Evidence map›Paper›PMID 36196143›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2022

Combination of TyG Index and GRACE Risk Score as Long-Term Prognostic Marker in Patients with ACS Complicated with T2DM Undergoing PCI.

Zhen Qin, Shuai Xu, Ruixia Yuan, Zeyu Wang, Yongzheng Lu, Yanyan Xu, Yan Lv, Fengyi Yu, Jing Bai, Hui Zhang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 4 pooled it
2.0field-weighted citation impact, top 14% 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

12 citing papers in PubMed, 4 syntheses or guidelines pooled it, 15 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

13 authors at 2 institutions in 1 country.

Zhen QinDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Shuai XuDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Ruixia YuanClinical Big Data Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Zeyu WangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Yongzheng LuDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Yanyan XuDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Yan LvDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Fengyi YuDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Jing BaiDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Hui ZhangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Li ZhangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Jinying ZhangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Junnan TangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
First Affiliated Hospital of Zhengzhou University · CNZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We aimed to investigate the prognostic value of the triglyceride-glucose (TyG) index combined the with Global Registry of Acute Coronary Events (GRACE) score in adult acute coronary syndrome (ACS) patients with type 2 diabetes mellitus (T2DM) who underwent percutaneous coronary intervention (PCI). Methods: The study enrolled total 899 ACS patients with T2DM who underwent PCI. TyG index and the GRACE risk score were calculated and assessed by median. The correlation was analyzed by Spearman's rank correlation coefficient. The cumulative major adverse cardiovascular event (MACE) curve was generated using the Kaplan-Meier method. Multivariate Cox regression was used to identify predictors of MACEs. Additionally, the receiver operating characteristic curve (ROC), net reclassification index (NRI) and Integrated Discrimination Improvement (IDI) were applied to analyze the performance of each single factor index and combined multivariate index in predicting MACE. Results: In the ACS patients with T2DM after PCI, there were significant differences in the TyG index and GRACE risk score between the MACE group and the MACE-free group ( Conclusion: Both the GRACE risk score and the TyG index could be significant and independent predictors of clinical outcomes in ACS patients with T2DM after PCI. A combination of them could be enhanced predictions of clinical outcomes in these patients.

Indexed as

acute coronary syndromeGRACE risk scorepercutaneous coronary interventionpredictive biomarkertriglyceride-glucose indextype 2 diabetes mellitus

Identifiers

PMID36196143
PMCPMC9527003
OpenAlexW4297347846

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.