Evidence map›Paper›PMID 36152040›Full record

ArticleEuropean radiology2023

CT imaging findings in lung transplant recipients with COVID-19.

Bruno Hochhegger, Andres Pelaez, Tiago Machuca, Tan-Lucien Mohammed, Pratik Patel, Matheus Zanon, Felipe Torres, Stephan Altmayer, Douglas Zaione Nascimento

Open access · bronzeAbstract read
In one paragraph

Article in European radiology, 2023. 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
0.9field-weighted citation impact, top 26% 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. 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

9 authors at 3 institutions in 3 countries.

Bruno HochheggerDepartment of Radiology, University of Florida, Gainesville, FL, USA. bhochhegger@ufl.edu.
Andres PelaezDepartment of Medicine, University of Florida, Gainesville, FL, USA.
Tiago MachucaDepartment of Surgery, University of Florida, Gainesville, FL, USA.
Tan-Lucien MohammedDepartment of Radiology, University of Florida, Gainesville, FL, USA.
Pratik PatelDepartment of Radiology, University of Florida, Gainesville, FL, USA.
Matheus ZanonDepartment of Radiology, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil.
Felipe TorresDepartment of Radiology, University of Toronto, Toronto, Canada.
Stephan AltmayerDepartment of Radiology, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil.
Douglas Zaione NascimentoDepartment of Lung Transplantation, Santa Casa de Misericordia de Porto Alegre, Porto Alegre, Brazil.
University of Florida · USPontifícia Universidade Católica do Rio Grande do Sul · BRUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesOur goal was to compare the chest computed tomography (CT) imaging findings of COVID-19 in lung transplant recipients (LTR) and a group of non-transplanted controls (NTC).

methodsThis retrospective study included 51 consecutive LTR hospitalized with COVID-19 from two centers. A total of 75 NTC were included for comparison. Images were classified regarding the standardized RSNA category, main pattern of lung attenuation, and longitudinal and axial distribution. Quantitative CT (QCT) analysis was performed to evaluate percentage of high attenuation areas (%HAA, threshold -250 to -700 HU). CT scoring was used to measure severity of parenchymal abnormalities.

resultsThe imaging findings of COVID-19 in LTR were significantly different from controls regarding the RSNA classification and pattern of lung attenuation. LTR had a significantly higher proportion of patients with an indeterminate pattern on CT (0.31 vs. 0.11, p = 0.014). The most frequent pattern of attenuation in LTR was predominantly consolidation (0.39 vs. 0.22, p = 0.144) followed by a mixed pattern of ground-glass opacities (GGO) and consolidation (0.37 vs. 0.20, adjusted p = 0.102). On the other hand, the most common pattern in NTC was GGO predominant (0.58 vs. 0.24 of LTR, p = 0.001). LTR had significantly more severe parenchymal disease measured by CT score and %HAA by QCT (0.372 ± 0.08 vs. 0.148 ± 0.06, p < 0.001).

conclusionThe most frequent finding of COVID-19 in LTR is a predominant pattern of consolidation. Compared to NTC, LTR more frequently demonstrated an indeterminate pattern according to the RSNA classification and more extensive lung abnormalities on QCT and semi-quantitative scoring. KEY POINTS: • The most common CT finding of COVID-19 in LTR is a predominant pattern of consolidation followed by a mixed pattern of GGO and consolidation, while controls more often have a predominant pattern of GGO. • LTR more often presents with an indeterminate pattern of COVID-19 by RSNA classification than controls; therefore, molecular testing for COVID-19 is essential for LTR presenting with lower airway infection independently of imaging findings. • LTR had more extensive disease by semi-quantitative CT score and increased percentage areas of high attenuation on QCT.

Indexed as

COVID-19COVID-19 TestingHumansLungRetrospective StudiesSARS-CoV-2Tomography, X-Ray ComputedTransplant RecipientsComputed tomographyCOVID-19Lung transplantQuantitative CT

Identifiers

PMID36152040
PMCPMC9510464
OpenAlexW4297175524

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.