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Circular RNAs to predict clinical outcome after cardiac arrest
Francesca M. Stefanizzi
,
Lu Zhang
, Antonio Salgado-Somoza
, Josef Dankiewicz
, Pascal Stammet
, Christian Hassager
, Matthew P. Wise
, Hans Friberg
, Tobias Cronberg
,
Alexander Hundt
, Jesper Kjaergaard
, Niklas Nielsen
,
Yvan Devaux
*
*
Corresponding author for this work
Cardiovascular Research Unit
Biospecimen Processing Team
Research output
:
Contribution to journal
›
Article
›
Research
›
peer-review
8
Citations (Scopus)
Overview
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Keyphrases
Clinical Outcomes
100%
Circular RNA
100%
Cardiac Arrest
100%
Management Experiment
50%
Neurological Outcome
50%
Targeted Temperature Management
50%
Circulating Circular RNA
50%
Novel Biomarkers
16%
Quantitative PCR
16%
Survivors
16%
Adjusted Hazard Ratio
16%
Return of Spontaneous Circulation
16%
Poor Outcome
16%
Adjusted Odds Ratio
16%
Cause of Death
16%
Whole Blood Sample
16%
Good Neurological Outcome
16%
Neurological Sequelae
16%
Blood Biomarkers
16%
In-hospital Death
16%
Whole Transcriptome RNA Sequencing
16%
95% Confidence Interval
16%
Circulating Long Non-coding RNAs
16%
Biochemistry, Genetics and Molecular Biology
Circular RNA
100%
Cardiac Arrest
100%
RNA Sequence
16%
Real-Time Polymerase Chain Reaction
16%
Non-Coding RNA
16%
Return of Spontaneous Circulation
16%
Transcriptome
16%
Neuroscience
Circular RNA
100%
Biological Marker
75%
Non-Coding RNA
25%
Transcriptome
25%
Real-Time Polymerase Chain Reaction
25%
RNA Sequence
25%
Pharmacology, Toxicology and Pharmaceutical Science
Heart Arrest
100%
Biological Marker
50%
Untranslated RNA
16%
Transcriptome
16%
Immunology and Microbiology
Ribonucleic Acid
100%
Transcriptome
20%
Real-Time Polymerase Chain Reaction
20%
RNA Sequence
20%
Return of Spontaneous Circulation
20%