Diagnostic performance of CT and its key signs for COVID-19: A systematic review and meta-analysis

  1. Xiuting Wu
  2. Yuhui Zhong
  3. Wanyue Qin
  4. Zhenxi Zhang
  5. Kai Li

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Abstract

Purpose

To evaluate the diagnostic value of chest CT in 2019 novel coronavirus disease (COVID-19), using the reverse transcription polymerase chain reaction (RT-PCR) as a reference standard. At the same time, the imaging features of CT in confirmed COVID-19 patients would be summarized.

Methods

A comprehensive literature search of 5 electronic databases was performed. The pooled sensitivity, specificity, positive predictive value, and negative predictive value were calculated using the random-effects model and the summary receiver operating characteristic (SROC) curve. We also conducted a meta-analysis to estimate the pooled incidence of the chest CT imaging findings and the 95% confidence interval (95%CI). Meta-regression analysis was used to explore the source of heterogeneity.

Results

Overall, 25 articles comprising 4,857 patients were included. The pooled sensitivity of CT was 93% (95% CI, 89-96%) and specificity was 44% (95% CI, 27-62%). The area under the SROC curve was 0.94 (95% CI, 0.91-0.96). For the RT-PCR assay, the pooled sensitivity of the initial test and the missed diagnosis rate after the second-round test were 76% (95% CI: 59-89%; I 2 =96%) and 26% (95% CI: 14-39%; I 2 =45%), respectively. According to the subgroup analysis, the diagnostic sensitivity of CT in Hubei was higher than that in other regions. Besides, the most common patterns on CT imaging finding was ground glass opacities (GGO) 58% (95% CI: 49-70%), followed by air bronchogram 51% (95% CI: 31-70%). Lesions were inclined to distribute in peripheral 64% (95% CI: 49-78%), and the incidence of bilateral lung involvement was 69% (95% CI: 58-79%).

Conclusions

There were still several cases of missed diagnosis after multiple RT-PCR examinations. In high-prevalence areas, CT could be recommended as an auxiliary screening method for RT-PCR.

Key points

  • Taking RT-PCR as the reference standard, the pooled sensitivity of CT was 93% (95% CI, 89-96%) and the specificity was 44% (95% CI, 27-62%). The area under the SROC curve was 0.94 (95% CI, 0.91-0.96).

  • For the RT-PCR assay, the pooled sensitivity of the initial test and the missed diagnosis rate after the second-round test were 76% (95% CI: 59-89%) and 26% (95% CI: 14-39%), respectively.

  • GGO was the key sign of the CT imaging, with an incidence of 58% (95% CI: 49-70%) in patients with SARS-CoV-2 infection. Pneumonia lesions were inclined to distribute in peripheral 64% (95% CI: 49-78%) and bilateral 69% (95% CI: 58-79%) lung lobes.

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    1. ScreenIT

      SciScore for 10.1101/2020.05.24.20111773: (What is this?)

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

      Table 1: Rigor

      Institutional Review Board Statementnot detected.
      Randomizationnot detected.
      Blindingnot detected.
      Power Analysisnot detected.
      Sex as a biological variablenot detected.

      Table 2: Resources

      Software and Algorithms
      SentencesResources
      2.1 literature searches: Searches were conducted in five medical databases including three English databases (PubMed, Embase, and Web of Science) and two Chinese databases (China Biology Medicine disc, and China National Knowledge Infrastructure).
      PubMed
      suggested: (PubMed, RRID:SCR_004846)
      Embase
      suggested: (EMBASE, RRID:SCR_001650)

      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 review had several limitations. Only two documents came from non-Chinese regions, and the detailed information of CT in different regions was lacking. Information about the diagnostic specificity of CT could not be obtained from most studies. Therefore, we only included 11 articles with 2 × 2 tables to draw the SROC curve. Some studies did not mention the time of CT and RT-PCR examination. When exploring heterogeneity, the literature with the interval between CT and PCR examinations less than two weeks was divided into one group, and the rest constituted another group. It was best to obtain the specific time interval information to fully understand the factors influencing diagnostic sensitivity of CT. In addition, the study did not obtain sufficient CT image data to explain the relationship between imaging manifestations and duration of Infection. In conclusion, CT was highly sensitive in the diagnosis of COVID-19. There were still several cases of missed diagnosis after multiple RT-PCR examinations. In high-prevalence areas, CT can be recommended as an auxiliary screening method for RT-PCR. In the future, large samples and high-quality prospective studies can make up for the deficiency of the current small sample size and further verify the results.

      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 10.1101/2020.05.24.20111773v1 on medRxiv