Background: Self-reported mental stress is not consistently recognized as a risk factor for stroke. This prompted development of a novel algorithm for stress-phenotype indices to quantify chronic stress prevalence in relation to a modified stroke risk score in a South African cohort. The algorithm is based on biomarkers adrenocorticotrophic hormone, high-density lipoprotein cholesterol, high-sensitive cardiac-troponin-T, and diastolic blood pressure which exemplifies the stress-ischemic-phenotype index. Further modification of the stroke risk score to accommodate alcohol misuse established the stress-diabetes-phenotype index. Whether positive stress-phenotype individuals will demonstrate a higher incidence of stroke in an independent Swedish cohort was unknown and investigated.
Methods: Stress-phenotyping was done at baseline for 50 participants with incident stroke and 100 age-, and sex matched controls (aged 76 ± 5 years) from 2,924 individuals in southern Sweden. The mean time from inclusion to first stroke event was 5 ± 3 years. Stress-phenotyping comparisons and stroke incidence risk were determined.
Results: A positive stress-ischemic-phenotype reflected higher incident stroke (72% vs. 28%, = 0.019) and mortality rates (41% vs. 23%, = 0.019). Whereas a positive stress-diabetes-phenotype reflected a higher incident stroke rate (80% vs. 20%, = 0.008) but similar mortality rate (38% vs. 25%, = 0.146). Both the positive stress-ischemic (OR: 2.9, 95% CI: 1.3-6.5, = 0.011) and stress-diabetes-phenotypes (OR: 3.7, 95% CI: 1.5-8.9, = 0.004) showed large effect size associations with incident stroke independent of cardiovascular risk confounders.
Conclusion: Positive stress-phenotype indices demonstrated a higher incidence of stroke. Ultimately the Malan stress-phenotype algorithms developed in South Africa could confirm incident stroke in an independent Swedish cohort. Stress-phenotyping could thus be useful in clinical routine practice in order to detect individuals at higher stroke risk.
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http://dx.doi.org/10.1080/10253890.2024.2443980 | DOI Listing |
Sci Rep
December 2024
Department of Neurology, The First Affiliated Hospital of Zhengzhou University, JianShe Road 1#, Zhengzhou, 450000, China.
Previous observational studies have suggested at a potential link between migraine, particularly migraine with aura, and the susceptibility to early-onset ischemic stroke. We aimed to investigate the causal effects of genetically determined migraine and its subtypes on the risk of early-onset ischemic stroke using the two-sample Mendelian randomization method. Genetic instrumental variables associated with migraine and its subtypes were acquired from two sources with the largest sample sizes available.
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December 2024
Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York, USA.
This study investigated the incidence of new-onset cardiovascular disorders up to 3.5 years post SARS-CoV-2 infection for 56,400 individuals with COVID-19 and 1,093,904 contemporary controls without COVID-19 in the Montefiore Health System (03/11/2020 to 07/01/2023). Outcomes were new incidence of major adverse cardiovascular event (MACE), arrhythmias, inflammatory heart disease, thrombosis, cerebrovascular disorders, ischemic heart disease and other cardiac disorders between 30 days and (up to) 3.
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December 2024
Bao Feng Key Laboratory of Genetics and Metabolism, Beijing, China.
Many lipid biomarkers of stroke have been identified, but the lipid metabolism in elderly patients with leukoaraiosis remains poorly understood. This study aims to explore lipid metabolic processes in stroke among leukoaraiosis patients, which could provide valuable insights for guiding future antithrombotic therapy. In a cohort of 215 individuals undergoing MRI, 13 stroke patients were matched with controls, and 48 stroke patients with leukoaraiosis were matched with 40 leukoaraiosis patients.
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December 2024
Neurology Department of Affiliated Hospital of Jiangsu University, No. 438 Jiefang Road, Zhenjiang, Jiangsu, China.
This study aims to compare the incidences of neurological deterioration (ND) and poor outcome (a modified Ranking scale > 2 points at discharge) among patients with different atherosclerotic stroke patterns. A total of 688 participants were categorized into 4 groups according to atherosclerotic stroke pattern: multiple small infarcts (MSI), single subcortical infarction (SSI), borderzone infarct (BZI) and large infarct groups. Among the 4 groups, MSI group had the lowest incidences of ND and poor outcome (13.
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December 2024
Artificial Intelligence in Medical Sciences Research Center, Smart University of Medical Sciences, Tehran, Iran.
Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and mitigate the long-term effects of strokes. The aim of this study is to compare these models, exploring their efficacy in predicting stroke.
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