Evidence map›Paper›PMID 35846283›Full record

ArticleFrontiers in endocrinology2022

Impact of Metabolic Syndrome and Its Components on Clinical Severity and Long-Term Prognosis in Patients With Premature Myocardial Infarction.

Jing Gao, Yuan Wang, Ya-Nan Yang, Xiao-Yuan Wu, Yan Cui, Zhong-He Zou, Zhuang Cui, Yin Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

11 citing papers in PubMed, 28 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

8 authors at 3 institutions in 1 country.

Jing GaoChest Hospital, Tianjin University, Tianjin, China.
Yuan WangThoracic Clinical College, Tianjin Medical University, Tianjin, China.
Ya-Nan YangCancer Department, Daping Hospital, Army Medical University, Chongqing, China.
Xiao-Yuan WuThoracic Clinical College, Tianjin Medical University, Tianjin, China.
Yan CuiThoracic Clinical College, Tianjin Medical University, Tianjin, China.
Zhong-He ZouThoracic Clinical College, Tianjin Medical University, Tianjin, China.
Zhuang CuiEpidemiology and Biostatistics Institute, School of Public Health, Tianjin Medical University, Tianjin, China.
Yin LiuThoracic Clinical College, Tianjin Medical University, Tianjin, China.
Tianjin Medical University · CNArmy Medical University · CNTianjin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The effects of metabolic syndrome (MS) on premature myocardial infarction (PMI) are not clear to date. This study aimed to investigate the impact of MS and its components on clinical severity and long-term prognosis in patients with PMI. Methods: We enrolled 772 patients aged ≤45 years old who were diagnosed with acute myocardial infarction (AMI) at our hospital consecutively between 2015 and 2020. The patients were divided into an MS group and non-MS group. The parameters of clinical severity were compared using regression analysis. Patients were followed for median of 42 months for major adverse cardiovascular events (MACE). Results: Hyperglycemia was associated with multi-vessel disease [odds ratio Conclusions: In patients with PMI, 1) hyperglycemia usually indicates more severe lesions; 2) MS as a whole was an independent risk factor for MACE; 3) BMI ≥28.0 kg/m

Indexed as

HyperglycemiaMetabolic SyndromeMyocardial InfarctionHumansMiddle AgedPrognosisRisk Factorsclinical severitylong-term prognosisMACEmetabolic syndromepremature myocardial infarction

Identifiers

PMID35846283
PMCPMC9279730
OpenAlexW4283729754

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.