Evidence map›Paper›PMID 39474370›Full record

ArticleFrontiers in neurology2024

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

Weiwei Gao, Lingfeng Yu, Shouyue Jin, Lijuan Cai, Jingjing Fang, Xiaoqian Wang, Qingwei Yang, Xingyu Chen, Tao Ye, Renjing Zhu

Abstract read
In one paragraph

Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

10 authors.

Weiwei Gao *Department of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Lingfeng Yu *Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Shouyue JinDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Lijuan CaiDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Jingjing FangDepartment of Cardiovascular, West China Xiamen Hospital of Sichuan University, Xiamen, China.
Xiaoqian WangXiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Qingwei YangDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Xingyu ChenDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Tao YeXiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Renjing ZhuDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

albumincardio-cerebral infarctionin-hospital mortalityneutrophil-to-lymphocyte ratioN-terminal pro-B-type natriuretic peptide

Identifiers

PMID39474370
PMCPMC11520769

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.