Evidence map›Paper›PMID 34766163›Full record

ReviewView (Beijing, China)2021

Point-of-care detection of cytokines in cytokine storm management and beyond: Significance and challenges.

Guozhen Liu, Cheng Jiang, Xiaoting Lin, Yang Yang

Open access · goldAbstract readReview
In one paragraph

Review in View (Beijing, China), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 6% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 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

4 authors at 3 institutions in 3 countries.

Guozhen LiuSchool of Life and Health Sciences The Chinese University of Hong Kong Shenzhen 518172 P.R. China.ORCID https://orcid.org/0000-0002-0556-6404
Cheng JiangNuffield Department of Clinical Neurosciences John Radcliffe Hospital University of Oxford Oxford OX3 9DU United Kingdom.
Xiaoting LinGraduate School of Biomedical Engineering University of New South Wales Sydney NSW 2052 Australia.
Yang YangSchool of Life and Health Sciences The Chinese University of Hong Kong Shenzhen 518172 P.R. China.
UNSW Sydney · AUChinese University of Hong Kong, Shenzhen · CNJohn Radcliffe Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cytokines are signaling molecules between cells in immune system. Cytokine storm, due to the sudden acute increase in levels of pro-inflammatory circulating cytokines, can result in disease severity and major-organ damage. Thus, there is urgent need to develop rapid, sensitive, and specific methods for monitoring of cytokines in biology and medicine. Undoubtedly, point-of-care testing (POCT) will provide clinical significance in disease early diagnosis, management, and prevention. This review aims to summarize and discuss the latest technologies for detection of cytokines with a focus on POCT. The overview of diseases resulting from imbalanced cytokine levels, such as COVID-19, sepsis and other cytokine release syndromes are presented. The clinical cut-off levels of cytokine as biomarkers for different diseases are summarized. The challenges and perspectives on the development of cytokine POCT devices are also proposed and discussed. Cytokine POCT devices are expected to be the ongoing spotlight of disease management and prevention during COVID-19 pandemic and also the post COVID-19 pandemic era.

Indexed as

COVID‐19cytokine biosensorscytokine stormdisposable sensorspoint‐of‐care diagnostics

Identifiers

PMID34766163
PMCPMC8242812
OpenAlexW3158731709

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.