COVID-19 impact on consecutive neurological patients admitted to the emergency department

  1. Andrea Pilotto
  2. Alberto Benussi
  3. Ilenia Libri
  4. Stefano Masciocchi
  5. Loris Poli
  6. Enrico Premi
  7. Antonella Alberici
  8. Enrico Baldelli
  9. Sonia Bonacina
  10. Laura Brambilla
  11. Matteo Benini
  12. Salvatore Caratozzolo
  13. Matteo Cortinovis
  14. Angelo Costa
  15. Stefano Cotti Piccinelli
  16. Elisabetta Cottini
  17. Viviana Cristillo
  18. Ilenia Delrio
  19. Massimiliano Filosto
  20. Massimo Gamba
  21. Stefano Gazzina
  22. Nicola Gilberti
  23. Stefano Gipponi
  24. Marcello Giunta
  25. Alberto Imarisio
  26. Paolo Liberini
  27. Martina Locatelli
  28. Francesca Schiano
  29. Ranata Rao
  30. Barbara Risi
  31. Luca Rozzini
  32. Andrea Scalvini
  33. Veronica Vergani
  34. Irene Volonghi
  35. Nicola Zoppi
  36. Barbara Borroni
  37. Mauro Magoni
  38. Matilde Leonardi
  39. Gianluigi Zanusso
  40. Sergio Ferrari
  41. Sara Mariotto
  42. Alessandro Pezzini
  43. Roberto Gasparotti
  44. Ciro Paolillo
  45. Alessandro Padovani

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Abstract

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  1. Version published to 10.1136/jnnp-2020-323929
  2. ScreenIT

    SciScore for 10.1101/2020.05.23.20110650: (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 local ethics committee of ASST Spedali Civili di Brescia Hospital (NP 4067, approved 08.05.2020).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    All data were imputed and checked by five physicians (AP, AB, IL, SM, MG).
    AB
    suggested: RRID:BDSC_203)
    Software and Algorithms
    SentencesResources
    Data analyses were carried out using SPSS software (version 22.0)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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: We detected the following sentences addressing limitations in the study:
    We acknowledge that this study entails some limitations. First, due to the study design we limited the observation to patients presenting with prominent neurological manifestations thus probably underestimating neurological symptoms such as headache/pain or confusion in more severe patients, as suggested in previous reports[2,4,6]. Second, interpretation of findings could be limited by the single-centre design and by the re-distribution of emergency network in the region, potentially leading to decrease access to healthcare systems for less severe neurological manifestations. In conclusion, this study has shown that one third of neurological patients admitted to emergency department were SARS-CoV-2 positive and that most of them were affected by cerebrovascular disorders and altered mental status due to encephalitis or severe delirium. Coronavirus plays a relevant impact on health status as neurological patients required more frequently hospitalization, and were at higher risk of mortality and disability at discharge. Further studies are needed to compare different models of care in order to identify the most efficacious organisation to counteract the impact of COVID-19 on neurological patients.

    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.

  3. Version published to 10.1101/2020.05.23.20110650v1 on medRxiv