COVID-19 and congenital heart disease: an insight of pathophysiology and associated risks

Ana Alina Haiduc1, Michael Ogunjimi2, Rohma Shammus1

  • 1Medical School, St George's, University of London, Cranmer Terrace, UK.

Cardiology in the Young
|November 11, 2020
PubMed

Insights

Congenital heart disease (CHD) patients with coronavirus disease 2019 (COVID-19) may face increased risks of adverse outcomes. Further research with larger cohorts is needed to confirm these findings for COVID-19 and CHD patients.

Area of Science:

  • Cardiology
  • Infectious Diseases
  • Public Health

Background:

  • Congenital heart disease (CHD) affects individuals across all age groups.
  • The impact of coronavirus disease 2019 (COVID-19) on patients with CHD is not fully understood.
  • Existing literature includes case reports and series, necessitating a comprehensive review.

Purpose of the Study:

  • To systematically review existing literature on the risk of poor outcomes in pediatric and adult patients with CHD who contract COVID-19.
  • To compare outcomes of COVID-19 in patients with and without CHD.
  • To identify potential increased risks associated with co-infection.

Main Methods:

  • A systematic literature review adhering to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.
  • Extensive database searches on EMBASE, Medline, Scopus, and Global Health.
  • Keyword and Medical Subject Headings (MeSH) term utilization for article identification.

Main Results:

  • Twelve articles met the inclusion criteria for the systematic review.
  • Data analysis focused on themes of increased risk and no increased risk in CHD patients.
  • Out of 99 CHD patients analyzed, 12 required intensive care unit (ICU) admission.

Conclusions:

  • Congenital heart disease may be associated with an elevated risk of adverse outcomes in patients with COVID-19.
  • The current evidence base, primarily from case studies, necessitates more robust research.
  • Future studies should aim for larger sample sizes and control for confounding factors to quantify risk accurately.
Abstract

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