Evidence map›Paper›PMID 35575286›Full record

SynthesisThe Cochrane database of systematic reviews2022

Thoracic imaging tests for the diagnosis of COVID-19.

Sanam Ebrahimzadeh, Nayaar Islam, Haben Dawit, Jean-Paul Salameh, Sakib Kazi, Nicholas Fabiano, Lee Treanor, Marissa Absi, Faraz Ahmad, Paul Rooprai and 23 more

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 3 pooled it
11.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 3 syntheses or guidelines pooled it, 82 citations in OpenAlex.

  1. Rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection.The Cochrane database of systematic reviews · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

33 authors at 14 institutions in 5 countries.

Sanam Ebrahimzadeh *Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.
Nayaar Islam *Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.
Haben DawitClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.
Jean-Paul SalamehDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Sakib KaziDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Nicholas FabianoDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Lee TreanorDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Marissa AbsiDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Faraz AhmadDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Paul RoopraiDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Ahmed Al KhalilDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Kelly HarperDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Neil KamraDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Mariska Mg LeeflangDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Lotty HooftCochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands.
Christian B van der PolDepartment of Radiology, McMaster University, Hamilton, Canada.
Ross PragerDepartment of Medicine, University of Ottawa, Ottawa, Canada.
Samanjit S HareDepartment of Radiology, Royal Free London NHS Trust, London , UK.
Carole DennieDepartment of Radiology, University of Ottawa, Ottawa, Canada.
René SpijkerCochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands.
Jonathan J DeeksTest Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Jacqueline DinnesTest Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Kevin JenniskensCochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Daniël A KorevaarDepartment of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
Jérémie F CohenObstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), UMR1153, Université de Paris, Paris, France.
Ann Van den BruelAcademic of Primary Care, KU Leuven, Leuven, Belgium.
Yemisi TakwoingiTest Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Janneke van de WijgertCochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Junfeng WangJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands.
Elena PenaDepartment of Radiology, University of Ottawa, Ottawa, Canada.
Sandra SabonguiFaculty of Medicine, University of Toronto, Toronto, Canada.
Matthew Df McInnesClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.
Cochrane COVID-19 Diagnostic Test Accuracy GroupNIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK.
University of Ottawa · CAUniversity Medical Center Utrecht · NLAmsterdam University Medical Centers · NLOttawa Hospital Research InstituteCentre de Recherche Épidémiologie et StatistiqueKU Leuven · BEMcMaster University · CANIHR Birmingham Biomedical Research Centre · GBOttawa Hospital · CARoyal Free London NHS Foundation Trust · GBUniversity Hospitals Birmingham NHS Foundation Trust · GBUniversity of Birmingham · GBUniversity of Toronto · CAUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur March 2021 edition of this review showed thoracic imaging computed tomography (CT) to be sensitive and moderately specific in diagnosing COVID-19 pneumonia. This new edition is an update of the review.

objectivesOur objectives were to evaluate the diagnostic accuracy of thoracic imaging in people with suspected COVID-19; assess the rate of positive imaging in people who had an initial reverse transcriptase polymerase chain reaction (RT-PCR) negative result and a positive RT-PCR result on follow-up; and evaluate the accuracy of thoracic imaging for screening COVID-19 in asymptomatic individuals. The secondary objective was to assess threshold effects of index test positivity on accuracy. SEARCH

methodsWe searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 17 February 2021. We did not apply any language restrictions. SELECTION CRITERIA: We included diagnostic accuracy studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19. Studies had to assess chest CT, chest X-ray, or ultrasound of the lungs for the diagnosis of COVID-19, use a reference standard that included RT-PCR, and report estimates of test accuracy or provide data from which we could compute estimates. We excluded studies that used imaging as part of the reference standard and studies that excluded participants with normal index test results. DATA COLLECTION AND ANALYSIS: The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using QUADAS-2. We presented sensitivity and specificity per study on paired forest plots, and summarized pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. MAIN

resultsWe included 98 studies in this review. Of these, 94 were included for evaluating the diagnostic accuracy of thoracic imaging in the evaluation of people with suspected COVID-19. Eight studies were included for assessing the rate of positive imaging in individuals with initial RT-PCR negative results and positive RT-PCR results on follow-up, and 10 studies were included for evaluating the accuracy of thoracic imaging for imagining asymptomatic individuals. For all 98 included studies, risk of bias was high or unclear in 52 (53%) studies with respect to participant selection, in 64 (65%) studies with respect to reference standard, in 46 (47%) studies with respect to index test, and in 48 (49%) studies with respect to flow and timing. Concerns about the applicability of the evidence to: participants were high or unclear in eight (8%) studies; index test were high or unclear in seven (7%) studies; and reference standard were high or unclear in seven (7%) studies. Imaging in people with suspected COVID-19 We included 94 studies. Eighty-seven studies evaluated one imaging modality, and seven studies evaluated two imaging modalities. All studies used RT-PCR alone or in combination with other criteria (for example, clinical signs and symptoms, positive contacts) as the reference standard for the diagnosis of COVID-19. For chest CT (69 studies, 28285 participants, 14,342 (51%) cases), sensitivities ranged from 45% to 100%, and specificities from 10% to 99%. The pooled sensitivity of chest CT was 86.9% (95% confidence interval (CI) 83.6 to 89.6), and pooled specificity was 78.3% (95% CI 73.7 to 82.3). Definition for index test positivity was a source of heterogeneity for sensitivity, but not specificity. Reference standard was not a source of heterogeneity. For chest X-ray (17 studies, 8529 participants, 5303 (62%) cases), the sensitivity ranged from 44% to 94% and specificity from 24 to 93%. The pooled sensitivity of chest X-ray was 73.1% (95% CI 64. to -80.5), and pooled specificity was 73.3% (95% CI 61.9 to 82.2). Definition for index test positivity was not found to be a source of heterogeneity. Definition for index test positivity and reference standard were not found to be sources of heterogeneity. For ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases), the sensitivity ranged from 73% to 94% and the specificity ranged from 21% to 98%. The pooled sensitivity of ultrasound was 88.9% (95% CI 84.9 to 92.0), and the pooled specificity was 72.2% (95% CI 58.8 to 82.5). Definition for index test positivity and reference standard were not found to be sources of heterogeneity. Indirect comparisons of modalities evaluated across all 94 studies indicated that chest CT and ultrasound gave higher sensitivity estimates than X-ray (P = 0.0003 and P = 0.001, respectively). Chest CT and ultrasound gave similar sensitivities (P=0.42). All modalities had similar specificities (CT versus X-ray P = 0.36; CT versus ultrasound P = 0.32; X-ray versus ultrasound P = 0.89). Imaging in PCR-negative people who subsequently became positive For rate of positive imaging in individuals with initial RT-PCR negative results, we included 8 studies (7 CT, 1 ultrasound) with a total of 198 participants suspected of having COVID-19, all of whom had a final diagnosis of COVID-19. Most studies (7/8) evaluated CT. Of 177 participants with initially negative RT-PCR who had positive RT-PCR results on follow-up testing, 75.8% (95% CI 45.3 to 92.2) had positive CT findings. Imaging in asymptomatic PCR-positive people For imaging asymptomatic individuals, we included 10 studies (7 CT, 1 X-ray, 2 ultrasound) with a total of 3548 asymptomatic participants, of whom 364 (10%) had a final diagnosis of COVID-19. For chest CT (7 studies, 3134 participants, 315 (10%) cases), the pooled sensitivity was 55.7% (95% CI 35.4 to 74.3) and the pooled specificity was 91.1% (95% CI 82.6 to 95.7). AUTHORS'

conclusionsChest CT and ultrasound of the lungs are sensitive and moderately specific in diagnosing COVID-19. Chest X-ray is moderately sensitive and moderately specific in diagnosing COVID-19. Thus, chest CT and ultrasound may have more utility for ruling out COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. The uncertainty resulting from high or unclear risk of bias and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.

Indexed as

COVID-19HumansSARS-CoV-2Sensitivity and SpecificityTomography, X-Ray ComputedUltrasonography

Identifiers

PMID35575286
PMCPMC9109458
OpenAlexW4280536144

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.