Evidence map›Paper›PMID 32383543›Full record

ArticleJournal of diabetes investigation2020

General glycosylated hemoglobin goals potentially increase myocardial infarction severity in diabetes patients with comorbidities: Insights from a nationwide multicenter study.

Qianzi Che, Yan Zhang, Jianan Wang, Zheng Wan, Xianghua Fu, Jiyan Chen, Hongbing Yan, Yundai Chen, Junbo Ge, Dafang Chen and 1 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Journal of diabetes investigation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 8 institutions in 1 country.

Qianzi CheDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.ORCID https://orcid.org/0000-0002-8688-6628
Yan ZhangDepartment of Cardiology, Peking University First Hospital, Beijing, China.
Jianan WangDepartment of Cardiology, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China.
Zheng WanDepartment of Cardiology, Tianjin Medical University General Hospital, Tianjin, China.
Xianghua FuDepartment of Cardiology, Second Hospital of Hebei Medical University, Shijiazhuang, China.
Jiyan ChenDepartment of Cardiology, Guangdong General Hospital, Guangzhou, China.
Hongbing YanDepartment of Cardiology, Chinese Academy of Medical Sciences & Peking Union Medical College Fuwai Hospital, Beijing, China.
Yundai ChenDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Junbo GeDepartment of Cardiology, Zhongshan Hospital Fudan University, Shanghai, China.
Dafang ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yong HuoDepartment of Cardiology, Peking University First Hospital, Beijing, China.
Peking University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNChinese PLA General Hospital · CNGuangdong General Hospital · CNHebei Medical University · CNSecond Affiliated Hospital of Zhejiang University · CNSun Yat-sen University · CNTianjin Medical University General Hospital · CN

Funding

Abbott FundAstraZenecaEssen Technology (Beijing) Co., Ltd.Lepu Medical Technology (Beijing) Co., Ltd.SanofiShenzhen Salubris Pharmaceuticals Co., Ltd.Tasly Pharmaceutical Group Co., Ltd.
6 · The paper itself

Abstract

AIMS/

introductionWe aimed to investigate the relationship between glycemic status and coronary artery disease (CAD) extent and severity in ST-elevation myocardial infarction (STEMI) patients, and further examine whether diabetes patients could benefit from glycosylated hemoglobin (HbA1c) below the recommended level. MATERIALS AND

methodsConsecutive STEMI patients admitted in 2015-2017 across 244 hospitals were included in the China STEMI Care Project-2. We carried out a cross-sectional study comprising 8,370 participants with a record of HbA1c testing after admission. CAD extent and severity were assessed by admission heart rate, Killip classification and the number of stenosed vessels based on the coronary angiogram.

resultsDiabetes patients showed a greater risk for higher Killip class, admission tachycardia (admission heart rate ≥100 b.p.m.) and multivessel CAD (presence of left main and/or triple vessel disease). Likewise, HbA1c level was significantly associated with CAD extent and severity. While dividing diabetes patients according to general HbA1c targets (HbA1c ≤6.5, 6.5-7.0 and ≥7.0%), diabetes patients with HbA1c ≤6.5% showed a 1.30-fold higher risk for multivessel CAD (adjusted odds ratio 1.30, 95% confidence interval 1.05-1.62). In stratified analysis, the association was even stronger in patients with hypertension (adjusted odds ratio 1.41, 95% confidence interval 1.08-1.86) or hyperlipidemia (adjusted odds ratio 1.57, 95% confidence interval 1.17-2.12).

conclusionsHbA1c level is independently correlated with CAD extent and severity in STEMI patients. HbA1c below generally recommended levels might still increase the risk of CAD progression, especially for diabetes patients with hypertension or hyperlipidemia.

Indexed as

Severity of Illness IndexBiomarkersBlood GlucoseChinaComorbidityCoronary Artery DiseaseCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleFollow-Up StudiesGlycated HemoglobinHumansMaleMiddle AgedPrognosisProspective StudiesBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanDiabetes mellitusGlycosylated hemoglobinST-segment elevation myocardial infarction

Identifiers

PMID32383543
PMCPMC7610123
OpenAlexW3022097257

What OpenQuestion holds

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LicenceCC BY-NC
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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.