Atrial Fibrillation Detection: Fishing for An Irregular Heartbeat Before and After Stroke

FCER1G as a novel immune-associated blood biomarker in cardiogenic stroke

Background

Cardioembolic stroke (CE) exhibits the highest recurrence rate and mortality rate among all subtypes of cerebral ischemic stroke (CIS), yet its pathogenesis remains uncertain. The immune system plays a pivotal role in the progression of CE. Growing evidence indicates that several immune-associated blood biomarkers may inform the causes of stroke. The study aimed to identify new immune-associated blood biomarkers in patients with CE and create an online predictive tool in distinguishing CE from noncardioembolic stroke (non-CE) in CIS.

Methods

Gene expression profiles that were publicly available were obtained from the Gene Expression Omnibus (GEO). The identification of differentially expressed genes (DEGs) was conducted using the Limma package. The hub module and hub genes were identified through the application of weighted gene coexpression network analysis (WGCNA). In order to identify potential diagnostic biomarkers for CE, both the random forest (RF) model and least absolute shrinkage and selection operator (LASSO) regression analysis were employed. Concurrently, the CIBERSORT algorithm was employed to evaluate the infiltration of immune cells in CE samples and examine the correlation between the biomarkers and the infiltrating immune cells. The diagnostic gene expression in blood samples was confirmed using qRT-PCR in a self-constructed dataset. Univariate and multiple logistic regression analyses were used to identify the risk factors for CE. Subsequently, the mathematical model of the nomogram was employed via Java's "Spring Boot" framework to develop the corresponding online tool, which was then deployed on a cloud server utilizing "nginx".

Results

Eleven differentially expressed genes (DEGs) that were upregulated and seven DEGs that were downregulated were identified. Through bioinformatics analysis and clinical sample verification, it was discovered that Fc Fragment of IgE Receptor Ig (FCER1G) could serve as a novel potential blood biomarker for CE. FCER1G, along with other risk factors associated with CE, were utilized to develop a nomogram. The training and validation sets, which consisted of 65 CIS patients, yielded areas under the curve (AUCs) of 0.9722 and 0.9689, respectively. These results indicate a high level of precision in risk delineation by the nomogram. Furthermore, the associated online predictive platform has the potential to serve as a more efficacious and appropriate predictive instrument (https://www.origingenetic.com/CardiogenicStroke-FCER1G) for distinguishing between CE and non-CE.

Conclusion

Blood biomarker FCER1G has the potential to identify patients who are at a higher risk of cardioembolism and direct the search for occult AF.The utilization of this online tool is anticipated to yield significant implications in terms of distinguishing between CE and non-CE, as well as enhancing the optimization of treatment decision support.

Artificial intelligence-enhanced 12-lead electrocardiography for identifying atrial fibrillation during sinus rhythm (AIAFib) trial: protocol for a multicenter retrospective study

Introduction

Atrial fibrillation (AF) is the most common arrhythmia, contributing significantly to morbidity and mortality. In a previous study, we developed a deep neural network for predicting paroxysmal atrial fibrillation (PAF) during sinus rhythm (SR) using digital data from standard 12-lead electrocardiography (ECG). The primary aim of this study is to validate an existing artificial intelligence (AI)-enhanced ECG algorithm for predicting PAF in a multicenter tertiary hospital. The secondary objective is to investigate whether the AI-enhanced ECG is associated with AF-related clinical outcomes.

Methods and analysis

We will conduct a retrospective cohort study of more than 50,000 12-lead ECGs from November 1, 2012, to December 31, 2021, at 10 Korean University Hospitals. Data will be collected from patient records, including baseline demographics, comorbidities, laboratory findings, echocardiographic findings, hospitalizations, and related procedural outcomes, such as AF ablation and mortality. De-identification of ECG data through data encryption and anonymization will be conducted and the data will be analyzed using the AI algorithm previously developed for AF prediction. An area under the receiver operating characteristic curve will be created to test and validate the datasets and assess the AI-enabled ECGs acquired during the sinus rhythm to determine whether AF is present. Kaplan-Meier survival functions will be used to estimate the time to hospitalization, AF-related procedure outcomes, and mortality, with log-rank tests to compare patients with low and high risk of AF by AI. Multivariate Cox proportional hazards regression will estimate the effect of AI-enhanced ECG multimorbidity on clinical outcomes after stratifying patients by AF probability by AI.

Discussion

This study will advance PAF prediction based on AI-enhanced ECGs. This approach is a novel method for risk stratification and emphasizes shared decision-making for early detection and management of patients with newly diagnosed AF. The results may revolutionize PAF management and unveil the wider potential of AI in predicting and managing cardiovascular diseases.

Ethics and dissemination

The study findings will be published in peer-reviewed publications and disseminated at national and international conferences and through social media. This study was approved by the institutional review boards of all participating university hospitals. Data extraction, storage, and management were approved by the data review committees of all institutions.

Clinical Trial Registration

[cris.nih.go.kr], identifier (KCT0007881).

The use of digital health in heart rhythm care

INTRODUCTION

Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligence, machine learning, and other novel technologies, digital health is particularly relevant to the field of cardiac arrhythmias, with roles pertinent to education, prevention, diagnosis, management, prognosis, and surveillance.

AREAS COVERED

This review summarizes information on the clinical use of digital health technology in arrhythmia care and discusses its opportunities and challenges.

EXPERT OPINION

Digital health has begun to play an essential role in arrhythmia care regarding diagnostics, long-term monitoring, patient education and shared decision making, management, medication adherence, and research. Despite remarkable advances, integrating digital health technologies into healthcare faces challenges, including patient usability, privacy, system interoperability, physician liability, analysis and incorporation of the huge amount of real-time information from wearables, and reimbursement. Successful implementation of digital health technologies requires clear objectives and deep changes to existing workflows and responsibilities.

Subcutaneous mechano-electrocardiogram (MECG) sensor for complementary cardiac diagnosis

Since the heart pumps out the blood through the excitation-contraction coupling, simultaneous monitoring of the electrical and mechanical characteristics is beneficial for comprehensive diagnosis of cardiac disorders. Currently, these characteristics are monitored separately with electrocardiogram (ECG) and medical imaging techniques. This work presents a fully implantable device named mechano-electrocardiogram (MECG) sensor that can measure mechanocardiogram (MCG) and ECG together. The key to the success is fabrication of permeable electrodes on a single low-modulus porous nanofiber mat, which helps immediate adhesion of the sensor on the tissue. A strain-insensitive electrode is used as the ECG electrode and a strain-sensitive electrode is used for MCG. The MECG device is implanted subcutaneously in the skin above the heart of the rat. Through a vasopressor (phenylephrine) injection test, the MECG signals indicate that the MCG amplitude is related with blood pressure and the ECG peak interval is more related with heart rate. These results confirm that the MECG device is clinically meaningful for continuous and comprehensive monitoring of the electrical and mechanical characteristics of the heart.

MGNN: A multiscale grouped convolutional neural network for efficient atrial fibrillation detection

The reliable detection of atrial fibrillation (AF) is of great significance for monitoring disease progression and developing tailored care paths. In this work, we proposed a novel and robust method based on deep learning for the accurate detection of AF. Using RR interval sequences, a multiscale grouped convolutional neural network (MGNN) combined with self-attention was designed for automatic feature extraction, and AF and non-AF classification. An average accuracy of 97.07% was obtained in the 5-fold cross-validation. The generalization ability of the proposed MGNN was further independently tested on four other unseen datasets, and the accuracy was 92.23%, 96.86%, 94.23% and 95.91%. Moreover, comparison of the network structures indicated that the MGNN had not only better detection performance but also lower computational complexity. In conclusion, the proposed model is shown to be an efficient AF detector that has great potential for use in clinical auxiliary diagnosis and long-term home monitoring based on wearable devices.

Atrial fibrillation detection using a automated electrocardiographic monitoring in a transient ischaemic attack service

Background

The vast majority of the transient ischaemic attacks (TIA) services in UK reported significant delays in the initiation of the routine cardiac monitoring that may result in a significant number of missed atrial fibrillation (AF) paroxysms and increased long-term risk of recurrent stroke. Automated continuous ECG monitoring (ACEM) system has shown promising results in terms of AF detection but it is unclear if ACEM improves AF detection in a rapid outpatient TIA service.

Objectives

We assessed ACEM in patients with TIA with the aim to significantly reduce the delay to initiate the cardiac monitoring and to enhance the yield of AF detection in these patients. We also aimed to determine the impact of a more rapid initiation of ACEM on the 6-month risk of recurrent stroke/TIA.

Methods

This is an observational, prospective before (phase 1: 1 July to 31 December 2018) versus after (phase 2: 1 January to 30 June 2019) study of the effect of ACEM, compared with routine initiation of 24h-Holter ECG, in patients with TIA assessed in our service.

Results

The phase 1 (n=136) and phase 2 (n=105) cohorts did not differ with regards to age, risk factors, duration of cardiac monitoring. The rate of newly detected AF was significantly higher in phase 2 compared with phase 1 (9.52% vs 2.21%, p<0.001). The 6-month risk of recurrent stroke/TIA was significantly lower in phase 2 compared with phase 1 (7.4% vs 1%, p=0.018).

Conclusions

Early initiation of ACEM improves AF detection after TIA in a rapid TIA service and is associated with a reduced risk of recurrent TIA/stroke.

Mobile Single-Lead Electrocardiogram Technology for Atrial Fibrillation Detection in Acute Ischemic Stroke Patients

(1) Background: AliveCor KardiaMobile (KM) is a portable electrocardiography recorder for detection of atrial fibrillation (AF). The aim of the study was to define the group of acute ischemic stroke (AIS) patients who can use the KM device and assess the diagnostic test accuracy. (2) Methods: the AIS patients were recruited to the study. Thirty-second single-lead electrocardiogram (ECG) usages were recorded on demand for three days using KM portable device. Each KM ECG record was verified by a cardiologist. The feasibility was evaluated using operationalization criteria. (3) Results: the recruitment rate among AIS patients was 26.3%. The withdrawal rate before the start of the intervention was 26%. The withdrawal rate after the start of the intervention was 6%. KM device detected AF in 2.8% of AIS patients and in 2.2% of ECG records. Cardiologist confirmed the AF in 0.3% AIS patients. Sensitivity and specificity of KM for AF was 100% and 98.3%, respectively. (4) Conclusions: the results of this study suggest that it is feasible to use KM device to detect AF in the selected AIS patients (younger and in better neurological condition). KM detected AF in the selected AIS patients with high specificity and sensitivity.

Costs of Stroke and Incidence of First Diagnosis of Atrial Fibrillation at Time of Stroke. Neurology Ward Hospital Poznań, Poland 2018

Stroke is a major cause of morbidity in industrialized countries, representing 8% of total deaths across Europe in 2017. It is also a very costly disorder, frequently caused by atrial fibrillation. We aimed to calculate the cost of stroke hospitalization in 2018 in Poznań (Poland). We also intended to present patients with the first AF diagnosis at the time of stroke. The study was conducted from January 2019 to July 2020. Data were obtained from hospital records and from the hospital accounting department. Out of 164 patients included in the study, 41 had AF and in 18 cases AF was first diagnosed at the time of stroke. The cost of hospitalization in Poznań was EUR 139,257.21 (x¯= EUR 849.13). Among those with concomitant AF, the general cost of inpatient care was EUR 33,859.18 (x¯= EUR 825.83). Considering those who had AF first diagnosed during hospitalization the cost was EUR 16,248.97 (x¯= EUR 906.24). Stroke is associated with high costs of inpatient care, which turned out to be higher among those with AF first diagnosed at the time of stroke. The number of patients who used oral anticoagulants at the time of admission was relatively low. The most frequently used NOAC was dabigatran.

Cost-effectiveness of insertable cardiac monitors for diagnosis of atrial fibrillation in cryptogenic stroke in Australia

INTRODUCTION

Detection of atrial fibrillation (AF) is required to initiate oral anticoagulation (OAC) after cryptogenic stroke (CS). However, paroxysmal AF can be difficult to diagnose with short term cardiac monitoring. Taking an Australian payer perspective, we evaluated whether long-term continuous monitoring for 3 years with an insertable cardiac monitor (ICM) is cost-effective for preventing recurrent stroke in patients with CS.

METHODS

A lifetime Markov model was developed to simulate the follow-up of patients, comparing long-term continuous monitoring with an ICM to monitoring by conventional care. We used a linked evidence approach to estimate the rates of recurrent stroke when AF detection leads to initiation of OAC, as detected using ICM during the lifetime of the device or as detected using usual care. All diagnostic and patient management costs were modeled. Other model inputs were determined by literature review. Probabilistic sensitivity analysis (PSA) was undertaken to explore the effect of parameter uncertainty according to CHADS2 score and OAC treatment effect.

RESULTS

In the base-case analysis, the model predicted an incremental cost-effectiveness ratio (ICER) of A$29 570 per quality-adjusted life year (QALY). Among CHADS2 subgroups analyses, the ICER ranged from A$26 342/QALY (CHADS2 = 6) to A$42 967/QALY (CHADS2 = 2). PSA suggested that the probabilities of ICM strategy being cost-effective were 53.4% and 78.7%, at thresholds of $30 000 (highly cost-effective) and $50 000 per QALY (cost-effective), respectively.

CONCLUSIONS

Long-term continuous monitoring with an ICM is a cost-effective intervention to prevent recurrent stroke in patients following CS in the Australian context.

Combined Omic Analyzes of Cerebral Thrombi: A New Molecular Approach to Identify Cardioembolic Stroke Origin

[Figure: see text].

ECG Restitution Analysis and Machine Learning to Detect Paroxysmal Atrial Fibrillation: Insight from the Equine Athlete as a Model for Human Athletes

Atrial fibrillation is the most frequent arrhythmia in both equine and human athletes. Currently, this condition is diagnosed via electrocardiogram (ECG) monitoring which lacks sensitivity in about half of cases when it presents in paroxysmal form. We investigated whether the arrhythmogenic substrate present between the episodes of paroxysmal atrial fibrillation (PAF) can be detected using restitution analysis of normal sinus-rhythm ECGs. In this work, ECG recordings were obtained during routine clinical work from control and horses with PAF. The extracted QT, TQ, and RR intervals were used for ECG restitution analysis. The restitution data were trained and tested using k-nearest neighbor (k-NN) algorithm with various values of neighbors k to derive a discrimination tool. A combination of QT, RR, and TQ intervals was used to analyze the relationship between these intervals and their effects on PAF. A simple majority vote on individual record (one beat) classifications was used to determine the final classification. The k-NN classifiers using two-interval measures were able to predict the diagnosis of PAF with area under the receiving operating characteristic curve close to 0.8 (RR, TQ with k ≥ 9) and 0.9 (RR, QT with k ≥ 21 or TQ, QT with k ≥ 25). By simultaneously using all three intervals for each beat and a majority vote, mean area under the curves of 0.9 were obtained for all tested k-values (3-41). We concluded that 3D ECG restitution analysis can potentially be used as a metric of an automated method for screening of PAF.

Predicting Atrial Fibrillation with High Risk of Embolization with Atrial Strain and NT-proBNP

The aim of the study was to determine markers of atrial dysfunction in patients with cryptogenic stroke to predict episodes of paroxysmal atrial fibrillation with high risk of embolization (HpAF). We classified patients included in the Crypto-AF study, Cryptogenic Stroke registry, to detect paroxysmal atrial fibrillation (pAF) with wearable Holter, according to the longest episode of pAF in three groups: without pAF detection, episodes of pAF shorter than 5 h, and episodes of pAF longer than 5 h (HpAF). Atrial dysfunction surrogates were evaluated: EKG pattern, Holter record and echocardiography parameters (left atria volume (LAVI), and peak atrial longitudinal and contraction strain (PALS and PACS). The level of N-terminal pro b-type natriuretic peptide (NT-proBNP) was determined. All patients were followed for 2 years to detect pAF and stroke recurrence. From 308 patients, 253 patients with high quality Holter analysis were selected. The distribution was No pAF 78.6% (n = 199), pAF < 5 h 7.9% (n = 20), and HpAF > 5 h 13.4% (n = 34). Age of the patients and combination of PALS and NT-proBNP independently predicted HpAF OR 1.07 (1.00; 1.15) and OR 3.05 (1.08; 8.60) respectively. The validity of PALS and NT-proBNP to detect patients at risk of HpAF was higher than the validity of age (AUC 0.82, sensitivity 78.95%, specificity 63%). Patients with PALS < 25% and NT-proBNP > 283 pg/ml had more detection of pAF during follow-up 35% vs. 5.1% OR 2.33 (1.05-5.13) (p < 0.001). Multimodal assessment of atrial dysfunction with PALS and NT-proBNP improved the prediction of pAF episodes with high embolic risk in patients with cryptogenic stroke.

Risk of Atrial Fibrillation, Ischemic Stroke and Cognitive Impairment: Study of a Population Cohort ≥65 Years of Age

PURPOSE

To evaluate a model for calculating the risk of AF and its relationship with the incidence of ischemic stroke and prevalence of cognitive decline.

MATERIALS AND METHODS

It was a multicenter, observational, retrospective, community-based study of a cohort of general population ≥6ct 35 years, between 01/01/2016 and 31/12/2018. Setting: Primary Care. Participants: 46,706 people ≥65 years with an active medical history in any of the primary care teams of the territory, information accessible through shared history and without previous known AF. Interventions: The model to stratify the risk of AF (PI) has been previously published and included the variables sex, age, mean heart rate, mean weight and CHA2DS2VASc score. Main measurements: For each risk group, the incidence density/1000 person/years of AF and stroke, number of cases required to detect a new AF, the prevalence of cognitive decline, Kendall correlation, and ROC curve were calculated.

RESULTS

The prognostic index was obtained in 37,731 cases (80.8%) from lowest (Q1) to highest risk (Q4). A total of 1244 new AFs and 234 stroke episodes were diagnosed. Q3-4 included 53.8% of all AF and 69.5% of strokes in men; 84.2% of all AF and 85.4% of strokes in women; and 77.4% of cases of cognitive impairment. There was a significant linear correlation between the risk-AF score and the Rankin score (p < 0.001), the Pfeiffer score (p < 0.001), but not NIHSS score (p 0.150). The overall NNS was 1/19.

CONCLUSION

Risk stratification allows identifying high-risk individuals in whom to intervene on modifiable risk factors, prioritizing the diagnosis of AF and investigating cognitive status.

Patient-reported feasibility of chest and thumb ECG after cryptogenic stroke in Sweden: an observational study

OBJECTIVES

The aim of this study was to assess the feasibility, based on a questionnaire, of the chest and thumb ECG system Coala Heart Monitor in patients who recently had a stroke.

DESIGN

Observational study.

SETTING

Two stroke units, Region Gävleborg, Sweden.

PARTICIPANTS AND INTERVENTIONS

This study, Transient ECG Assessment in Stroke Evaluation (TEASE), included patients who had a stroke between 2017 and 2019. Patients eligible for anticoagulation in the presence of atrial fibrillation were scheduled for 28 days monitoring.

PRIMARY AND SECONDARY OUTCOME MEASURES

The questionnaire regarding feasibility of monitoring included seven questions, using a 100 mm Visual Analogue Scale which covered overall satisfaction, technical feasibility, remember to monitor, physical application, feeling of security, help from others and recommendation to others. A lower score indicated better outcome.

RESULTS

The prespecified number of 100 patients underwent the monitoring and 83 out of the 97 alive patients returned the questionnaire (response rate 85.6%). The median age was 69.5 years, mean CHA₂DS₂-VASc score was 4.4±1.3 points and 59.0% were men (n=49). The median time from index stroke to start of monitoring was 7.0 days. Patients performed on average 90.1%±15.0% of scheduled ECG-transmissions. In all seven questions, the median score ranged from 4 to 8. The vast majority reported acceptable outcomes, that is, the 95th percentile ranged from 30 to 54. There was no significant difference between men and women with regard to any of the seven questions (p values ranging from 0.117 to 0.849). Two of the seven outcome scores correlated significantly to patient age (Spearman's r=-0.238 and r=-0.308, and p values 0.031 and 0.005 for 'overall satisfaction' and 'remember to monitor', respectively).

CONCLUSION

In stroke survivors, chest and thumb ECG two times per day over a period of 4 weeks is feasible from a patient's perspective. The Coala Heart Monitor provides a valuable and convenient tool for monitoring after stroke.

TRIAL REGISTRATION NUMBER

NCT03301662.

P Wave Dispersion and Silent Atrial Fibrillation in Cryptogenic Stroke: The Pathogenic Role of Inflammation

BACKGROUND

Cryptogenic stroke (CS) represents 25% of ischemic strokes. Especially after CS, the detection of atrial fibrillation (AF) is important because it provides clues to the mechanism of stroke. However, the relationship between AF and stroke appears more complex than a simple cause-effect mechanism, suggesting that the association between AF and stroke may be due to other systemic and atrial factors including systemic inflammation that may lead to atrial remodeling and subsequent atrial cardiopathy.

OBJECTIVE

The aim of this study was to evaluate the relationship among different electrocardiographic parameters, inflammatory markers and in-hospital AF occurrence after acute CS.

METHODS

222 patients with CS underwent 12-lead resting ECG at admission and 7-day in-hospital ECG monitoring. The following indices were evaluated: P-wave dispersion (PWD), P-wave index, P-wave axis, atrial size and high-sensitivity-C reactive protein (CRP).

RESULTS

AF was detected in 44 patients. AF-group had significantly higher PWD, P-wave index, PR interval, CRP and greater frequency of abnormal P-wave axis in comparison with no-AF group. There was a significant correlation between CRP and PWD (r=0.28). By using the mediation analysis, performed according to the "bootstrapping" method, we found that PWD is a significant mediator variable of the relationship between CRP and AF occurrence, accounting for 40% of the association.

CONCLUSIONS

In cryptogenic stroke, high PWD is partly due to systemic inflammation that increases AF risk possibly via atrial electric remodeling. These findings could also suggest inflammation as a possible therapeutic target in order to prevent atrial electrical alterations and finally AF occurrence in CS.

Practice advisory update summary: Patent foramen ovale and secondary stroke prevention: Report of the Guideline Subcommittee of the American Academy of Neurology

OBJECTIVE

To update the 2016 American Academy of Neurology (AAN) practice advisory for patients with stroke and patent foramen ovale (PFO).

METHODS

The guideline panel followed the AAN 2017 guideline development process to systematically review studies published through December 2017 and formulate recommendations.

MAJOR RECOMMENDATIONS

In patients being considered for PFO closure, clinicians should ensure that an appropriately thorough evaluation has been performed to rule out alternative mechanisms of stroke (level B). In patients with a higher risk alternative mechanism of stroke identified, clinicians should not routinely recommend PFO closure (level B). Clinicians should counsel patients that having a PFO is common; that it occurs in about 1 in 4 adults in the general population; that it is difficult to determine with certainty whether their PFO caused their stroke; and that PFO closure probably reduces recurrent stroke risk in select patients (level B). In patients younger than 60 years with a PFO and embolic-appearing infarct and no other mechanism of stroke identified, clinicians may recommend closure following a discussion of potential benefits (absolute recurrent stroke risk reduction of 3.4% at 5 years) and risks (periprocedural complication rate of 3.9% and increased absolute rate of non-periprocedural atrial fibrillation of 0.33% per year) (level C). In patients who opt to receive medical therapy alone without PFO closure, clinicians may recommend an antiplatelet medication such as aspirin or anticoagulation (level C).

Analysis of Relevant Features from Photoplethysmographic Signals for Atrial Fibrillation Classification

Atrial Fibrillation (AF) is the most common cardiac arrhythmia found in clinical practice. It affects an estimated 33.5 million people, representing approximately 0.5% of the world's population. Electrocardiogram (ECG) is the main diagnostic criterion for AF. Recently, photoplethysmography (PPG) has emerged as a simple and portable alternative for AF detection. However, it is not completely clear which are the most important features of the PPG signal to perform this process. The objective of this paper is to determine which are the most relevant features for PPG signal analysis in the detection of AF. This study is divided into two stages: (a) a systematic review carried out following the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) statement in six databases, in order to identify the features of the PPG signal reported in the literature for the detection of AF, and (b) an experimental evaluation of them, using machine learning, in order to determine which have the greatest influence on the process of detecting AF. Forty-four features were found when analyzing the signal in the time, frequency, or time-frequency domains. From those 44 features, 27 were implemented, and through machine learning, it was found that only 11 are relevant in the detection process. An algorithm was developed for the detection of AF based on these 11 features, which obtained an optimal performance in terms of sensitivity (98.43%), specificity (99.52%), and accuracy (98.97%).

Electrocardiographic RR Interval Dynamic Analysis to Identify Acute Stroke Patients at High Risk for Atrial Fibrillation Episodes During Stroke Unit Admission

Patients at short-term risk of paroxysmal atrial fibrillation (PAF) often exhibit increased RR interval variability during sinus rhythm. We studied if RR dynamic analysis, applied in the first hours after stroke unit (SU) admission, identified acute ischemic stroke patients at higher risk for subsequent PAF episodes detected within the SU hospitalization. Acute ischemic stroke patients underwent continuous cardiac monitoring (CCM) using standard bedside monitors immediately after SU admission. The CCM tracks from the first 48 h were analyzed using a telemedicine service (SRA clinic, Apoplex Medical, Germany). Based on the RR dynamics, the stroke risk analysis (SRA) algorithm stratified the risk for PAF as follows: low risk for PAF, high risk for PAF, presence of manifest AF. The subsequent presence/absence of PAF during the whole SU hospitalization was ruled out using all available CCMs, standard ECGs, or 24-h Holter ECGs. Two hundred patients (40% females, mean age 71 ± 16 years) were included. According to the initial SRA analysis, 111 patients (56%) were considered as low risk for PAF, 52 (26%) as high risk while 37 patients (18%) had manifest AF. A low-risk level SRA was associated with a reduced probability for subsequent PAF detection (1/111, 0.9%, 95% CI 0-4.3%) while a high-risk level SRA predicted an increased probability (20/52, 38.5% (95% CI 25-52%). RR dynamic analysis performed in the first hours after ischemic stroke may stratify patients into categories at low or high risk for forthcoming paroxysmal AF episodes detected within the SU hospitalization.

The Heart Rhythm Society/American College of Physicians Atrial Fibrillation Screening and Education Initiative

BACKGROUND

The prevalence of both atrial fibrillation (AF) and stroke is increasing. Stroke is common in AF and can have devastating consequences, especially when AF is unrecognized and anticoagulation is not initiated.

OBJECTIVE

The purpose of this study was to demonstrate the feasibility and yield, both in identifying previously undiagnosed AF and in educating patients and caregivers about AF, of systematic screening events in internal medicine practices using a mobile electrocardiogram device (Kardia/AliveCor iECG).

METHODS

With support from the Heart Rhythm Society and the American College of Physicians, 5 internal medicine practices performed systematic screening and education of patients at higher risk of AF using the Kardia/AliveCor device and a variety of educational materials. Patients screened as "unclassified" or "possible AF" were referred for further evaluation. Patients and providers (physicians, nurses, and allied professionals) assessed the screening process.

RESULTS

A total of 772 patients were screened. The mean age was 65.2 ± 15.4 years, and 281 (28.2%) were 75 years or older. The majority, 521 (67.5%), were female, and 586 (75.7%) had a CHA₂DS₂-VASc score of ≥2. Six hundred seventy patients (86.8%) were screened as "normal," 85 (11.0%) as "unclassified," and 17 (2.2%) as "possible AF." Participants demonstrated a significant knowledge deficit about stroke and AF before the screening events, and the majority felt that their awareness of these issues increased significantly as a result of their participation.

CONCLUSION

This collaborative Heart Rhythm Society/American College of Physicians systematic screening effort using the Kardia/AliveCor device was feasible. Although it resulted in a relatively modest yield of "unclassified" or "possible AF" screens, it had significant educational benefit to participants and caregivers. The diagnostic yield of future programs could be enriched by including more elderly patients and those with more risk factors for AF and stroke. A greater duration or frequency of monitoring would likely increase sensitivity but be more complicated and costlier to administer. Future events should include on-site confirmatory testing with a 12-lead electrocardiogram. Devices such as the Kardia/AliveCor monitor may enhance patient engagement in screening programs.

The application of Lempel-Ziv and Titchener complexity analysis for equine telemetric electrocardiographic recordings

The analysis of equine electrocardiographic (ECG) recordings is complicated by the absence of agreed abnormality classification criteria. We explore the applicability of several complexity analysis methods for characterization of non-linear aspects of electrocardiographic recordings. We here show that complexity estimates provided by Lempel-Ziv ’76, Titchener’s T-complexity and Lempel-Ziv ’78 analysis of ECG recordings of healthy Thoroughbred horses are highly dependent on the duration of analysed ECG fragments and the heart rate. The results provide a methodological basis and a feasible reference point for the complexity analysis of equine telemetric ECG recordings that might be applied to automate detection of equine arrhythmias in equine clinical practice.

Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke

BACKGROUND

Atrial fibrillation (AF) is one of the most prevalent sustained arrhythmias, however, epidemiological data may understate its actual prevalence. Meanwhile, AF is considered to be a major cause of ischemic strokes due to irregular heart-rhythm, coexisting chronic vascular inflammation, and renal insufficiency, and blood stasis. We studied co-expressed genes to understand relationships between atrial fibrillation (AF) and stroke and reveal potential biomarkers and therapeutic targets of AF-related stroke.

METHODS

AF-and stroke-related differentially expressed genes (DEGs) were identified via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE79768 and GSE58294, respectively. Subsequently, extensive target prediction and network analyses methods were used to assess protein-protein interaction (PPI) networks, Gene Ontology (GO) terms and pathway enrichment for DEGs, and co-expressed DEGs coupled with corresponding predicted miRNAs involved in AF and stroke were assessed as well.

RESULTS

We identified 489, 265, 518, and 592 DEGs in left atrial specimens and cardioembolic stroke blood samples at < 3, 5, and 24 h, respectively. LRRK2, CALM1, CXCR4, TLR4, CTNNB1, and CXCR2 may be implicated in AF and the hub-genes of CD19, FGF9, SOX9, GNGT1, and NOG may be associated with stroke. Finally, co-expressed DEGs of ZNF566, PDZK1IP1, ZFHX3, and PITX2 coupled with corresponding predicted miRNAs, especially miR-27a-3p, miR-27b-3p, and miR-494-3p may be significantly associated with AF-related stroke.

CONCLUSION

AF and stroke are related and ZNF566, PDZK1IP1, ZFHX3, and PITX2 genes are significantly associated with novel biomarkers involved in AF-related stroke.

Management of atrial fibrillation-flutter: uptodate guideline paper on the current evidence

The term 'flutter' and 'fibrillation' were first coined to differentiate the differences between fast, regular contractions in Atrial Flutter (AFLUT) with irregular, vermiform contractions of Atrial Fibrillation (AFIB). Management of these two diseases has been a challenge for physicians. Rate control (along with rhythm control) is the first line of management for symptomatic AFIB/AFLUT with Rapid Ventricular Rate (RVR). In some situations, atrial rhythms may not be well controlled by these anti-arrhythmic drugs, making cardioversion to sinus rhythm necessary. Anti-coagulation therapy in both the disease population is essential. Catheter ablation is an effective treatment option in certain patients that have AFIB/AFLUT refractory to medical management. Newer techniques like left atrial appendage (LAA) has been developed and is a highly attractive concept for the future in the management of AFIB/AFLUT. Newer novel drugs targeting specific ion channels are approaching the stages of clinical investigation. However, while advances in technologies have helped elucidate many aspects of these diseases, many mysteries still remain. This literature review serves as one of the guideline papers for current up-to-date management on both AFIB and AFLUT.

Atrial Cardiopathy and Sympatho-Vagal Imbalance in Cryptogenic Stroke: Pathogenic Mechanisms and Effects on Electrocardiographic Markers

Recently, atrial cardiopathy has emerged as possible pathogenic mechanism in cryptogenic stroke and many electrocardiographic (ECG) markers have been proposed in order to detect an altered atrial substrate at an early stage. The autonomic nervous system (ANS) plays a well-known role in determining significant and heterogeneous electrophysiological changes of atrial cardiomyocytes, that promote atrial fibrillation episodes in cardioembolic stroke. Conversely, the role of ANS in atrial cardiopathy and cryptogenic stroke is less known, as well as ANS effects on ECG markers of atrial dysfunction. In this paper, we review the evidence linking ANS dysfunction and atrial cardiopathy as a possible pathogenic factor in cryptogenic stroke.

Management of Acute Retinal Ischemia: Follow the Guidelines!

Acute retinal arterial ischemia, including vascular transient monocular vision loss (TMVL) and branch (BRAO) and central retinal arterial occlusions (CRAO), are ocular and systemic emergencies requiring immediate diagnosis and treatment. Guidelines recommend the combination of urgent brain magnetic resonance imaging with diffusion-weighted imaging, vascular imaging, and clinical assessment to identify TMVL, BRAO, and CRAO patients at highest risk for recurrent stroke, facilitating early preventive treatments to reduce the risk of subsequent stroke and cardiovascular events. Because the risk of stroke is maximum within the first few days after the onset of visual loss, prompt diagnosis and triage are mandatory. Eye care professionals must make a rapid and accurate diagnosis and recognize the need for timely expert intervention by immediately referring patients with acute retinal arterial ischemia to specialized stroke centers without attempting to perform any further testing themselves. The development of local networks prompting collaboration among optometrists, ophthalmologists, and stroke neurologists should facilitate such evaluations, whether in a rapid-access transient ischemic attack clinic, in an emergency department-observation unit, or with hospitalization, depending on local resources.