Reduction in stroke patients’ referral to the ED in the COVID-19 era: A four-year comparative study

  1. Saban Mor
  2. Reznik Anna
  3. Shachar Tal
  4. Sivan-Hoffmann Roten

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Abstract

Introduction

Current reports indicate that the increased use of social distancing for preventive COID-19 distribution may have a negative effect on patients who suffering from acute medical conditions.

Aim

We examined the effect of social distancing on acute ischemic stroke (AIS) patients’ referral to the emergency department (ED)

Method

A retrospective archive study was conducted between January 2017 and April 2020 in a comprehensive stroke center. We compare the number of neurologic consultations, time from symptoms onset to ED arrival, patients diagnosis with AIS, number of patients receiving treatment (tPA, endovascular thrombectomy (EVT) or combine) and in-hospital death.

Results

The analysis included a total of 14,626 neurological consultations from the years 2017 to 2020. A significant decrease of 58.6% was noted during the months of January-April of the year 2020 compared to the parallel period of 2017. Percent of final AIS diagnosis for the year of 2020 represent 24.8% of suspected cases, with the highest diagnosis rate demarcated for the year of 2019 with 25.6% of confirmed patients. The most remarkable increase was noted in EVT performance through the examined years (2017, n=21; 2018, n=32; 2019, n=42; 2020, n=47).

Conclusion

COVID-19 pandemic resulted in routing constraints on health care system resources that were dedicated for treating COVID-19 patients.

The healthcare system must develop and offer complementary solutions that will enable access to health services even during these difficult times.

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    SciScore for 10.1101/2020.05.30.20118125: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the institutional review boards of the hospital (#3023–18-RMB).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The data analysis was performed using SAS® software (SAS Enterprise Guide 7.1) and Python 3.6.5 software version 2019a.
    SAS®
    suggested: (SASqPCR, RRID:SCR_003056)
    Python
    suggested: (IPython, RRID:SCR_001658)

    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: No clinical trial numbers were referenced.

    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.

  2. Version published to 10.1101/2020.05.30.20118125v1 on medRxiv