D‐dimer levels on admission to predict in‐hospital mortality in patients with Covid‐19
Open accessAbstract
Background The outbreak of the coronavirus disease 2019 (Covid-19) has shown a global spreading trend. Early and effective predictors of clinical outcomes are urgently needed to improve management of Covid-19 patients.Objective The aim of the present study was to evaluate whether elevated D-dimer levels could predict mortality in patients with Covid-19.Methods Patients with laboratory confirmed Covid-19 were retrospective enrolled in Wuhan Asia General Hospital from January 12, 2020, to March 15, 2020. D-dimer levels on admission and death events were collected to calculate the optimum cutoff using receiver operating characteristic curves. According to the cutoff, the subjects were divided into two groups. Then the in-hospital mortality between two groups were compared to assess the predictive value of D-dimer level.Results A total of 343 eligible patients were enrolled in the study. The optimum cutoff value of D-dimer to predict in-hospital mortality was 2.0 µg/mL with a sensitivity of 92.3% and a specificity of 83.3%. There were 67 patients with D-dimer ≥2.0 µg/mL, and 267 patients with D-dimer <2.0 µg/mL on admission. 13 deaths occurred during hospitalization. Patients with D-dimer levels ≥2.0 µg/mL had a higher incidence of mortality when comparing with those who with D-dimer levels <2.0 µg/mL (12/67 vs 1/267, P < .001; hazard ratio, 51.5; 95% confidence interval, 12.9-206.7).Conclusions D-dimer on admission greater than 2.0 µg/mL (fourfold increase) could effectively predict in-hospital mortality in patients with Covid-19, which indicated D-dimer could be an early and helpful marker to improve management of Covid-19 patients. (Chinese Clinical Trial Registry: ChiCTR2000031428).
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The CDS model used chest X-ray images, vital signs, demographic data, and laboratory values that prior publications showed to be predictive of COVID-19 outcomes.
“The inputs to the CDS model were Chest X-Ray (CXR) images, vital signs, demographic data, and lab values that were shown in previous publications to be predictive of COVID-19 patient outcomes18–21.”
From Federated learning for predicting clinical outcomes in patients with COVID-19 (2021) · cites this paper as [20]
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- Authors
- Zhang, L., Yan, X., Fan, Q., Liu, H., Liu, X., Liu, Z., & Zhang, Z.
- Affiliations
- Wuhan Asia Heart Hospital (CN)
- Corresponding author
- Zhang, Zhenlu
- Venue
- Journal of Thrombosis and Haemostasis
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 18
- Issue
- 6
- Pages
- 1324-1329
- ISSN
- 1538-7836 (ISSN-L)
- PMC
- PMC7264730
- OpenAlex
- W3016508437
- Cited by
- 1,347
- References
- 25
- Citations by year
- 2026: 21 · 2025: 48 · 2024: 92 · 2023: 158 · 2022: 287 · 2021: 426 · 2020: 312
- FWCI
- 38.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Thrombosis and Haemostasis (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
- Health Sciences › Medicine › Neurology › Long-Term Effects of COVID-19
- Keywords
- D-dimer, COVID-19 pandemic, in-hospital mortality, prognostic factors, mortality prediction, diagnostic thresholds, thrombosis
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Aged, China, Female, Fibrin Fibrinogen Degradation Products, Humans, Male, Middle Aged, Patient Admission, Pneumonia, Viral, Predictive Value of Tests, Prognosis, Retrospective Studies, Risk Factors, Time Factors, Biomarkers, Hospital Mortality, Coronavirus Infections, Risk Assessment, Early Diagnosis, Pandemics
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