Evidence map›Paper›PMID 36160629›Full record

ReviewWorld journal of radiology2022

Molecular imaging as a tool for evaluation of COVID-19 sequelae - A review of literature.

Kunal R Chandekar, Swayamjeet Satapathy, Harmandeep Singh, Anish Bhattacharya

Abstract readReview
In one paragraph

Review in World journal of radiology, 2022. 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
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.

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.

Kunal R ChandekarDepartment of Nuclear Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India.
Swayamjeet SatapathyDepartment of Nuclear Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India. swayamjeet.satapathy@gmail.com.
Harmandeep SinghDepartment of Nuclear Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India.
Anish BhattacharyaDepartment of Nuclear Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) is caused by the novel viral pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 primarily involves the lungs. Nucleic acid testing based on reverse-transcription polymerase chain reaction of respiratory samples is the current gold standard for the diagnosis of SARS-CoV-2 infection. Imaging modalities have an established role in triaging, diagnosis, evaluation of disease severity, monitoring disease progression, extra-pulmonary involvement, and complications. As our understanding of the disease improves, there has been substantial evidence to highlight its potential for multi-systemic involvement and development of long-term sequelae. Molecular imaging techniques are highly sensitive, allowing non-invasive visualization of physiological or pathological processes at a cellular or molecular level with potential for detection of functional changes earlier than conventional radiological imaging. The purpose of this review article is to highlight the evolving role of molecular imaging in evaluation of COVID-19 sequelae. Though not ideal for diagnosis, the various modalities of molecular imaging play an important role in assessing pulmonary and extra-pulmonary sequelae of COVID-19. Perfusion imaging using single photon emission computed tomography fused with computed tomography (CT) can be utilized as a first-line imaging modality for COVID-19 related pulmonary embolism.

Indexed as

COVID-19Functional imagingMolecular imagingNuclear medicineSARS-CoV-2Sequelae

Identifiers

PMID36160629
PMCPMC9350609

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.