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D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19

Litao Zhang1,2,3, Xinsheng Yan3, Qingkun Fan1

  • 1Laboratory Medicine, Wuhan Asia Heart Hospital, Wuhan, China.

Journal of Thrombosis and Haemostasis : JTH
|April 20, 2020
PubMed

Insights

Elevated D-dimer levels on admission can predict in-hospital mortality in patients with coronavirus disease 2019 (Covid-19). A D-dimer level greater than 2.0 µg/mL is a significant indicator of increased mortality risk.

Area of Science:

  • Clinical Medicine
  • Hematology
  • Infectious Diseases

Background:

  • The COVID-19 pandemic necessitates early identification of patients at high risk of mortality.
  • Effective predictors are crucial for timely clinical intervention and improved patient outcomes.

Purpose of the Study:

  • To investigate the predictive value of D-dimer levels on admission for in-hospital mortality in COVID-19 patients.
  • To determine an optimal cutoff value for D-dimer to stratify mortality risk.

Main Methods:

  • Retrospective enrollment of 343 laboratory-confirmed COVID-19 patients.
  • D-dimer levels and mortality events were collected.
  • Receiver operating characteristic (ROC) curves were used to determine the optimal D-dimer cutoff value.

Main Results:

  • An optimal D-dimer cutoff of 2.0 µg/mL was identified with 92.3% sensitivity and 83.3% specificity.
  • Patients with D-dimer ≥ 2.0 µg/mL exhibited a significantly higher mortality rate (12/67) compared to those with D-dimer < 2.0 µg/mL (1/267, P < .001).
  • A hazard ratio of 51.5 indicated a substantially increased risk of mortality for patients with elevated D-dimer.

Conclusions:

  • D-dimer levels ≥ 2.0 µg/mL on admission are a strong predictor of in-hospital mortality in COVID-19 patients.
  • This finding suggests D-dimer can serve as an early and valuable biomarker for managing COVID-19 patients.
  • The study provides evidence for integrating D-dimer testing into early risk assessment protocols for COVID-19.
Abstract

Keywords:
D-dimerSARS-CoV-2coronavirus diseasemortalityprognosis

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