Evidence map›Paper›PMID 33504028›Full record

ArticleBiology2021

Coronavirus Disease 2019 (COVID-19) in Italy: Double Reading of Chest CT Examination.

Alfonso Reginelli, Roberta Grassi, Beatrice Feragalli, Maria Paola Belfiore, Alessandro Montanelli, Gianluigi Patelli, Michelearcangelo La Porta, Fabrizio Urraro, Roberta Fusco, Vincenza Granata and 6 more

Abstract read
In one paragraph

Article in Biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Thoracic imaging tests for the diagnosis of COVID-19.The Cochrane database of systematic reviews · 2022
    Pooled it
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  18. Lymphadenopathy afterBiology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Alfonso ReginelliDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Roberta GrassiDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Beatrice FeragalliOral and Biotechnological Sciences-Radiology Unit "G. D'Annunzio", Department of Medical, University of Chieti-Pescara, 66100 Chieti, Italy.
Maria Paola BelfioreDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Alessandro MontanelliLaboratory Medicine Unit, ASST Bergamo Est, 24068 Seriate, Italy.
Gianluigi PatelliDepartment of Radiology, ASST Bergamo Est, 24068 Seriate, Italy.
Michelearcangelo La PortaDepartment of Radiology, UOC San Severo Hospital, 71016 San Severo, Italy.
Fabrizio UrraroDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Roberta FuscoRadiology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy.ORCID 0000-0002-0469-9969
Vincenza GranataRadiology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy.
Antonella PetrilloRadiology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy.ORCID 0000-0003-2465-5370
Giuliana GiacobbeDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Gaetano Maria RussoDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Palmino SaccoDiagnostic Imaging Unit, Department of Radiological Sciences, Azienda Ospedaliera Universitaria Senese, 53100 Siena, Italy.
Roberto GrassiDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.
Salvatore CappabiancaDepartment of Precision Medicine, Università degli Studi della Campania Luigi Vanvitelli, 80121 Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To assess the performance of the second reading of chest compute tomography (CT) examinations by expert radiologists in patients with discordance between the reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test for COVID-19 viral pneumonia and the CT report. Three hundred and seventy-eight patients were included in this retrospective study (121 women and 257 men; 71 years median age, with a range of 29-93 years) and subjected to RT-PCR tests for suspicious COVID-19 infection. All patients were subjected to CT examination in order to evaluate the pulmonary disease involvement by COVID-19. CT images were reviewed first by two radiologists who identified COVID-19 typical CT patterns and then reanalyzed by another two radiologists using a CT structured report for COVID-19 diagnosis. Weighted к values were used to evaluate the inter-reader agreement. The median temporal window between RT-PCRs execution and CT scan was zero days with a range of (-9,11) days. The RT-PCR test was positive in 328/378 (86.8%). Discordance between RT-PCR and CT findings for viral pneumonia was revealed in 60 cases. The second reading changed the CT diagnosis in 16/60 (26.7%) cases contributing to an increase the concordance with the RT-PCR. Among these 60 cases, eight were false negative with positive RT-PCR, and 36 were false positive with negative RT-PCR. Sensitivity, specificity, positive predictive value and negative predictive value of CT were respectively of 97.3%, 53.8%, 89.0%, and 88.4%. Double reading of CT scans and expert second readers could increase the diagnostic confidence of radiological interpretation in COVID-19 patients.

Indexed as

chest CTCOVID-19double readingradiological signsstructured report

Identifiers

PMID33504028
PMCPMC7911408

What OpenQuestion holds

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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.