Evidence map›Paper›PMID 37448469›Full record

ReviewBJR open2023

Pictorial guide for variants of Covid-19: CT imaging and interpretation.

Giacomo Bonito, Valeria Martinelli, Francesco Vullo, Fabrizio Basilico, Eleonora Polito, Antonella Izzo, Laura Corso, Paolo Ricci

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in BJR open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 2 institutions in 1 country.

Giacomo BonitoUnit of Emergency Radiology, Policlinico Umberto I Hospital, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Valeria MartinelliUnit of Emergency Radiology, Policlinico Umberto I Hospital, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Francesco VulloUnit of Emergency Radiology, Policlinico Umberto I Hospital, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Fabrizio BasilicoUnit of Emergency Radiology, Policlinico Umberto I Hospital, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Eleonora PolitoDepartment of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Antonella IzzoDepartment of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Laura CorsoDepartment of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena, Rome, Italy.
Paolo RicciORCID https://orcid.org/0000-0001-5212-0678
Policlinico Umberto I · ITSapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Typical radiologic images of Covid-19 pneumonia consists in a wide spectrum of chest manifestations, which range from peripheral predominant ground-glass opacities to an organizing pneumonia pattern, with additional features including crazy-paving, consolidations, fibrotic streaks and linear opacities. With variants imaging profile of Covid-19 evolves, producing relatively atypical/indeterminate CT pattern of pulmonary involvement, which overlap with imaging features of a variety of other respiratory diseases, including infections, drug reaction and hypersensitivity pneumonia. Our knowledge of these radiological findings is incomplete and there is a need to strengthen the recognition of the many faces of Covid-19 pneumonia.

Identifiers

PMID37448469
PMCPMC10337581
OpenAlexW4295290424

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.