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Effective prognostic and clinical risk stratification in COVID-19 using multimodality biomarkers

Alexander Liu1, Robert Hammond1, Peter D Donnelly1

  • 1University of St Andrews School of Medicine, St Andrews, UK.

Journal of Internal Medicine
|April 28, 2023
PubMed

Insights

Effective clinical risk stratification for coronavirus disease 19 (COVID-19) patients is crucial. This review explores prognostic biomarkers, including patient factors, blood tests, and imaging, to predict COVID-19 severity and outcomes.

Area of Science:

  • Medical research
  • Clinical diagnostics
  • Prognostic biomarkers

Background:

  • Effective clinical risk stratification is vital for managing acute coronavirus disease 19 (COVID-19) patients, impacting treatment and resource allocation.
  • Patient characteristics, comorbidities (cardiovascular, respiratory), and physiological measurements (oxygen saturation) are linked to increased mortality risk.
  • Existing risk scores like the 4C-score offer multi-factorial prognostic estimation.

Purpose of the Study:

  • To review and synthesize evidence on biomarkers with prognostic value in COVID-19 patients.
  • To identify key clinical, laboratory, and imaging markers associated with COVID-19 prognosis.
  • To highlight gaps in current understanding and suggest future research directions.

Main Methods:

  • Systematic review of existing literature on COVID-19 prognostic biomarkers.
  • Analysis of patient characteristics, comorbidities, blood tests (inflammation, cardiac injury, d-dimer), electrocardiogram findings, and imaging modalities (lung ultrasound, echocardiography, CXR, CT).
  • Evaluation of dynamic changes in biomarkers for disease severity assessment.

Main Results:

  • Peripheral oxygen saturation and arterial oxygenation predict severe respiratory compromise.
  • Blood tests (inflammation markers, cardiac injury, d-dimer) and ECG abnormalities correlate with inpatient prognosis.
  • Imaging techniques like lung ultrasound, echocardiography, CXR, and CT reveal prognostic pulmonary and cardiovascular pathologies.
  • Cardiovascular CT can identify high-risk features such as coronary artery and aortic calcification.

Conclusions:

  • A wide range of biomarkers, including clinical, laboratory, and imaging data, offer prognostic value in COVID-19.
  • Dynamic monitoring of these biomarkers can further inform disease severity and prognosis.
  • Further research is needed to elucidate the pathophysiological basis of these markers, investigate under-explored tests, and validate findings through prospective studies for clinical implementation.

Keywords:
COVID-19biomarkerclinical outcomesdiagnostic performanceprognosisrisk stratification

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