Clinical features and in-hospital mortality predictors of concurrent cardio-cerebral infarction: insights from a dual-center retrospective study

 Oh my God, predicting a problem; BUT DOING NOTHING TO PREVENT IT! You're fired!

Clinical features and in-hospital mortality predictors of concurrent cardio-cerebral infarction: insights from a dual-center retrospective study

Weiwei Gao^1†Lingfeng Yu^2†Shouyue Jin¹Lijuan Cai¹Jingjing Fang³Xiaoqian Wang²Qingwei Yang¹Xingyu Chen¹Tao Ye^2*Renjing Zhu^1*

• ¹Department of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
• ²Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
• ³Department of Cardiovascular, West China Xiamen Hospital of Sichuan University, Xiamen, China

Objective: This study aimed to enhance the understanding of cardio-cerebral infarction (CCI) clinical features and identify key prognostic factors, thereby providing an empirical foundation for advancing prevention and treatment strategies and ultimately improving clinical outcomes for CCI patients.

Methods: We retrospectively analyzed 17,645 AIS and 7,584 AMI patients admitted to two hospitals from 2014 to 2023. Univariate analysis, Spearman correlation, and multivariate logistic regression were performed to identify independent risk factors. Receiver operating characteristic (ROC) curves were used to determine optimal cutoff values.

Results: This study enrolled 85 patients with CCI, representing an overall CCI incidence of approximately 0.34%. Males comprised 64.71% of the cohort. ST-segment elevation myocardial infarction and cardiogenic cerebral infarction were the most predominant subtypes. The in-hospital mortality rate was 30.59%, with 65.38% of deaths attributed to cardiac causes. Multivariate logistic regression analysis identified three independent risk factors for in-hospital mortality: elevated neutrophil-to-lymphocyte ratio (NLR), decreased serum albumin, and increased peak N-terminal pro-B-type natriuretic peptide levels (NT-proBNP). ROC curve analysis demonstrated that the area under the curve (AUC) for the NLR, albumin concentration and peak NT-proBNP concentration were 0.863, 0.723, and 0.824, respectively. The optimal cutoff values were 6.914 for NLR, 33.80 g/L for albumin, and 9474.50 pg/mL for peak NT-proBNP. The AUC of the combined diagnostic model reached 0.959, significantly outperforming the individual indicators.

Conclusion: Elevated NLR, decreased serum albumin, and increased peak NT-proBNP levels independently predict in-hospital mortality in CCI patients. Combining these biomarkers enhances predictive capability for adverse outcomes.

1 Introduction

Acute myocardial infarction (AMI) and acute ischemic stroke (AIS) are the leading causes of mortality and disability worldwide and pose significant public health challenges (1). AMI remains a primary cause of death in developed countries, while AIS ranks as the second leading cause of mortality and third leading cause of disability globally (2, 3). In 2010, Omar et al. (4) first introduced the concept of cardiocerebral infarction (CCI), defined as the simultaneous or sequential occurrence of AMI and AIS within a short timeframe.

Current CCI research faces several challenges. Firstly, the lack of consensus on the time window for AMI and AIS co-occurrence has led to widely varying reported CCI incidence rates (5), ranging from 0.009 to 12.7% (6–9). Secondly, as a complex critical syndrome involving cardiac and cerebral damage, CCI is characterized by a narrow therapeutic window, complex treatment decisions, poor prognosis, and high mortality (10). These factors significantly complicate clinical management. Therefore, a comprehensive understanding of CCI pathogenesis and clinical features is critical for developing effective treatment strategies. However, evidence-based guidelines and expert consensus on CCI management are scarce, with existing studies predominantly limited to case reports and small case series. Clinicians often rely on single-disease guidelines and empirical approaches for AMI or AIS when formulating treatment plans.

While numerous studies have independently explored predictors of short-term adverse outcomes in patients with AIS or AMI, the CCI, as a composite disease, has more complex pathophysiological mechanisms and diverse clinical features. The risk factors for adverse outcomes in CCI patients may differ significantly from those in patients with isolated AIS or AMI. However, systematic research in this area remains limited.

Given this context, our dual-center study investigated the clinical features of CCI patients and identified independent risk factors for in-hospital mortality. This study aimed to enhance the understanding of CCI clinical features and identify key prognostic factors, thereby providing an empirical foundation for advancing prevention and treatment strategies and ultimately improving clinical outcomes for CCI patients.