Evidence map›Paper›PMID 36856591›Full record

ArticleAnatolian journal of cardiology2023

Downregulated Circulating Long Non-coding RNA GAS6-AS1 Screens and Predicts Acute Myocardial Infarction.

Zhenhua Wang, Mingqing Zhang, Yan Fu

Open access · diamondAbstract read
In one paragraph

Article in Anatolian journal of cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 4 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

3 authors at 1 institution in 1 country.

Zhenhua WangDepartment of Emergency, Beijing JiShuiTan Hospital, Beijing, China.
Mingqing ZhangDepartment of Emergency, Beijing JiShuiTan Hospital, Beijing, China.
Yan FuDepartment of Emergency, Beijing JiShuiTan Hospital, Beijing, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute myocardial infarction seriously threatens human health and life quality, which needs novel biomarkers to improve its early detection and development prediction. This study aimed to assess the potential of long non-coding RNA GAS6-AS1 in discriminating acute myocardial infarction patients and predicting patients' outcomes.

methodsThe circulating expression of GAS6-AS1 in 83 acute myocardial infarction patients and 62 healthy individuals was evaluated using polymerase chain reaction. The value of GAS6-AS1 in the distinguishing acute myocardial infarction patients was evaluated with receiver operating characteristic analysis, and its prognosis predictive potential was assessed by Kaplan-Meier and Cox analysis. Additionally, the correlation of GAS6-AS1 with patients' critical features was evaluated by Spearman's correlation analysis.

resultsSignificant downregulation of GAS6-AS1 was observed in the plasma of acute myocardial infarction patients relative to healthy individuals. Reduced GAS6-AS1 could discriminate acute myocardial infarction patients from healthy controls and indicate patients' unoptimistic prognosis. Moreover, GAS6-AS1 was found to be negatively cor-related with the levels of creatine kinase, creatine kinasemyocardial bland, lactic dehy-drogenase, hydroxybutyrate dehydrogenase, troponin T, and positively correlated with the ejection fraction of acute myocardial infarction patients.

conclusionChanges in circulating GAS6-AS1 in acute myocardial infarction served as a potential diagnostic and prognostic biomarker of acute myocardial infarction.

Indexed as

Myocardial InfarctionRNA, Long NoncodingCreatineCreatine KinaseDown-RegulationHumansCreatineCreatine KinaseRNA, Long Noncoding

Identifiers

PMID36856591
PMCPMC9995557
OpenAlexW4322718916

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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.