Evidence map›Paper›PMID 36819223›Full record

ReviewPolish journal of radiology2023

COVID-19 diagnostic approaches with an extensive focus on computed tomography in accurate diagnosis, prognosis, staging, and follow-up.

Fereshteh Koosha, Mahdieh Ahmadi Kamalabadi, Amirmohammad Yousefi, Davood Bashash

Open access · diamondAbstract readReview
In one paragraph

Review in Polish journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 1 country.

Fereshteh KooshaDepartment of Radiology Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mahdieh Ahmadi KamalabadiNon-communicable Diseases Research Centre, Rafsanjan University of Medical Sciences, Rafsanjan, Iran.
Amirmohammad YousefiDepartment of Haematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Davood BashashDepartment of Haematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shahid Beheshti University of Medical Sciences · IRRafsanjan University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although a long time has passed since its outbreak, there is currently no specific treatment for COVID-19, and it seems that the most appropriate strategy to combat this pandemic is to identify and isolate infected individuals. Various clinical diagnosis methods such as molecular techniques, serologic assays, and imaging techniques have been developed to identify suspected patients. Although reverse transcription-quantitative PCR (RT-qPCR) has emerged as a reference standard method for diagnosis of SARS-CoV-2, the high rate of false-negative results and limited supplies to meet current demand are the main shortcoming of this technique. Based on a comprehensive literature review, imaging techniques, particularly computed tomography (CT), show an acceptable level of sensitivity in the diagnosis and follow-up of COVID-19. Indeed, because lung infection or pneumonia is a common complication of COVID-19, the chest CT scan can be an alternative testing method in the early diagnosis and treatment assessment of the disease. In this review, we summarize all the currently available frontline diagnostic tools for the detection of SARS-CoV-2-infected individuals and highlight the value of chest CT scan in the diagnosis, prognosis, staging, management, and follow-up of infected patients.

Indexed as

computed tomographyCOVID-19 pneumoniaCT scandiagnosisfollow-upSARS-CoV-2

Identifiers

PMID36819223
PMCPMC9907165
OpenAlexW4319350724

What OpenQuestion holds

Textmetadata
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.