Atrial Fibrillation Monitoring in Cryptogenic Stroke: the Gaps Between Evidence and Practice

An In Silico Analysis Reveals Sustained Upregulation of Neuroprotective Genes in the Post-Stroke Human Brain

Ischemic stroke is a cerebrovascular disease caused by an interruption of blood flow to the brain, thus determining a lack of oxygen and nutrient supply. The ischemic event leads to the activation of several molecular signaling pathways involved in inflammation and the production of reactive oxygen species, causing irreversible neuronal damage. Several studies have focused on the acute phase of ischemic stroke. It is not clear if this traumatic event can influence some of the molecular processes in the affected area even years after the clinical event. In our study, we performed an in silico analysis using freely available raw data with the purpose of evaluating the transcriptomic state of post-mortem brain tissue. The samples were taken from non-fatal ischemic stroke patients, meaning that they suffered an ischemic stroke and lived for a period of about 2 years after the event. These samples were compared with healthy controls. The aim was to evaluate possible recovery processes useful to mitigating neuronal damage and the detrimental consequences of stroke. Our results highlighted differentially expressed genes codifying for proteins along with long non-coding genes with anti-inflammatory and anti-oxidant functions. This suggests that even after an amount of time from the ischemic insult, different neuroprotective mechanisms are activated to ameliorate brain conditions and repair post-stroke neuronal injury.

The value of STAF (Score for the Targeting of Atrial Fibrillation) in Patients with Cryptogenic Embolic Stroke

Introduction

The aim of the present study was to predict paroxysmal atrial fibrillation (PAF) in acute ischemic stroke patients with presumed cryptogenic embolic etiology.

Methods

In this retrospective cohort study, demographics, blood tests, data of neuroimaging studies such as non-contrast computed tomography (NCCT), magnetic resonance imaging (MRI), standard 12-lead electrocardigraphy (ECG), 24-hour Holter ECG, echocardiography was collected. The diagnostic work-up to detect atrial fibrillation (AF) was either medical history of the patient or 12-lead ECG or 24-hour Holter ECG or continuous ECG monitoring. Score for the targeting of atrial fibrillation (STAF) was calculated for all patients. Cryptogenic ischemic stroke (CS) patients with and without documented AF were recorded.

Results

Between July 2014 and December 2015, a total of 133 of the 258 patients with CS were included in this study. Overall, 133 patients were enrolled and AF was detected in 30 (22.6%) patients. In univariate analysis gender (p<0.001), age (p=0.001), smoking habit (p=0.004), aortic and mitral valve insufficiency (p=0.014 and p=0.021), left ventricular systolic dysfunction (p=0.04), and left atrial dilatation (p=0.03) were predictors of AF but multivariate analysis showed that only gender and age were independent predictors of AF in patients with presumed cryptogenic ischemic stroke. According to ROC analysis, area under the curve was 70% and the sensitivity and specificity of STAF score of ≥5 was 86% and 71% respectively.

Conclusion

STAF score predicted with fair accuracy, and has a limited use for the risk of PAF in stroke patients.

Prevalence and risk factors of ischaemic stroke in the young: a regional Australian perspective

BACKGROUND

There is no universally accepted age cut-off for defining young strokes.

AIMS

We aimed to determine, based on the profile of young stroke patients in our regional centre, an appropriate age cut-off for young strokes.

METHODS

A retrospective analysis of all ischaemic stroke patients admitted to our centre from 2015 to 2017. We identified 391 ischaemic stroke patients; 30 patients between the ages of ≤50, 40 between 51-60 inclusive and 321 ≥ 61 years of age. We collected data on demographic profiles, risk factors and stroke classification using the Trial of Org 10 172 in Acute Stroke Treatment criteria.

RESULTS

We found significant differences between the ≤50 and ≥61 age groups for most of the risk factors and similarities between the 51-60 inclusive and ≥ 61 age groups. At least one of the six risk factors assessed in the study was present in 86.7% of the youngest group, 97.5% of the intermediate age group and 97.2% in the oldest group. In terms of the mechanisms of stroke, the youngest and oldest age groups in our study differed in the prevalence of cryptogenic, cardioembolic and other causes of stroke. The middle and older age groups had similar mechanisms of stroke.

CONCLUSIONS

The prevalence of vascular risk factors and mechanisms of stroke likewise differed significantly across age groups. This study suggests that 50 years is an appropriate age cut-off for defining young strokes and reinforces the importance of primary prevention in all age groups.

Cryptogenic Acute Ischemic Stroke: Assessment of the Performance of a New Continuous Long-Term Monitoring System in the Detection of Atrial Fibrillation

Background

Long-term monitoring has been advocated to enhance the detection of atrial fibrillation (AF) in patients with stroke.

Objective

To evaluate the performance of a new ambulatory monitoring system with mobile data transmission (PoIP) compared with 24-hour Holter. We also aimed to evaluate the incidence of arrhythmias in patients with and without stroke or transient ischemic attack.

Methods

Consecutive patients with and without stroke or TIA, without AF, were matched by propensity score. Participants underwent 24-hour Holter and 7-day PoIP monitoring.

Results

We selected 52 of 84 patients (26 with stroke or TIA and 26 controls). Connection and recording times were 156.5 ± 22.5 and 148.8 ± 20.8 hours, with a signal loss of 6,8% and 11,4%, respectively. Connection time was longer in ambulatory (164.3 ± 15.8 h) than in hospitalized patients (148.8 ± 25.6 h) (p = 0.02), while recording time did not differ between them (153.7 ± 16.9 and 143.0 ± 23.3 h). AF episodes were detected in 1 patient with stroke by Holter, and in 7 individuals (1 control and 6 strokes) by PoIP. There was no difference in the incidence of arrhythmias between the groups.

Conclusions

Holter and PoIP performed equally well in the first 24 hours. Data transmission loss (4.5%) occurred by a mismatch between signal transmission (2.5G) and signal reception (3G) protocols in cell phone towers (3G). The incidence of arrhythmias was not different between stroke/TIA and control groups.

Atrial fibrillation and cryptogenic stroke. What is the current evidence? Role of electrocardiographic monitoring

The diagnosis of cryptogenic stroke is made by exclusion. However, current evidence supports the role of atrial fibrillation episodes as a cause of this condition. Prospective data have demonstrated the benefits of long‐term electrocardiographic monitoring to identify atrial fibrillation in association with cryptogenic stroke. This aim of this article was to analyze the contemporary evidence for the possible relationship between atrial fibrillation and cryptogenic stroke and the role of continuous electrocardiographic monitoring to clarify this hypothesis.

The complexity of atrial fibrillation newly diagnosed after ischemic stroke and transient ischemic attack: advances and uncertainties

Purpose of review

Atrial fibrillation is being increasingly diagnosed after ischemic stroke and transient ischemic attack (TIA). Patient characteristics, frequency and duration of paroxysms, and the risk of recurrent ischemic stroke associated with atrial fibrillation detected after stroke and TIA (AFDAS) may differ from atrial fibrillation already known before stroke occurrence. We aim to summarize major recent advances in the field, in the context of prior evidence, and to identify areas of uncertainty to be addressed in future research.

Recent findings

Half of all atrial fibrillations in ischemic stroke and TIA patients are AFDAS, and most of them are asymptomatic. Over 50% of AFDAS paroxysms last less than 30 s. The rapid initiation of cardiac monitoring and its duration are crucial for its timely and effective detection. AFDAS comprises a heterogeneous mix of atrial fibrillation, possibly including cardiogenic and neurogenic types, and a mix of both. Over 25 single markers and at least 10 scores have been proposed as predictors of AFDAS. However, there are considerable inconsistencies across studies. The role of AFDAS burden and its associated risk of stroke recurrence have not yet been investigated.

Summary

AFDAS may differ from atrial fibrillation known before stroke in several clinical dimensions, which are important for optimal patient care strategies. Many questions remain unanswered. Neurogenic and cardiogenic AFDAS need to be characterized, as it may be possible to avoid some neurogenic cases by initiating timely preventive treatments. AFDAS burden may differ in ischemic stroke and TIA patients, with distinctive diagnostic and treatment implications. The prognosis of AFDAS and its risk of recurrent stroke are still unknown; therefore, it is uncertain whether AFDAS patients should be treated with oral anticoagulants.

How and When to Screen for Atrial Fibrillation after Stroke: Insights from Insertable Cardiac Monitoring Devices

The introduction of insertable cardiac monitoring devices has dramatically altered our understanding of the role of intermittent atrial fibrillation in cryptogenic stroke. In this narrative review we discuss the incidence, timing and relationship between atrial fibrillation and cryptogenic stroke, how to select patients for monitoring and the value and limitations of different monitoring strategies. We also discuss the role of empirical anticoagulation, and atrial fibrillation burden as a means of tailoring anticoagulation in patients at high risk of bleeding.