The CT Scan Lung Severity Score and Vaccination Status in COVID-19 patients in India: Perspective of an Independent Radiology Practice

  1. Revat Lakhia
  2. Jaimin Trivedi

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Abstract

Background Patients with COVID-19 often undergo a high-resolution CT scan to determine the extent of lung involvement. The aim of this study was to determine lung involvement in confirmed/suspected COVID-19 patients (encountered at an independent radiology practice) and its correlation to vaccination status amidst the second COVID-19 wave in India. Methods We retrospectively queried our data from April 2021 to identify adult patients (>17 years) who had confirmed (positive RT-PCR or antigen test) or suspected COVID-19 (classic symptoms but negative RT-PCR) and received a high-resolution CT scan to determine the extent of lung involvement using the CT severity (CT-SS) score. The patients were classified into three groups based on their vaccination status to determine their correlation with the CT-SS score: fully vaccinated, partially vaccinated, and unvaccinated. Basic descriptive statistics, univariate tests, and multivariate linear regression analyses were performed. Results We identified 229 patients (median age, 45 years; 60% male), of whom 205 (89%) had confirmed COVID-19 (positive RT-PCR) and 24 had suspected disease (negative RT-PCT but classic symptoms). Of 229 patients, 29 (13%) had complete vaccination, 38 (17%) had partial vaccination, and 162 (70%) had no vaccination. The CT score of the completely vaccinated patients was significantly lower than that of the partially or unvaccinated patients (median 0 v. 3.5 v. 10, respectively p<.01). Conclusion Here, we present real-world findings from an independent radiology practice (a unique and common practice model) in India amid the second COVID-19 wave, showing significantly lower CT severity scores in fully or partially vaccinated patients compared to unvaccinated patients. Complete vaccination of patients may be critical in preventing severe lung disease.

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  1. Version published to 10.12688/f1000research.145771.1
  2. Version published to 10.1101/2021.07.15.21260597v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.07.15.21260597: (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
    We retrospectively queried our data since April 2021 to identify adult patients (>17 years) who had confirmed (positive RT-PCR or antigen test) or suspected COVID-19 (classic symptoms but negative RT-PCR) and received a high-resolution CT scan to determine the extent of their lung involvement using the CT severity (CORAD) score6.
    CORAD
    suggested: None
    All the analyses were conducted using SAS 9.4 software (SAS Inc. Cary, NC) at 95% confidence interval level.
    SAS
    suggested: (SASqPCR, RRID:SCR_003056)

    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:
    Our study has several limitations being a retrospective single center study. We did not have patient details other than their basic demographics, COVID-19 RT-PCR status, vaccination status and CT severity score. Patient details such as their oxygen saturations, hospital admission status, co-morbidities and mortality were not available. In conclusion, we present here the real-world findings from an independent radiology practice (a unique and common practice model), in India amid the second COVID-19 wave showing significantly lower CT severity score in fully or partially vaccinated patients compared to unvaccinated patients. We report a higher CT severity score in patients with positive RT-PCR. Complete vaccination in patients could be critical in preventing severe lung disease.

    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.

  4. Version published to 10.1101/2021.07.15.21260597v1 on medRxiv