High Resolution CHEST CT(HRCT) Evaluation in Patients Hospitalized with COVID-19 Infection

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Abstract

Introduction

Currently the main diagnostic modality for COVID-19 (Coronavirus disease-2019) is reverse transcriptase polymerase chain reaction (RT-PCR) via nasopharyngeal swab which has high false negative rates. We evaluated the performance of high-resolution computed tomography (HRCT) imaging in the diagnosis of suspected COVID-19 infection compared to RT-PCR nasopharyngeal swab alone in patients hospitalized for suspected COVID-19 infection.

Methods

This was a retrospective analysis of 324 consecutive patients admitted to Temple University Hospital. All hospitalized patients who had RT-PCR testing and HRCT were included in the study. HRCTs were classified as Category 1, 2 or 3. Patients were then divided into four groups based on HRCT category and RT-PCR swab results for analysis.

Results

The average age of patients was 59.4 (±15.2) years and 123 (38.9%) were female. Predominant ethnicity was African American 148 (46.11%). 161 patients tested positive by RT-PCR, while 41 tested positive by HRCT. 167 (52.02%) had category 1 scan, 63 (19.63%) had category 2 scan and 91 (28.35%) had category 3 HRCT scans. There was substantial agreement between our radiologists for HRCT classification (κ = 0.64). Sensitivity and specificity of HRCT classification system was 77.6 and 73.7 respectively. Ferritin, LDH, AST and ALT were higher in Group 1 and D-dimers levels was higher in Group 3; differences however were not statistically significant.

Conclusion

Due to its high infectivity and asymptomatic transmission, until a highly sensitive and specific COVID-19 test is developed, HRCT should be incorporated into the assessment of patients who are hospitalized with suspected COVID-19.

Key Points

Key Question

Can High Resolution CT chest (HRCT) improve diagnostic accuracy of current Nasopharyngeal swab in suspected COVID-19 patients?

Bottom Line

In this retrospective analysis, our novel HRCT classification identified 20% of all COVID-19 patients who had negative nasopharyngeal reverse transcriptase polymerase chain reaction (RT-PCR) tests but had HRCT findings consistent with COVID-19 pneumonia. These patients were ruled out for other infections and laboratory markers were similar to other RT-PCR positive patients

Why Read on

Our new HRCT classification when combined with RT-PCR can improve diagnostic accuracy while promptly improving triaging in COVID-19 patients.

Article activity feed

  1. SciScore for 10.1101/2020.05.26.20114082: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: A waiver of consent was granted due to minimal risk.
    RandomizationTreatments provided to patients: Patients with RT-PCR positive swabs were screened for eligibility for two randomized controlled trials involving sarilumab (Regeneron Pharmaceuticals; NCT04315298) and remdesivir (Gilead Sciences; NCT04292730 and NCT04292899).
    BlindingHRCT Scoring of COVID-19 Pattern and Severity: Three attending radiologists (two thoracic radiologists and a third non-thoracic radiologist each with more than 20 years’ experience), blinded to RT-PCR results, interpreted the HRCT scans independently and classified them into one of the 3 categories: Category 1 – consistent with multifocal pneumonia; Category 2 – indeterminate for multifocal pneumonia; Category 3 – not consistent with multifocal pneumonia (figure 1).
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were performed with the use of Stata 14.0 (StataCorp LP, College Station, TX).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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. The most important is that we provide no measure of viral loads or antibody test results to confirm the absolute presence or absence of COVID-19 infection due to lack of availability. Not all clinical and laboratory data was available for all patients. Additionally, due to limited use of bronchoscopy out of aerosolization and contamination concerns, confirmatory bronchoalveolar lavage could not be performed to definitively stratify Group 3 patients as true false negatives. Interpretation of our findings might be limited by the sample size and should be validated in larger studies. In conclusion, the findings outlined in this study suggests that a false negative RT-PCR population can be isolated for clinical re-evaluation if concomitant HRCT findings are consistent with a Category 1 stratification. We believe that combining RT-PCR with HRCT evaluation can increase the sensitivity and specificity of diagnostic testing to greater than 90%. To our knowledge, this is the first study that evaluates the utility of an HRCT based stratification system for the diagnosis of COVID-19. It is our contention that utilization of HRCT in the evaluation of a suspected COVID-19 infection will curb the false negativity of sole RT-PCR testing and help influence triage and clinical management decisions.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04315298CompletedEvaluation of the Efficacy and Safety of Sarilumab in Hospit…
    NCT04292730CompletedStudy to Evaluate the Safety and Antiviral Activity of Remde…
    NCT04292899CompletedStudy to Evaluate the Safety and Antiviral Activity of Remde…
    NCT04292899CompletedStudy to Evaluate the Safety and Antiviral Activity of Remde…


    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.
    • Thank you for including a protocol registration statement.

    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.