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ORIGINAL RESEARCH article

Front. Cardiovasc. Med.

Sec. Intensive Care Cardiovascular Medicine

Characteristics and Risk Factors for Mortality in Patients with Acute Coronary Syndrome concomitant Sepsis: A Retrospective Multicenter Cohort Study

Provisionally accepted
Yinuo  ZhuYinuo Zhu1,2Lei  WangLei Wang1,3Yan  LiuYan Liu4Guoying  ZhengGuoying Zheng5Jinxia  ZhangJinxia Zhang1,2*Zhifeng  LiuZhifeng Liu1,6*Ming  WuMing Wu4*
  • 1The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
  • 2Department of Cardiology, General Hospital of Southern Theatre Command of PLA, Guangzhou, China
  • 3High dependency unit, Department of Critical Care Medicine, Central People's Hospital of Zhanjiang, Zhanjiang, China
  • 4Hospita-Acquired Infection Control Department, Shenzhen Second People's Hospital, Shenzhen, China
  • 5Department of Critical Care Medicine, Huadu District People's Hospital of Guangzhou, Guangzhou, China
  • 6Department of Medicine Critical Care Medicine, General Hospital of Southern Theatre Command of PLA, Guangzhou, China

The final, formatted version of the article will be published soon.

Objective The purpose of this research was to examine the risk factors associated with in-hospital mortality in patients with acute coronary syndrome (ACS) concomitant sepsis, and to develop and verify a nomogram model for predicting mortality risk. Methods This multicenter retrospective analysis examined clinical data from patients with ACS concomitant sepsis who were hospitalized in the intensive care units of tertiary hospitals in Southern China between January 2013 and December 2023. In-hospital mortality functioned as the principal outcome. Univariate and multivariate logistic regression analysis, together with LASSO regression, were used to ascertain independent risk factors for the outcome. The evaluation of model performance was conducted by receiver operating characteristic (ROC) curves, area under the curve (AUC), and calibration plots. Results This study comprised a total of 200 patients. During hospitalization, 122 people (61.0%) succumbed. Multivariate logistic regression analysis indicated that the diagnosis of ST-segment elevation myocardial infarction (STEMI) at admission (OR=2.081, 95% CI: 1.120–3.866, P =0.0206), an elevated initial neutrophil count (OR=1.05, 95% CI: 1.000–1.102, P =0.0495), and a history of coronary artery disease (OR=2.953, 95% CI: 1.173–7.436, P =0.0215) were independent risk factors for in-hospital mortality. The nomogram model that includes these parameters exhibited an AUC of 0.641 (95% CI: 0.564-0.718), with a sensitivity of 0.656 and a specificity of 0.603. Calibration curves demonstrated strong concordance between expected and observed results (Hosmer-Lemeshow test P>0.05). Conclusion Patients with ACS concomitant sepsis experience heightened in-hospital mortality, which is substantially correlated with a diagnosis of STEMI at admission, increased initial neutrophil count, and pre-existing coronary artery disease. While the discriminative capacity (AUC=0.641) of this three-factor nomogram necessitates additional enhancement, its commendable calibration provides a first instrument for early risk categorization, illustrating practical applicability for swift evaluation. Extensive investigations are necessary to improve model efficacy.

Keywords: Acute Coronary Syndrome, Sepsis, Risk factors, nomogram, acute myocardial infarction

Received: 11 Sep 2025; Accepted: 29 Oct 2025.

Copyright: © 2025 Zhu, Wang, Liu, Zheng, Zhang, Liu and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Jinxia Zhang, zhjinxia@foxmail.com
Zhifeng Liu, zhifengliu7797@163.com
Ming Wu, boshiyy@126.com

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