Correlation between Chest CT Severity Scores and the Clinical Parameters of Adult Patients with COVID-19 Pneumonia

  1. Ghufran Aref Saeed
  2. Waqar Gaba
  3. Asad Shah
  4. Abeer Ahmed Al Helali
  5. Emadullah Raidullah
  6. Ameirah Bader Al Ali
  7. Mohammed Elghazali
  8. Deena Yousef Ahmed
  9. Shaikha Ghanam Al Kaabi
  10. Safaa Almazrouei

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Abstract

Purpose. Our aim is to correlate the clinical condition of patients with COVID-19 infection with the 25-point CT severity score by Chang et al. (devised for assessment of ARDS in patients with SARS in 2005). Materials and Methods. Data of consecutive symptomatic patients who were suspected to have COVID-19 infection and presented to our hospital were collected from March to April 2020. All patients underwent two consecutive RT-PCR tests and had a noncontrast HRCT scan done at presentation. From the original cohort of 1062 patients, 160 patients were excluded leaving a total number of 902 patients. Results. The mean age was 44.2 ± 11.9 years (85.3% males, 14.7% females). CT severity score was found to be positively correlated with lymphopenia, increased serum CRP, d-dimer, and ferritin levels ( p < 0.0001 ). The oxygen requirements and length of hospital stay were increasing with the increase in scan severity. Conclusion. The 25-point CT severity score correlates well with the COVID-19 clinical severity. Our data suggest that chest CT scoring system can aid in predicting COVID-19 disease outcome and significantly correlates with lab tests and oxygen requirements.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.15.20213058: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data collection: Ethical approval was obtained from Institutional Review Board (IRB) and Department of health (DOH), Abu Dhabi, United Arab Emirates (UAE).
    Consent: The informed consent was waved off as per the Ethics committee.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Severity then was assessed using the following scoring system which depends on the visual assessment of each lobe involved (13, 14, 15), (Figure1): The sum of the lobar scores indicates the overall severity: Statistical analysis: The analysis was performed using SPSS 21.0.
    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:
    There are several limitations in this study. First, the need for a larger multicenter cohort to increase the accuracy of the findings. Second, the fact that the assessment of disease severity on CT scans can be subjective. This was reduced by involving two experienced readers to reach a consensus. Finally, the other factors that might contribute to the disease outcome such as lifestyle, as well as relying on self-reporting/ underreporting of the comorbidities should be considered. In conclusion, CT scans can have a pivotal role in assisting physicians in the management plan as well as work as an indicator for disease severity and possible outcome. CT severity score is positively correlated with inflammatory lab markers, length of hospital stays and oxygen requirement in patients with COVID-19 infection. More studies from different regions would enhance the accuracy of information regarding this novel 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.

    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 10.1155/2021/6697677
  3. Version published to 10.1101/2020.10.15.20213058v1 on medRxiv