2021
DOI: 10.1155/2021/9977312
|View full text |Cite
|
Sign up to set email alerts
|

Potential Influential Factors of In‐Hospital Myocardial Reinfarction in ST‐Segment Elevation Myocardial Infarction (STEMI) Patients: Finding from the Improving Care for Cardiovascular Disease in China‐ (CCC‐) Acute Coronary Syndrome (ACS) Project

Abstract: In this study, 39915 inpatients with a discharge diagnosis of STEMI from the CCC-ACS project phase I and II were included. The prevalence of the medical history, clinical complications on admission and treatment during hospitalization in the STEMI inpatients with and without in-hospital reinfarction was presented. The factors that were differentially distributed and of critical clinical significance (e.g., age, sex, heart rate, smoking, MI history, HF history, COPD history, stroke, hypertension, diabetes, PCI … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 40 publications
(43 reference statements)
0
1
0
Order By: Relevance
“… 30 However, the rates in the present study were similar with data from the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome project, which was also a nationwide registry in China. 31 32 The distinct prevalence of comorbidity in patients with myocardial infarction between countries highlighted the importance of developing risk prediction models for specific populations.…”
Section: Discussionmentioning
confidence: 99%
“… 30 However, the rates in the present study were similar with data from the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome project, which was also a nationwide registry in China. 31 32 The distinct prevalence of comorbidity in patients with myocardial infarction between countries highlighted the importance of developing risk prediction models for specific populations.…”
Section: Discussionmentioning
confidence: 99%