The interplay between COVID-19 and heart disease: Unravelling a complex connection

G D Duerr1, M Hamiko2, J Beer1

  • 1Department of Cardiovascular Surgery, University Medical Center, Johannes-Gutenberg University, Mainz, Germany.

Life Sciences
|March 5, 2025
PubMed

Insights

This study identified key predictors of severe COVID-19 outcomes in patients with heart disease. Circulating monocytes and C-reactive protein levels help predict myocardial damage and survival, aiding clinical practice.

Area of Science:

  • Cardiology
  • Infectious Diseases
  • Immunology

Background:

  • COVID-19 poses significant risks to individuals with pre-existing heart conditions.
  • SARS-CoV-2 infection can directly cause cardiac damage, including myocarditis and heart failure.
  • Identifying patients at risk for severe cardiac complications and predicting COVID-19 severity is crucial.

Purpose of the Study:

  • To stratify COVID-19 patients based on clinical and immunological parameters.
  • To identify predictors of myocardial damage (pericardial effusion - PE) and disease severity.
  • To evaluate machine learning algorithms for predicting COVID-19 patient outcomes.

Main Methods:

  • Analysis of clinical and immunological data from 134 SARS-CoV-2 positive patients.
  • Stratification of disease severity into three categories (SWOSS A-C).
  • Machine learning algorithms applied to identify predictive markers for PE and survival.

Main Results:

  • Pericardial effusion (PE) and SWOSS-C were linked to reduced survival.
  • CD14+ HLA-DR+ monocytes were the strongest predictor of myocardial damage (PE).
  • C-reactive protein (CRP) was a key predictor for PE and SWOSS-category; SWOSS-category predicted survival.

Conclusions:

  • A condensed severity classification (SWOSS) aids clinical practice.
  • Predictive markers for PE and survival can be identified using clinical and immunological data.
  • AI-identified prognostic features offer insights into COVID-19 and heart disease interactions.

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