Incidence of Venous Thromboembolism in Hospitalized Patients with COVID-19

Middeldorp, Saskia; Coppens, Michiel; Haaps, Thijs F. van; Foppen, Merijn; Vlaar, Alexander P.J.; Müller, Marcella C.A.; Bouman, Catherine C. S.; Beenen, Ludo F. M.; Kootte, Ruud S.; Heijmans, Jarom; Smits, Loek P.; Bonta, Peter I.; Es, Nick van

doi:10.20944/preprints202004.0345.v1

Cited by 285 publications

(454 citation statements)

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“…It has also been observed that COVID-19 may predispose patients to thromboembolic disease (Klok et al, 2020;Middeldorp et al, 2020). Indeed, the gene expression analyses presented here showing altered expression of coagulation factors and fibrinogen genes suggests dysfunction within the intrinsic clotting pathway.…”

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confidence: 52%

Comprehensive Transcriptomic Analysis of COVID-19 Blood, Lung, and Airway

Daamen

Bachali

Owen

et al. 2020

Preprint

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SARS-CoV2 is a previously uncharacterized coronavirus and causative agent of the COVID-19 pandemic. The host response to SARS-CoV2 has not yet been fully delineated, hampering a precise approach to therapy. To address this, we carried out a comprehensive analysis of gene expression data from the blood, lung, and airway of COVID-19 patients. Our results indicate that COVID-19 pathogenesis is driven by populations of myeloid-lineage cells with highly inflammatory but distinct transcriptional signatures in each compartment. The relative absence of cytotoxic cells in the lung suggests a model in which delayed clearance of the virus may permit exaggerated myeloid cell activation that contributes to disease pathogenesis by the production of inflammatory mediators. The gene expression profiles also identify potential therapeutic targets that could be modified with available drugs. The data suggest that transcriptomic profiling can provide an understanding of the pathogenesis of COVID-19 in individual patients.3 1 Methods Read quality, trimming, mapping and summarizationPublicly available data sets used in this study are listed in Table S1. RNA-seq data were processed using a consistent workflow using FASTQC, Trimmomatic, STAR, Sambamba, and featureCounts. As described below SRA files were downloaded and converted into FASTQ format using SRA toolkit. Read ends and adapters were trimmed with Trimmomatic (v0.38) using a sliding window, ilmnclip, and headcrop filters. Both datasets were head cropped at 6bp and adapters were removed before read alignment.Reads were mapped to the human reference genome hg38 using STAR, and the .sam files were converted to sorted .bam files using Sambamba. Read counts were summarized using the featureCounts function of the Subread package (v1.61.)The RNA-seq tools are all free, open source programs available at the following web addresses SRA toolkit -https

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supporting

confidence: 52%

Comprehensive Transcriptomic Analysis of COVID-19 Blood, Lung, and Airway

Daamen

Bachali

Owen

et al. 2020

Preprint

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“… 5 Other studies have reported the incidence of thrombosis in around 20%–30% of the critically ill patients even with prophylaxis. 4 6 …”

Section: Discussionmentioning

confidence: 99%

Venous thromboembolism in patients with COVID-19 and correlation with D-dimers: a single-centre experience

et al. 2020

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ObjectiveTo study the frequency of venous thromboembolism in hospitalised patients with COVID-19 and correlation with the D-dimers and thromboprophylaxis.DesignCross-sectional descriptive study.Place and duration of studyQueen Elizabeth Hospital, 20 April 2020–13 May 2020.Patients and methodsOne hundred and seven (n=107) patients of PCR-confirmed COVID-19 pneumonia admitted to Queen Elizabeth Hospital, Birmingham, between 20 April 2020 and 13 May 2020 were included in the study using consecutive sampling. Data were collected using the Excel audit tool and included age, gender, weight, estimated eGFR, D-dimer values on admission, intensive care unit admission, presence of respiratory failure, imaging results for evaluation of venous thromboembolism (VTE) and anticoagulation received on admission. The data were entered in the SPSS (V.17) and were analysed. Data were summarised as means±SD, number or percentage as appropriate. A p value of less than 0.05 was considered significant.ResultsThe frequency of VTE was found to be 11.2% in patients hospitalised with COVID-19 pneumonia. The mean D-dimers were 3322.24 ng/mL±9603 ng/mL with the values significantly higher for patients with VTE and those requiring intensive care unit admission. All of the seven patients (100%) with D-dimers value above 2000 ng/mL who underwent imaging were found to have VTE.ConclusionVTE is frequent in patients with COVID-19 pneumonia despite anticoagulation. A higher D-dimers value correlates well with the risk of VTE in these patients and further evaluation of such patients for VTE is necessary especially with D-dimers values above 2000 ng/mL.

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“…Indeed, it is not recommended to base PE diagnosis on pulmonary ventilation-perfusion imaging [7]. The cumulative incidence of VTE on the wards is reported to be lower than in the ICU (10% versus 48% at 14 days, respectively) [8] where investigation for PE is not always feasible due to critical illness and prone position [9].…”

Section: Textmentioning

confidence: 99%