High Prevalence of Deep Venous Thrombosis in Non-Severe COVID-19 Patients Hospitalized for a Neurovascular Disease

This article has been Reviewed by the following groups

Read the full article

Abstract

<b><i>Introduction:</i></b> Severe SARS-CoV-2 infection induces COVID-19 along with venous thromboembolic occurrences particularly in intensive care units. For non-severe COVID-19 patients affected by neurovascular diseases, the prevalence of deep venous thrombosis (DVT) is unknown. The aim of our study was to report data obtained after systematic Doppler ultrasound scanning (DUS) of lower limbs in such patients. <b><i>Methods:</i></b> Between March 20 and May 2, 2020, the deep venous system of 13 consecutive patients diagnosed with neurovascular diseases and non-severe COVID-19 was investigated with a systematic bedside DUS. <b><i>Results:</i></b> Thirteen patients were enrolled in the study including 9 acute ischaemic strokes, 1 occlusion of the ophthalmic artery, 1 transient ischaemic attack, 1 cerebral venous thrombosis and 1 haemorrhagic stroke. On admission, the median National Institute of Health Stroke Scale (NIHSS) score was of 6 (IQR, 0–20). During the first week after admission, and despite thromboprophylaxis, we found a prevalence of 38.5% of asymptomatic calves’ DVT (<i>n</i> = 5). One patient developed a symptomatic pulmonary embolism and 2 other patients died during hospitalization. The outcome was positive for the other patients with a discharge median NIHSS score of 1 (IQR, 0–11). <b><i>Discussion/Conclusion:</i></b> Despite thromboprophylaxis, systematic bedside DUS showed a high prevalence (38.5%) of asymptomatic DVT in non-severe COVID-19 patients suffering from a neurovascular disease. In the absence of a reliable marker of DVT, we suggest that this non-invasive investigation could be an interesting tool to monitor peripheral venous thrombotic complications in such patients.

Article activity feed

  1. SciScore for 10.1101/2020.09.03.20187344: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The approval for this study was obtained from the local ethics committee of the Strasbourg University Hospital (reference CE-2020–111) and verbal informed consent was obtained from each patient.
    Consent: The approval for this study was obtained from the local ethics committee of the Strasbourg University Hospital (reference CE-2020–111) and verbal informed consent was obtained from each patient.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04452422RecruitingDeep Venous Thrombosis in Non-severe COVID-19 Patients Hospi…


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.