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Comparisons of Prehospital Delay and Related Factors Between Acute Ischemic Stroke and Acute Myocardial Infarction.

ABSTRACT: Background Prehospital delay is an important contributor to poor outcomes in both acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We aimed to compare the prehospital delay and related factors between AIS and AMI. Methods and Results We identified patients with AIS and AMI who were admitted to the 11 Korean Regional Cardiocerebrovascular Centers via the emergency room between July 2016 and December 2018. Delayed arrival was defined as a prehospital delay of >3 hours, and the generalized linear mixed-effects model was applied to explore the effects of potential predictors on delayed arrival. This study included 17 895 and 8322 patients with AIS and AMI, respectively. The median value of prehospital delay was 6.05 hours in AIS and 3.00 hours in AMI. The use of emergency medical services was the key determinant of delayed arrival in both groups. Previous history, 1-person household, weekday presentation, and interhospital transfer had higher odds of delayed arrival in both groups. Age and sex had no or minimal effects on delayed arrival in AIS; however, age and female sex were associated with higher odds of delayed arrival in AMI. More severe symptoms had lower odds of delayed arrival in AIS, whereas no significant effect was observed in AMI. Off-hour presentation had higher and prehospital awareness had lower odds of delayed arrival; however, the magnitude of their effects differed quantitatively between AIS and AMI. Conclusions The effects of some nonmodifiable and modifiable factors on prehospital delay differed between AIS and AMI. A differentiated strategy might be required to reduce prehospital delay.

SUBMITTER: Yoon CW

PROVIDER: S-EPMC9238627 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Comparisons of Prehospital Delay and Related Factors Between Acute Ischemic Stroke and Acute Myocardial Infarction.

Yoon Cindy W CW Oh Hoonji H Lee Juneyoung J Rha Joung-Ho JH Woo Seong-Ill SI Lee Won Kyung WK Jung Han-Young HY Ban Byeolnim B Kang Jihoon J Kim Beom Joon BJ Kim Won-Seok WS Yoon Chang-Hwan CH Lee Heeyoung H Kim Seongheon S Kim Sung Hun SH Kang Eun Kyoung EK Her Ae-Young AY Cha Jae-Kwan JK Kim Dae-Hyun DH Kim Moo-Hyun MH Lee Jang Hoon JH Park Hun Sik HS Kim Keonyeop K Kim Rock Bum RB Choi Nack-Cheon NC Hwang Jinyong J Park Hyun-Woong HW Park Ki Soo KS Yi SangHak S Cho Jae Young JY Kim Nam-Ho NH Choi Kang-Ho KH Kim Yongcheol Y Kim Juhan J Han Jae-Young JY Choi Jay Chol JC Kim Song-Yi SY Choi Joon-Hyouk JH Kim Jei J Jee Sung Ju SJ Sohn Min Kyun MK Choi Si Wan SW Shin Dong-Ick DI Lee Sang Yeub SY Bae Jang-Whan JW Lee Kunsei K Bae Hee-Joon HJ

Journal of the American Heart Association 20220502 9

Background Prehospital delay is an important contributor to poor outcomes in both acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We aimed to compare the prehospital delay and related factors between AIS and AMI. Methods and Results We identified patients with AIS and AMI who were admitted to the 11 Korean Regional Cardiocerebrovascular Centers via the emergency room between July 2016 and December 2018. Delayed arrival was defined as a prehospital delay of >3 hours, and the ge ...[more]

PMID: 35491981

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Project description:BackgroundAcute ischemic stroke (AIS) and acute myocardial infarction (AMI) share several features on multiple levels. These two events may occur in conjunction or in rapid succession, and the occurrence of one event may increase the risk of the other. Owing to their similar pathophysiologies, we aimed to identify immune-related biomarkers common to AIS and AMI as potential therapeutic targets.MethodsWe identified differentially expressed genes (DEGs) between the AIS and control groups, as well as AMI and control groups using microarray data (GSE16561 and GSE123342). A weighted gene co-expression network analysis (WGCNA) approach was used to identify hub genes associated with AIS and/or AMI progression. The intersection of the four gene sets identified key genes, which were subjected to functional enrichment and protein-protein interaction (PPI) network analyses. We confirmed the expression levels of hub genes using two sets of gene expression profiles (GSE58294 and GSE66360), and the ability of the genes to distinguish patients with AIS and/or AMI from control patients was assessed by calculating the receiver operating characteristic values. Finally, the investigation of transcription factor (TF)-, miRNA-, and drug-gene interactions led to the discovery of therapeutic candidates.ResultsWe identified 477 and 440 DEGs between the AIS and control groups and between the AMI and control groups, respectively. Using WGCNA, 2,776 and 2,811 genes in the key modules were identified for AIS and AMI, respectively. Sixty key genes were obtained from the intersection of the four gene sets, which were used to identify the 10 hub genes with the highest connection scores through PPI network analysis. Functional enrichment analysis revealed that the key genes were primarily involved in immunity-related processes. Finally, the upregulation of five hub genes was confirmed using two other datasets, and immune infiltration analysis revealed their correlation with certain immune cells. Regulatory network analyses indicated that GATA2 and hsa-mir-27a-3p might be important regulators of these genes.ConclusionUsing comprehensive bioinformatics analyses, we identified five immune-related biomarkers that significantly contributed to the pathophysiological mechanisms of both AIS and AMI. These biomarkers can be used to monitor and prevent AIS after AMI, or vice versa.

Dataset Information

Comparisons of Prehospital Delay and Related Factors Between Acute Ischemic Stroke and Acute Myocardial Infarction.

Publications

Comparisons of Prehospital Delay and Related Factors Between Acute Ischemic Stroke and Acute Myocardial Infarction.

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