Association between biomarkers and COVID-19 severity and mortality: a nationwide Danish cohort study

Gethin Hodges1, Jannik Pallisgaard2, Anne-Marie Schjerning Olsen3,4

  • 1Department of Cardiology, Copenhagen University Hospital Herlev and Gentofte, Hellerup, Denmark gethin.william.hodges@regionh.dk.

BMJ Open
|December 3, 2020
PubMed

Insights

Elevated levels of C-reactive protein (CRP), leucocytes, procalcitonin, urea, troponins, and D-dimer, along with decreased estimated glomerular filtration rate (eGFR), are linked to increased death or intensive care unit (ICU) admission risk in COVID-19 patients.

Area of Science:

  • Biochemistry
  • Critical Care Medicine
  • Infectious Diseases

Background:

  • COVID-19 poses significant risks of mortality and intensive care unit (ICU) admission.
  • Biomarkers are crucial for assessing disease severity and patient prognosis in COVID-19.
  • Understanding the predictive value of common biomarkers can aid clinical decision-making.

Purpose of the Study:

  • To investigate the association between baseline levels of common biomarkers and the risk of death or ICU admission in hospitalized COVID-19 patients.
  • To quantify the standardized absolute risks for various biomarker levels concerning adverse outcomes.

Main Methods:

  • Retrospective cohort study utilizing national registry data from all hospitals in Denmark.
  • Included 1310 adult patients hospitalized with COVID-19 between February and May 2020 with available biochemistry data.
  • Cox analysis and bootstrapping were employed to assess associations, adjusting for age and gender.

Main Results:

  • Higher levels of C-reactive protein (CRP), leucocytes, procalcitonin, urea, troponins, and D-dimer were significantly associated with increased risk of death/ICU admission.
  • Lower estimated glomerular filtration rate (eGFR) was also linked to a higher risk of the composite endpoint.
  • Specific absolute risks were quantified for different biomarker levels, demonstrating a clear dose-response relationship for many markers.

Conclusions:

  • Elevated CRP, leucocytes, procalcitonin, urea, troponins, and D-dimer, alongside low eGFR, are significant predictors of adverse outcomes in COVID-19 patients.
  • These findings highlight the utility of routine biochemical markers in risk stratification for COVID-19.
  • The study underscores the importance of monitoring these biomarkers for timely intervention and resource allocation.
Abstract

Related Concept Videos

Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers01:19

Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers

Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
368
Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
591
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.0K