Open access
264
Views
2
CrossRef citations to date
0
Altmetric
ORIGINAL RESEARCH
Comparison of Different Systemic Inflammatory Markers in Predicting Clinical Outcomes with Syntax Score in Patients with Non-ST Segment Elevation Myocardial Infarction: A Retrospective Study
Hong Li1 Emergency & Critical Care Center, Beijing Anzhen Hospital, Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence[email protected]
View further author information
, View further author information
Shuai Meng2 Department of Cardiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, People’s Republic of ChinaView further author information
, Weiguang Chen3 Department of Cardiology, 1st Hospital Affiliated of Hebei North University, Zhangjiakou, Hebei Province, People’s Republic of ChinaView further author information
, Xuan Lei4 Department of Cardiology, Beijing Chest Hospital, Capital Medical University, Beijing, People’s Republic of ChinaView further author information
, Xiangyun Kong5 Department of General Medicine, Beijing Luhe Hospital, Capital Medical University, Beijing, People’s Republic of ChinaView further author information
& Huagang Zhu6 Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, People’s Republic of China
https://orcid.org/0000-0002-2904-6331View further author information
Pages 2595-2607
|
Received 22 Mar 2023, Accepted 09 Jun 2023, Published online: 19 Jun 2023
Reprints and Permissions
Permission is granted subject to the terms of the License under which the work was published. Permission will be required if your reuse is not covered by the terms of the License.
To request a reprint or commercial or derivative permissions for this article, please click on the relevant link below.
For more information please visit our Permissions help page.
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.