Evidence map›Paper›PMID 34246422›Full record

ArticleRadiologia

Computed tomographic features of coronavirus disease-2019 (COVID-19) pneumonia in three groups of Iranian patients: A single center study.

S Ashtari, A Vahedian-Azimi, S Shojaee, M A Pourhoseingholi, R Jafari, F R Bashar, M R Zali

Abstract read
In one paragraph

Article in Radiologia. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

7 authors.

S AshtariCentro de Investigación de Epidemiología Básica y Molecular de los Trastornos Gastrointestinales, Instituto de Investigación de Gastroenterología y Enfermedades Hepáticas, Universidad de Ciencias Médicas Shahid Beheshti, Teheran, Iran.
A Vahedian-AzimiCentro de investigación de traumatismos, Facultad de Enfermería, Universidad de Ciencias Médicas de Baqiyatallah, Teheran, Iran.
S ShojaeeCentro de Investigación de Epidemiología Básica y Molecular de los Trastornos Gastrointestinales, Instituto de Investigación de Gastroenterología y Enfermedades Hepáticas, Universidad de Ciencias Médicas Shahid Beheshti, Teheran, Iran.
M A PourhoseingholiCentro de Investigación de Gastroenterología y Enfermedades Hepáticas, Instituto de Investigación de Gastroenterología y Enfermedades Hepáticas, Universidad de Ciencias Médicas Shahid Beheshti, Teheran, Iran. Electronic address: amin_phg@gmail.com.
R JafariDepartamento de Radiología, Centro de Investigación Sanitaria, Instituto de Estilo de Vida, Universidad de Ciencias Médicas Baqiyatallah, Teheran, Iran.
F R BasharDepartamento de Anestesia y Cuidados Críticos, Universidad de Ciencias Médicas de Hamadán, Hamadán, Iran.
M R ZaliCentro de Investigación de Gastroenterología y Enfermedades Hepáticas, Instituto de Investigación de Gastroenterología y Enfermedades Hepáticas, Universidad de Ciencias Médicas Shahid Beheshti, Teheran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

INTRODUCTION AND

objectivesThe pivotal role of chest computed tomographic (CT) to diagnosis and prognosis coronavirus disease-2019 (COVID-19) is still an open field to be explored. This study was conducted to assess the CT features in confirmed cases with COVID-19. MATERIALS AND

methodsRetrospectively, initial chest CT data of 363 confirmed cases with COVID-19 were reviewed. All subjects were stratified into three groups based on patients' clinical outcomes; non-critical group (n=194), critical group (n=65), and death group (n=104). The detailed of CT findings were collected from patients' medical records and then evaluated for each group. In addition, multinomial logistic regression was used to analyze risk factors according to CT findings in three groups of patients with COVID-19.

resultsCompared with the non-critical group, mixed ground-glass opacities (GGO) and consolidation lesion, pleural effusion lesion, presence of diffuse opacity in cases, more than 2 lobes involved and opacity scores were significantly higher in the critical and death groups (P<0.05). Having more mixed GGO with consolidation, pleural effusion, lack of pure GGO, more diffuse opacity, involvement of more than 2 lobes and high opacity score identified as independent risk factors of critical and death groups.

conclusionCT images of non-critical, critical and death groups with COVID-19 had definite characteristics. CT examination plays a vital role in managing the current COVID-19 outbreak, for early detection of COVID-19 pneumonia. In addition, initial CT findings may be useful to stratify patients, which have a potentially important utility in the current global medical situation.

Indexed as

Tomography, X-Ray ComputedAdultAgedAged, 80 and overCOVID-19FemaleHumansIranLogistic ModelsMaleMiddle AgedRadiography, ThoracicRetrospective StudiesRisk FactorsChest CT scanCOVID-2019Factor de riesgoIranIránPredicciónPredictRisk factorTC de tórax

Identifiers

PMID34246422
PMCPMC8064840

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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.