“Urban Tertiary Care Centre Experience of Characteristics of Severe COVID-19 Pneumonia”

  1. Nehal M Shah
  2. Janakkumar R Khambholja
  3. Nilay Suthar
  4. Hemant Tiwari
  5. Vandit Desai
  6. Vishal Beriwala

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Abstract

Introduction

The global pandemic of novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in Wuhan, China, in December 2019, and has since spread worldwide. [1] This study attempts to summarize current evidence regarding major inflammatory markers, severity predictors and its impact on outcome, which provide current clinical experience and treatment guidance for this novel coronavirus.

Methods

This is a retrospective observational study done at an urban teaching covid-19 designated hospital. Hospital data were analysed with aim of studying inflammatory markers, predictors and outcome. Patients were classified in Mild, Moderate, Severe & Critical categories of COVID cases. Their clinical parameters, laboratory investigations, radiological findings & Outcome measures were studied. Strength of association & correlation of those parameters with severity and in-hospital mortality were studied.

Results

A total 204 (N) patients were clinically classified into different severity groups, as per MOHFW and qCSI(quick Covid Severity Index) guidelines, as Mild (34), Moderate (56), Severe (39) and Critical (75). The mean(SD) age of the cohort was 55.1+13.2 years; 74.02% were male. Severe COVID-19 illness is seen more in patients more than 50 years of age. COVID-19 patients having IHD develop worse disease with excess early in-hospital mortality. Respiratory rate & Heart Rate on admission are correlated with severe and stormy disease. Among Inflammatory markers, on admission LDH, D-Dimer and CRP are related with severity and excess in-hospital death rate.

Conclusion

Advanced age, male gender, IHD, Respiratory Rate & Heart Rate on admission were associated with severe covid-19 illness. S. Lactate Dehydrogenase & D-dimer was associated with severe covid-19 illness and early in-hospital death.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.16.21262073: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical software were used as per necessity like SPSS v25/v26, GraphPad Prism, MedCalc& MS Excel 365.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.08.16.21262073 on medRxiv