Evidence map›Paper›PMID 39725628›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2024

[Association between serum BIN1 level and Killip class in patients with acute myocardial infraction].

Yanni Wang, Xia Huang, Fuheng Chen, Yuanyuan Gao, Xiangrong Cui, Qin Yan, Xuan Jing

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Yanni WangFifth Clinical Medical College of Shanxi Medical University, Taiyuan 030012, China.
Xia HuangFifth Clinical Medical College of Shanxi Medical University, Taiyuan 030012, China.
Fuheng ChenClinical Laboratory, Shanxi Provincial People's Hospital, Fifth Hospital of Shanxi Medical University, Taiyuan 030012, China.
Yuanyuan GaoStatistics for Laboratory Animal Centre, Shanxi Provincial People's Hospital, Taiyuan 030012, China.
Xiangrong CuiReproductive Medicine Center, Women and Children's Health Center of Shanxi Province, Taiyuan 030013, China.
Qin YanSecond Clinical College of Shanxi Medical University, Taiyuan 030002, China.
Xuan JingFifth Clinical Medical College of Shanxi Medical University, Taiyuan 030012, China.

Funding

National Natural Science Foundation of China 82000302
6 · The paper itself

Abstract

objectivesTo investigate the correlation of serum levels of bridging integrating factor 1 (BIN1) with acute myocardial infarction (AMI) and Killip class of the patients.

methodsWe retrospectively collected the data from 94 patients with AMI and 30 healthy individuals for analysis of the correlations of serum BIN1 levels with Killip class, TIMI scores, and neutrophil-to-lymphocyte ratio (NLR). We also assessed the diagnostic value of BIN1 combined with NLR for AMI.

resultsSerum BIN1 levels were significantly lower in AMI patients than in the healthy individuals (

conclusionsBIN1 is correlated with AMI and can be helpful for predicting short-term prognosis of the patients, and BIN1 combined with NLR has a high diagnostic value for AMI.

Indexed as

Adaptor Proteins, Signal TransducingMyocardial InfarctionNuclear ProteinsTumor Suppressor ProteinsFemaleHumansLymphocytesMaleMiddle AgedNeutrophilsPrognosisRetrospective StudiesAdaptor Proteins, Signal TransducingBIN1 protein, humanNuclear ProteinsTumor Suppressor Proteinsacute myocardial infractionbridging integrator 1Killip classificationsneutrophils-to-lymphocyte ratioTIMI scores

Identifiers

PMID39725628
PMCPMC11683350

What Socratic holds

Textmetadata
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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 Socratic graph.