Evidence map›Paper›PMID 34141091›Full record

ReviewWorld journal of radiology2021

Challenges and optimization strategies in medical imaging service delivery during COVID-19.

Yi Xiang Tay, Suchart Kothan, Sundaran Kada, Sihui Cai, Christopher Wai Keung Lai

Abstract readReview
In one paragraph

Review in World journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

5 authors.

Yi Xiang TayRadiography Department, Singapore General Hospital, Singapore 169608, Singapore.
Suchart KothanCenter of Radiation Research and Medical Imaging, Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai 50000, Thailand.
Sundaran KadaFaculty of Health and Social Sciences, Western Norway University of Applied Sciences, Bergen Postbox 7030, 5020 Bergen, Norway.
Sihui CaiRadiography Department, Singapore General Hospital, Singapore 169608, Singapore.
Christopher Wai Keung LaiDepartment of Health and Social Sciences, Singapore Institute of Technology, Singapore 138683, Singapore. chris.lai@singaporetech.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In coronavirus disease 2019 (COVID-19), medical imaging plays an essential role in the diagnosis, management and disease progression surveillance. Chest radiography and computed tomography are commonly used imaging techniques globally during this pandemic. As the pandemic continues to unfold, many healthcare systems worldwide struggle to balance the heavy strain due to overwhelming demand for healthcare resources. Changes are required across the entire healthcare system and medical imaging departments are no exception. The COVID-19 pandemic had a devastating impact on medical imaging practices. It is now time to pay further attention to the profound challenges of COVID-19 on medical imaging services and develop effective strategies to get ahead of the crisis. Additionally, preparation for operations and survival in the post-pandemic future are necessary considerations. This review aims to comprehensively examine the challenges and optimization of delivering medical imaging services in relation to the current COVID-19 global pandemic, including the role of medical imaging during these challenging times and potential future directions post-COVID-19.

Indexed as

COVID-19Medical imaging serviceOptimization strategiesPandemicRadiographyRadiology department

Identifiers

PMID34141091
PMCPMC8188837

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.