Evidence map›Paper›PMID 36395576›Full record

ReviewClinical imaging2023

Two in one: Overlapping CT findings of COVID-19 and underlying lung diseases.

Gamze Durhan, Selin Ardalı Düzgün, Yusuf Baytar, Meltem Gülsün Akpınar, Figen Başaran Demirkazık, Orhan Macit Arıyürek

Open access · bronzeAbstract readReview
In one paragraph

Review in Clinical imaging, 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
1.4field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
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

6 authors at 1 institution in 1 country.

Gamze DurhanDepartment of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey. Electronic address: gamzedurhan@gmail.com.
Selin Ardalı DüzgünDepartment of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Yusuf BaytarDepartment of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Meltem Gülsün AkpınarDepartment of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Figen Başaran DemirkazıkDepartment of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Orhan Macit ArıyürekDepartment of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Hacettepe University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) is associated with pneumonia and has various pulmonary manifestations on computed tomography (CT). Although COVID-19 pneumonia is usually seen as bilateral predominantly peripheral ground-glass opacities with or without consolidation, it can present with atypical radiological findings and resemble the imaging findings of other lung diseases. Diagnosis of COVID-19 pneumonia is much more challenging for both clinicians and radiologists in the presence of pre-existing lung disease. The imaging features of COVID-19 and underlying lung disease can overlap and obscure the findings of each other. Knowledge of the radiological findings of both diseases and possible complications, correct diagnosis, and multidisciplinary consensus play key roles in the appropriate management of diseases. In this pictorial review, the chest CT findings are presented of patients with underlying lung diseases and overlapping COVID-19 pneumonia and the various reasons for radiological lung abnormalities in these patients are discussed.

Indexed as

COVID-19RadiologyHumansRadiologistsThoraxTomography, X-Ray ComputedComputed tomographyCOVID-19 pneumoniaLung diseases

Identifiers

PMID36395576
PMCPMC9651998
OpenAlexW4308949026

What OpenQuestion holds

Textmetadata
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.