Evidence map›Paper›PMID 37105996›Full record

ArticleScientific reports2023

Pulmonary computed tomographic manifestations of COVID-19 in vaccinated and non-vaccinated patients.

Esther Askani, Katharina Mueller-Peltzer, Julian Madrid, Marvin Knoke, Dunja Hasic, Christopher L Schlett, Fabian Bamberg, Prerana Agarwal

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
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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

8 authors.

Esther AskaniDepartment of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg im Breisgau, Freiburg, Germany. esther.askani@uniklinik-freiburg.de.ORCID 0000-0001-6553-7763
Katharina Mueller-PeltzerDepartment of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg im Breisgau, Freiburg, Germany.
Julian MadridDepartment of Cardiology, Pneumology, Angiology and Intensive Care, Ortenau Klinikum, Lahr, Germany.
Marvin KnokeDepartment of Protestant Theology, Faculty of Theology, University of Heidelberg, Heidelberg, Germany.
Dunja HasicDepartment of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg im Breisgau, Freiburg, Germany.
Christopher L SchlettDepartment of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg im Breisgau, Freiburg, Germany.
Fabian BambergDepartment of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg im Breisgau, Freiburg, Germany.
Prerana AgarwalDepartment of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg im Breisgau, Freiburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to analyze computed tomographic (CT) imaging features of vaccinated and non-vaccinated COVID-19 patients. The study population of this retrospective single-center cohort study consisted of hospitalized COVID-19 patients who received a chest CT at the study site between July 2021 and February 2022. Qualitative scoring systems (RSNA, CO-RADS, COV-RADS), imaging pattern analysis and semi-quantitative scoring of lung changes were assessed. 105 patients (70,47% male, 62.1 ± 16.79 years, 53.3% fully vaccinated) were included in the data analysis. A significant association between vaccination status and the presence of the crazy-paving pattern was observed in univariate analysis and persisted after step-wise adjustment for possible confounders in multivariate analysis (RR: 2.19, 95% CI: [1.23, 2.62], P = 0.024). Scoring systems for probability assessment of the presence of COVID-19 infection showed a significant correlation with the vaccination status in univariate analysis; however, the associations were attenuated after adjustment for virus variant and stage of infection. Semi-quantitative assessment of lung changes due to COVID-19 infection revealed no association with vaccination status. Non-vaccinated patients showed a two-fold higher probability of the crazy-paving pattern compared to vaccinated patients. COVID-19 variants could have a significant impact on the CT-graphic appearance of COVID-19.

Indexed as

COVID-19Cohort StudiesFemaleHumansLungLung Diseases, InterstitialMaleRetrospective StudiesSARS-CoV-2Tomography, X-Ray Computed

Identifiers

PMID37105996
PMCPMC10134716

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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.