Evidence map›Paper›PMID 36213436›Full record

ArticleThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale2022

Radiological Findings in SARS-CoV-2 Viral Pneumonia Compared to Other Viral Pneumonias: A Single-Centre Study.

Rana Günöz Cömert, Eda Cingöz, Sevim Meşe, Görkem Durak, Atadan Tunaci, Ali Ağaçfidan, Mustafa Önel, Şükrü Mehmet Ertürk

Open access · goldAbstract read
In one paragraph

Article in The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

8 authors at 1 institution in 1 country.

Rana Günöz CömertIstanbul University, Istanbul Faculty of Medicine, Department of Radiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0003-3084-8232
Eda CingözIstanbul University, Istanbul Faculty of Medicine, Department of Radiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0003-0814-4597
Sevim MeşeIstanbul University, Istanbul Faculty of Medicine, Department of Medical Microbiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0001-5944-0180
Görkem DurakIstanbul University, Istanbul Faculty of Medicine, Department of Radiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-1608-1955
Atadan TunaciIstanbul University, Istanbul Faculty of Medicine, Department of Radiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-8796-8641
Ali AğaçfidanIstanbul University, Istanbul Faculty of Medicine, Department of Medical Microbiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-5470-296X
Mustafa ÖnelIstanbul University, Istanbul Faculty of Medicine, Department of Medical Microbiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-3987-6611
Şükrü Mehmet ErtürkIstanbul University, Istanbul Faculty of Medicine, Department of Radiology, Istanbul, Turkey.ORCID https://orcid.org/0000-0001-6008-5454
Istanbul University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Thorax computed tomography (CT) imaging is widely used as a diagnostic method in the diagnosis of coronavirus disease 2019 (COVID-19)-related pneumonia. Radiological differential diagnosis and isolation of other viral agents causing pneumonia in patients have gained importance, particularly during the pandemic. Aims: We aimed to investigate whether there is a difference between CT images from patients with COVID-19-associated pneumonia compared to CT images of patients with pneumonia due to other viral agents and which finding may be more effective in diagnosis. Methods: Demographic data (age, gender, and known chronic disease) and CT imaging findings (percentage of involvement, number of lesions, distribution preference, dominant pattern, ground-glass opacity distribution pattern, nodule, tree in bud sign, interstitial changes, crazy paving sign, reversed halo sign, vacuolar sign, halo sign, vascular enlargement, linear opacities, traction bronchiectasis, peribronchial wall thickness, air trapping, pleural retraction, pleural effusion, pericardial effusion, cavitation, mediastinal/hilar lymphadenopathy, dominant lesion size, consolidation, subpleural curvilinear opacities, air bronchogram, and pleural thickening) of the patients were evaluated. CT findings were also evaluated with the RSNA consensus guideline and the CORADS scoring system. Data were divided into two main groups-non-COVID-19 and COVID-19 pneumonia-and compared statistically with chi-squared tests and multiple regression analysis of independent variables. Results: RSNA and CORADS classifications of CT scan images were able to successfully differentiate between positive and negative COVID-19 pneumonia patients. Statistically significant differences were found between the two patient groups in various categories including the percentage of involvement, number of lesions, distribution preference, dominant pattern, nodule, tree in bud, interstitial changes, crazy paving, reverse halo vascular enlargement, peribronchial wall thickness, air trapping, pleural retraction, pleural/pericardial effusion, cavitation, and mediastinal/hilar lymphadenopathy ( Conclusion: The presence of reverse halo and absence of pleural effusion was found to be characteristic of COVID-19 pneumonia and therefore a reliable diagnostic tool to differentiate it from non-COVID-19 pneumonia.

Identifiers

PMID36213436
PMCPMC9536981
OpenAlexW4297989738

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.