Impact of Social Support on Cardiovascular Risk Prediction Models: A Systematic Review

  • Singh M
  • Nag A
  • Gupta L
  • et al.
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Abstract

Cardiovascular diseases (CVD) stand as the primary causes of both mortality and morbidity on a global scale. Social factors such as low social support can increase the risk of developing heart diseases and have shown poor prognosis in cardiac patients. Resources such as PubMed and Google Scholar were searched using a boolean algorithm for articles published between 2003 and 2023. Eligible articles showed an association between social support and cardiovascular risks. A systematic review was conducted using the guidance published in the Cochrane Prognosis Method Group and the PRISMA checklist, for reviews of selected articles. A total of five studies were included in our final analysis. Overall, we found that participants with low social support developed cardiovascular events, and providing a good support system can decrease the risk of readmission in patients with a history of CVD. We also found that integrating social determinants in the cardiovascular risk prediction model showed improvement in accessing the risk. Population with good social support showed low mortality and decreased rate of readmission. There are various prediction models, but the social determinants are not primarily included while calculating the algorithms. Although it has been proven in multiple studies that including the social determinants of health (SDOH) improves the accuracy of cardiovascular risk prediction models. Hence, the inclusion of SDOH should be highly encouraged.

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APA

Singh, M., Nag, A., Gupta, L., Thomas, J., Ravichandran, R., & Panjiyar, B. K. (2023). Impact of Social Support on Cardiovascular Risk Prediction Models: A Systematic Review. Cureus. https://doi.org/10.7759/cureus.45836

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