The Evolution and Application of Cardiac Monitoring for Occult Atrial Fibrillation in Cryptogenic Stroke and TIA

Emergency medicine updates: Transient ischemic attack

INTRODUCTION

Transient ischemic attack (TIA) is a condition commonly evaluated for in the emergency department (ED). Therefore, it is important for emergency clinicians to be aware of the current evidence regarding the diagnosis and management of this disease.

OBJECTIVE

This paper evaluates key evidence-based updates concerning TIA for the emergency clinician.

DISCUSSION

TIA is a harbinger of ischemic stroke and can result from a variety of pathologic causes. While prior definitions incorporated symptoms resolving within 24 h, modern definitions recommend a tissue-based definition utilizing advanced imaging to evaluate for neurologic injury and the etiology. In the ED, emergent evaluation includes assessing for current signs and symptoms of neurologic dysfunction, appropriate imaging to investigate for minor stroke or stroke risk, and arranging appropriate disposition and follow up to mitigate risk of subsequent ischemic stroke. Imaging should include evaluation of great vessels and intracranial arteries, as well as advanced cerebral imaging to evaluate for minor or subclinical stroke. Non-contrast computed tomography (CT) has limited utility for this situation; it can rule out hemorrhage or a large mass causing symptoms but should not be relied on for any definitive diagnosis. Noninvasive imaging of the cervical vessels can also be used (CT angiography or Doppler ultrasound). Treatment includes antithrombotic medications if there are no contraindications. Dual antiplatelet therapy may reduce the risk of recurrent ischemic events in higher risk patients, while anticoagulation is recommended in patients with a cardioembolic source. A variety of scoring systems or tools are available that seek to predict stroke risk after a TIA. The Canadian TIA risk score appears to have the best diagnostic accuracy. However, these scores should not be used in isolation. Disposition may include admission, management in an ED-based observation unit with rapid diagnostic protocol, or expedited follow-up in a specialty clinic.

CONCLUSIONS

An understanding of literature updates concerning TIA can improve the ED care of patients with TIA.

An Arrhythmia classification approach via deep learning using single-lead ECG without QRS wave detection

Arrhythmia, a frequently encountered and life-threatening cardiac disorder, can manifest as a transient or isolated event. Traditional automatic arrhythmia detection methods have predominantly relied on QRS-wave signal detection. Contemporary research has focused on the utilization of wearable devices for continuous monitoring of heart rates and rhythms through single-lead electrocardiogram (ECG), which holds the potential to promptly detect arrhythmias. However, in this study, we employed a convolutional neural network (CNN) to classify distinct arrhythmias without QRS wave detection step. The ECG data utilized in this study were sourced from the publicly accessible PhysioNet databases. Taking into account the impact of the duration of ECG signal on accuracy, this study trained one-dimensional CNN models with 5-s and 10-s segments, respectively, and compared their results. In the results, the CNN model exhibited the capability to differentiate between Normal Sinus Rhythm (NSR) and various arrhythmias, including Atrial Fibrillation (AFIB), Atrial Flutter (AFL), Wolff-Parkinson-White syndrome (WPW), Ventricular Fibrillation (VF), Ventricular Tachycardia (VT), Ventricular Flutter (VFL), Mobitz II AV Block (MII), and Sinus Bradycardia (SB). Both 10-s and 5-s ECG segments exhibited comparable results, with an average classification accuracy of 97.31%. It reveals the feasibility of utilizing even shorter 5-s recordings for detecting arrhythmias in everyday scenarios. Detecting arrhythmias with a single lead aligns well with the practicality of wearable devices for daily use, and shorter detection times also align with their clinical utility in emergency situations.

Recent advances in the management of transient ischemic attacks

Significant advances in our understanding of transient ischemic attack (TIA) have taken place since it was first recognized as a major risk factor for stroke during the late 1950's. Recently, numerous studies have consistently shown that patients who have experienced a TIA constitute a heterogeneous population, with multiple causative factors as well as an average 5–10% risk of suffering a stroke during the 30 days that follow the index event. These two attributes have driven the most important changes in the management of TIA patients over the last decade, with particular attention paid to effective stroke risk stratification, efficient and comprehensive diagnostic assessment, and a sound therapeutic approach, destined to reduce the risk of subsequent ischemic stroke. This review is an outline of these changes, including a discussion of their advantages and disadvantages, and references to how new trends are likely to influence the future care of these patients.

[Event recorder in cryptogenic stroke : Accepted and feasible indications]

It was proven in multiple studies that about 30 % of cryptogenic strokes are related to clinically silent atrial fibrillation (AF). There is an opportunity for prolonged ECG monitoring mainly through an implanted event recorder after completion of conventional diagnostic methods in an unidentified stroke source. The Crystal AF study has proven, together with other results, improved AF detection through prolonged monitoring for up to 36 months. An implanted event recorder for 2-3 years is suitable for this particular purpose. In addition, telemonitoring which is available in some recent models offers prompt detection and allows necessary therapies (e.g., oral anticoagulants) to be initiated. The implantation of an event recorder should also be considered in patients with a previous history of neurological symptoms in the context of undetectable sources of stroke or transient ischemic attack (TIA).