Evidence map›Paper›PMID 34332917›Full record

ArticleThe Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases

Tomographic score (RAD-Covid Score) to assess the clinical severity of the novel coronavirus infection.

Tatiana Figueiredo Guimarães Ribeiro, Ricardo Arroyo Rstom, Paula Nicole Vieira Pinto Barbosa, Maria Fernanda Arruda Almeida, Marina Martini Costa, Edivaldo Nery de Oliveira Filho, André Santos Barros, Talita Rombaldi Pereira, Silvio Fontana Velludo, Fabrício Próspero Machado

Open access · goldAbstract read
In one paragraph

Article in The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Tatiana Figueiredo Guimarães RibeiroDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil. Electronic address: tatiana.guimaraes@preventsenior.com.br.
Ricardo Arroyo RstomDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Paula Nicole Vieira Pinto BarbosaDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Maria Fernanda Arruda AlmeidaDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Marina Martini CostaDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Edivaldo Nery de Oliveira FilhoDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
André Santos BarrosDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Talita Rombaldi PereiraDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Silvio Fontana VelludoDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Fabrício Próspero MachadoDepartment of Radiology and Diagnostic Imaging at Prevent Senior, São Paulo, SP, Brazil.
Universidade Cidade de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe severity of pulmonary Covid-19 infection can be assessed by the pattern and extent of parenchymal involvement observed in computed tomography (CT), and it is important to standardize the analysis through objective, practical, and reproducible systems. We propose a method for stratifying the radiological severity of pulmonary disease, the Radiological Severity Score (RAD-Covid Score), in Covid-19 patients by quantifying infiltrate in chest CT, including assessment of its accuracy in predicting disease severity.

methodsThis retrospective, single-center study analyzed patients with a confirmed diagnosis of Covid-19 infection by real-time reverse-transcriptase polymerase chain reaction, who underwent chest CT at hospital admission between March 6 and April 6, 2020. CT scans were classified as positive, negative, or equivocal, and a radiological severity score (RAD-Covid Score) was assigned. Clinical severity was also assessed upon hospital admission.

results658 patients were included. Agreement beyond chance (kappa statistic) for the RAD-Covid Score was almost perfect among observers (0.833), with an overall agreement of 89.5%. The RAD-Covid Score was positively correlated with clinical severity and death, i.e., the higher the RAD-Covid Score, the greater the clinical severity and mortality. This association proved independent of age and comorbidities. Accuracy of this score was 66.9%.

conclusionsThe RAD-Covid Score showed good accuracy in predicting clinical severity at hospital admission and mortality in patients with confirmed Covid-19 infection and was an independent predictor of severity.

Indexed as

COVID-19SARS-CoV-2HumansLungRetrospective StudiesSeverity of Illness IndexTomography, X-Ray ComputedChest CTCovid-19HospitalizationInfectionSeverity

Identifiers

PMID34332917
PMCPMC8277556
OpenAlexW3185192775

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.