last_indexed | 2024-03-08T17:12:07Z |
| publishDate | 2023-11-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | Open Heart |
| spelling | doaj.art-aec5445aaf994503b8de4ee10ac07dd42024-01-03T21:10:07ZengBMJ Publishing GroupOpen Heart2053-36242023-11-0110210.1136/openhrt-2023-002395Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalitiesTibor V Varga0Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, DenmarkThe main purpose of prognostic risk prediction models is to identify individuals who are at risk of disease, to enable early intervention. Current prognostic cardiovascular risk prediction models, such as the Systematic COronary Risk Evaluation (SCORE2) and the SCORE2-Older Persons (SCORE2-OP) models, which represent the clinically used gold standard in assessing patient risk for major cardiovascular events in the European Union (EU), generally overlook socioeconomic determinants, leading to disparities in risk prediction and resource allocation. A central recommendation of this article is the explicit inclusion of individual-level socioeconomic determinants of cardiovascular disease in risk prediction models. The question of whether prognostic risk prediction models can promote health equity remains to be answered through experimental research, potential clinical implementation and public health analysis. This paper introduces four distinct fairness concepts in cardiovascular disease prediction and their potential to narrow existing disparities in cardiometabolic health.https://openheart.bmj.com/content/10/2/e002395.full |
| spellingShingle | Tibor V Varga Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities Open Heart |
| title | Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities |
| title_full | Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities |
| title_fullStr | Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities |
| title_full_unstemmed | Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities |
| title_short | Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities |
| title_sort | algorithmic fairness in cardiovascular disease risk prediction overcoming inequalities |
| url | https://openheart.bmj.com/content/10/2/e002395.full |
| work_keys_str_mv | AT tiborvvarga algorithmicfairnessincardiovasculardiseaseriskpredictionovercominginequalities |