scholarly journals Biomarkers, Clinical Variables, and the CHA2DS2-VASc Score to Detect Silent Brain Infarcts in Atrial Fibrillation Patients

2021 ◽  
Vol 23 (3) ◽  
pp. 449-452
Author(s):  
Philipp Krisai ◽  
Ceylan Eken ◽  
Stefanie Aeschbacher ◽  
Michael Coslovsky ◽  
Vinzent Rolny ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Clinical Variables ◽  
Brain Infarcts

scholarly journals The Omega-3 Fatty Acid Eicosapentaenoic Acid (EPA) Correlates Inversely with Ischemic Brain Infarcts in Patients with Atrial Fibrillation

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 651
Author(s):  
Martin F. Reiner ◽  
Philipp Baumgartner ◽  
Andrea Wiencierz ◽  
Michael Coslovsky ◽  
Nicole R. Bonetti ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Fatty Acid ◽  
Small Vessel Disease ◽  
Small Vessel ◽  
Omega 3 ◽  
Total N ◽  
Ischemic Brain ◽  
Omega 3 Fatty Acid ◽  
Vessel Disease ◽  
Brain Infarcts

The omega-3 fatty acid (n-3 FA) eicosapentaenoic acid (EPA) reduces stroke in patients with atherosclerotic cardiovascular disease. Whether EPA affects stroke or cerebral small vessel dis-ease in patients with atrial fibrillation (AF) remains uncertain. EPA, docosahexaenoic acid (DHA), docosapentaenoic acid (DPA), and alpha-linolenic acid (ALA) were determined by gas chromatography in 1657 AF patients from the Swiss Atrial Fibrillation study. All patients underwent brain MRI to detect ischemic brain infarcts, classified as large noncortical or cortical infarcts (LNCCIs); markers of small vessel disease, classified as small noncortical infarcts (SNCIs), number of microbleeds, and white matter lesion (WML) volumes. Individual and total n-3 FAs (EPA + DHA + DPA + ALA) were correlated with LNCCIs and SNCIs using logistic regression, with numbers of microbleeds using a hurdle model, and WML volumes using linear regression. LNCCIs were detected in 372 patients (22.5%). EPA correlated inversely with the prevalence of LNCCIs (odds ratio [OR] 0.51 per increase of 1 percentage point EPA, 95% confidence interval [CI] 0.29–0.90). DPA correlated with a higher LNCCI prevalence (OR 2.48, 95%CI 1.49–4.13). No associations with LNCCIs were found for DHA, ALA, and total n-3 FAs. Neither individual nor total n-3 FAs correlated with markers of small vessel disease. In conclusion, EPA correlates inversely with the prevalence of ischemic brain infarcts, but not with markers of small vessel disease in patients with AF.

P3712The omega-3 fatty acid eicosapentaenoic acid (EPA) is inversely associated with ischemic brain infarcts in elderly patients with atrial fibrillation

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M F Reiner ◽  
P Baumgartner ◽  
A Wiencierz ◽  
S Aeschbacher ◽  
N Rodondi ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Ischemic Stroke ◽  
Elderly Patients ◽  
Eicosapentaenoic Acid ◽  
Brain Mri ◽  
Omega 3 ◽  
Total N ◽  
Stroke Incidence ◽  
Ischemic Brain ◽  
Brain Infarcts

Abstract Background The association of individual omega-3 fatty acids (n-3 FAs) with ischemic stroke remains unclear. Experimental data strongly suggest that n-3 FAs reduce ischemic stroke due to their anti-thrombotic and anti-inflammatory properties. Yet, recent clinical trials yielded mixed results. While marine n-3 FA supplementation (1g/day) did not reduce stroke, icosapent ethyl, a purified eicosapentaenoic acid (EPA) ethyl ester (4g/day), significantly reduced stroke incidence in patients at high cardiovascular risk. In the current study, we examined the association of fish-derived EPA, docosapentaenoic acid (DPA), docosahexaenoic acid (DHA) and the plant-derived alpha-linolenic acid (ALA) with the prevalence of ischemic brain infarcts in elderly patients with atrial fibrillation. Methods In this cross-sectional analysis of the Swiss atrial fibrillation (swissAF) cohort study, we determined baseline whole blood n-3 FAs by gas chromatography according to the HS-Omega-3 Index methodology in 1665 patients aged ≥65 years with atrial fibrillation. Large non-cortical and cortical infarcts (LNCCI) were assessed by brain MRI. Total and individual n-3 FAs were correlated with the prevalence of LNCCI in a logit model with continuous factors. Analyses were adjusted for sex, age, body mass index, smoking, alcohol intake, family history of cardiovascular disease and atrial fibrillation, physical activity, hypertension, diabetes, chronic kidney disease, prior stroke, prior transient ischemic attack, aspirin, anticoagulation and type of atrial fibrillation. Results A total of 373 patients with LNCCI (22.4%) were identified. After adjustment, lower risk of LNCCI was associated with higher EPA (odds ratio [OR] 0.50 per increase of one percentage point EPA, 95% confidence interval [CI] 0.28–0.88) and a higher risk was detected with DPA (OR 2.39, 95% CI 1.43–4.01). No statistically significant association was detected with DHA (OR 1.13, 95% CI 0.94–1.35), ALA (OR 0.83, 95% CI 0.23–2.95) or total n-3 FAs (OR 1.03, 95% CI 0.92–1.16). Conclusions Higher levels of EPA are associated with a lower prevalence of ischemic infarcts in aged patients with atrial fibrillation. Unexpectedly, DPA shows a direct correlation with ischemic infarcts. This study demonstrates that individual n-3 FAs may differentially affect stroke risk and that supplementation of EPA may be an interesting strategy to prevent ischemic stroke in atrial fibrillation patients. Acknowledgement/Funding Swiss National Science Foundation

Association of platelet-to-lymphocyte ratio with silent brain infarcts in patients with paroxysmal atrial fibrillation

2016 ◽  
Vol 38 (9) ◽  
pp. 753-758 ◽  
Author(s):  
Ozge Altintas ◽  
Abdurrahman Tasal ◽  
Elvin Niftaliyev ◽  
Okkes Taha Kucukdagli ◽  
Talip Asil
Keyword(s):  
Atrial Fibrillation ◽  
Paroxysmal Atrial Fibrillation ◽  
Platelet To Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Brain Infarcts

P5710Clinical applications of machine learning for prediction of incident atrial fibrillation from the general population: a nationwide cohort study

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
I.-S Kim ◽  
P S Yang ◽  
H T Yu ◽  
T H Kim ◽  
J S Uhm ◽  
...  
Keyword(s):  
Machine Learning ◽  
Atrial Fibrillation ◽  
Logistic Regression ◽  
General Population ◽  
Regression Model ◽  
National Health ◽  
Logistic Regression Model ◽  
Learning System ◽  
Health Examination ◽  
Clinical Variables

Abstract Background To evaluate the ability of machine learning algorithms to predict incident atrial fibrillation (AF) from the general population using health examination items. Methods We included 483,343 subjects who received national health examinations from the Korean National Health Insurance Service-based National Sample Cohort (NHIS-NSC). We trained deep neural network model (DNN) of a deep learning system and decision tree model (DT) of a machine learning system using clinical variables and health examination items (including age, sex, body mass index, history of heart failure, hypertension or diabetes, baseline creatinine, and smoking and alcohol intake habits) to predict incident AF using a training dataset of 341,771 subjects constructed from the NHIS-NSC database. The DNN and DT were validated using an independent test dataset of 141,572 remaining subjects. C-indices of DNN and DT for prediction of incident AF were compared with that of conventional logistic regression model. Results During 1,874,789 person·years (mean±standard-deviation age 47.7±14.4 years, 49.6% male), 3,282 subjects with incident AF were observed. In the validation dataset, 1,139 subjects with incident AF were observed. The c-indices of the DNN and DT for incident AF prediction were 0.828 [0.819–0.836] and 0.835 [0.825–0.844], and were significantly higher (p<0.01) than conventional logistic regression model (c-index=0.789 [0.784–0.794]). Conclusions Application of machine learning using simple clinical variables and health examination items was helpful to predict incident AF in the general population. Prospective study is warranted to construct an individualized precision medicine.

scholarly journals Association of Heart Rate Variability With Silent Brain Infarcts in Patients With Atrial Fibrillation

2021 ◽  
Vol 8 ◽  
Author(s):  
Peter Hämmerle ◽  
Christian Eick ◽  
Sven Poli ◽  
Steffen Blum ◽  
Vincent Schlageter ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Autonomic Dysfunction ◽  
Brain Mri ◽  
Low Frequency ◽  
Total Power ◽  
Brain Infarcts ◽  
Clinical Covariates ◽  
Prior Stroke ◽  
Mean Heart Rate

Purpose: Silent brain infarcts (SBI) are frequently detected in patients with atrial fibrillation (AF), but it is unknown whether SBI are linked to autonomic dysfunction. We aimed to explore the association of autonomic dysfunction with SBI in AF patients.Methods: 1,358 AF patients without prior stroke or TIA underwent brain MRI and 5-min resting ECG. We divided our cohort into AF patients who presented in sinus rhythm (SR-group, n = 816) or AF (AF-group, n = 542). HRV triangular index (HRVI), standard deviation of normal-to-normal intervals, mean heart rate, root mean square root of successive differences of normal-to-normal intervals, 5-min total power and power in the low frequency, high frequency and very low frequency range were calculated. Primary outcome was presence of SBI in the SR group, defined as large non-cortical or cortical infarcts. Secondary outcomes were SBI volumes and topography.Results: Mean age was 72 ± 9 years, 27% were female. SBI were detected in 10.5% of the SR group and in 19.9% of the AF group (p &lt; 0.001). HRVI &lt;15 was the only HRV parameter associated with the presence of SBI after adjustment for clinical covariates in the SR group [odds ratio (OR) 1.67; 95% confidence interval (CI): 1.03–2.70; p = 0.037]. HRVI &lt;15 was associated with larger brain infarct volumes [β (95% CI) −0.47 (−0.84; −0.09), p = 0.016] in the SR group and was more frequently observed in patients with right- than left-hemispheric SBI (p = 0.017).Conclusion: Impaired HRVI is associated with SBI in AF patients. AF patients with autonomic dysfunction might undergo systematic brain MRI screening to initiate intensified medical treatment.Clinical Trials Gov Identifier: NCT02105844.

scholarly journals Trends of r-tPA (Recombinant Tissue-Type Plasminogen Activator) Treatment and Treatment-Influencing Factors in Acute Ischemic Stroke

Stroke ◽  
2020 ◽  
Vol 51 (4) ◽  
pp. 1240-1247 ◽  
Author(s):  
Martha Marko ◽  
Alexandra Posekany ◽  
Simon Szabo ◽  
Sebastian Scharer ◽  
Stefan Kiechl ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Plasminogen Activator ◽  
Time Trends ◽  
Posterior Circulation ◽  
Tissue Type ◽  
Tissue Type Plasminogen Activator ◽  
Clinical Variables ◽  
Posterior Circulation Stroke ◽  
Type Plasminogen Activator

Background and Purpose— Frequencies of treatment with r-tPA (recombinant tissue-type plasminogen activator) are increasing over the past 15 years. However, published data on the influence of various demographic and clinical factors on r-tPA treatment as well as estimates of future trajectories are limited. We evaluated time trends and future trajectories of r-tPA treatment in patients with acute stroke and the influence of various factors on r-tPA treatment by analyzing data of 103 970 patients enrolled in the Austrian Stroke Unit Registry from 2006 to 2018, of which 18 953 were treated with r-tPA. Methods— Time trends of r-tPA-treatment were investigated in predefined subgroups (minor/major stroke, age, anterior/posterior circulation stroke); limited exponential time series models were calculated to estimate future trends of r-tPA-treatment. Logistic regression models were calculated to estimate the influence of clinical variables on r-tPA-treatment. Results— Overall, r-tPA treatment frequencies increased from 9.9% in 2006 to 21.8% in 2018. We observed a particular increase in patients >80 years, patients presenting with a National Institutes of Health Stroke Scale Score of 2 to 3, patients with posterior circulation stroke, patients with wake-up stroke, and patients without atrial fibrillation. Forecast of overall r-tPA frequencies predicted a further but flattened increase up to 24% by 2025. Logistic regression of time-dependent associations of clinical variables with r-tPA-treatment revealed increasing odds of r-tPA-treatment in patients with a posterior circulation stroke and decreasing odds of r-tPA-treatment in patients with atrial fibrillation. Conclusions— We observed a positive development of r-tPA-treatment frequencies mirroring increasing confidence with intravenous thrombolysis in clinical practice; however, decreasing odds of r-tPA-treatment over time in patients with atrial fibrillation deserve particular attention.

scholarly journals Atrial Fibrillation, Stroke, and Silent Cerebrovascular Disease: A Population-Based MRI Study

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012675
Author(s):  
Lina Rydén ◽  
Simona Sacuiu ◽  
Hanna Wetterberg ◽  
Jenna Najar ◽  
Xinxin Guo ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Small Vessel Disease ◽  
Brain Mri ◽  
Population Based ◽  
Cerebrovascular Diseases ◽  
Register Data ◽  
Self Report ◽  
Birth Date ◽  
Intracranial Volume ◽  
Brain Infarcts

Background and Objectives:Atrial fibrillation (AF) has been associated with cognitive decline and dementia. However, the mechanisms behind these associations are not clear. Examination of cerebrovascular pathology on MRI may shed light on how AF affects the brain. This study aimed to determine whether AF is associated with a broad range of cerebrovascular diseases, beyond the well-known association with symptomatic stroke, including silent infarcts and markers of small vessel disease, e.g. cerebral microbleeds (CMBs), white matter hyperintensities (WMHs), and lacunes, in a population-based sample of 70-year-olds.Methods:Data were obtained from the Gothenburg H70 Birth Cohort Studies, where individuals are invited based on birth-date. This study has a cross-sectional design and includes individuals born 1944 who underwent structural brain MRI in 2014-17. AF diagnoses were based on self-report, EKG, and register data. Symptomatic stroke was based on self-report, proxy-interviews, and register data. Brain infarcts and CMBs were assessed by a radiologist. WMH volumes were measured on FLAIR images using the Lesion Segmentation Tool. Multivariate logistic regression was used to study the association between AF and infarcts/CMBs, and multivariate linear regression was used to study the association between AF and WMHs.Results:A total of 776 individuals were included and 65 (8.4%) had AF. AF was associated with symptomatic stroke (OR 4.5, 95% CI 2.1-9.5), and MRI findings of large infarcts (OR 5.0, 95% CI 1.5-15.9), lacunes (OR 2.7, 95% CI 1.2-5.6), and silent brain infarcts (OR 3.5; 95% CI 1.6-7.4). Among those with symptomatic stroke, individuals with AF had larger WMH volumes (0.0137 ml/total intracranial volume (TIV), 95% CI 0.0074-0.0252) compared to those without AF (0.0043 ml/TIV, 95% CI 0.0029-0.0064). There was no association between AF and WMH volumes among those without symptomatic stroke. In addition, AF was associated to CMBs in the frontal lobe.Discussion:AF was associated with broad range of cerebrovascular pathologies. Further research is needed to establish whether cerebrovascular MRI markers can be added to current treatment guidelines to further personalise anticoagulant treatment in AF patients and to further characterize the pathogenetic processes underlying the associations between AF and cerebrovascular diseases, as well as dementia.

Atrial fibrillation burden: an update—the need for a CHA2DS2-VASc-AFBurden score

EP Europace ◽  
2020 ◽  
Author(s):  
Kathryn D Tiver ◽  
Jing Quah ◽  
Anandaroop Lahiri ◽  
Anand N Ganesan ◽  
Andrew D McGavigan
Keyword(s):  
Atrial Fibrillation ◽  
Risk Factor ◽  
Risk Score ◽  
Independent Risk Factor ◽  
Stroke Risk ◽  
Published Data ◽  
Clinical Risk Score ◽  
Clinical Variables ◽  
Atrial Fibrillation Burden ◽  
Current Guidelines

Abstract Atrial fibrillation (AF) is an established independent risk factor for stroke. Current guidelines regard AF as binary; either present or absent, with the decision for anti-coagulation driven by clinical variables alone. However, there are increasing data to support a biological gradient of AF burden and stroke risk, both in clinical and non-clinical AF phenotypes. As such, this raises the concept of combining AF burden assessment with a clinical risk score to refine and individualize the assessment of stroke risk in AF—the CHA2DS2VASc-AFBurden score. We review the published data supporting a biological gradient to try and construct a putative schema of risk attributable to AF burden.

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