American Heart Association

Monthly Archives: November 2017

Reducing Recurrent Strokes with Secondary Risk-Factor Modification — Reflections from Temporal Trends in a Population-Based Study

Gurmeen Kaur, MBBS
@kaurgurmeen

Bergström L, Irewall AL, Söderström L, Ögren J, Laurell K, Mooe T. One-Year Incidence, Time Trends, and Predictors of Recurrent Ischemic Stroke in Sweden From 1998 to 2010: An Observational Study. Stroke. 2017

The risk of recurrent stroke has been on a decline as per estimates from different countries, including Italy, Taiwan and the “Western world.” Rikstroke is the Swedish Stroke Register where all Swedish hospital admissions because of stroke are recorded. The authors describe an excellent longitudinal study design where patients with ischemic strokes were followed up from 1998 to 2009. From the year 1998, all Swedish hospitals and rehab centers report their admissions to the Rikstroke registry, which had an astounding 85% coverage in the year 2009.

The recurrence of ischemic stroke events was calculated by amalgamating the Rikstroke registry with the Swedish National Inpatient Register (IPR), which contains data about diagnoses and dates of discharge from hospitalizations in Sweden.

Hide and Seek: Using Cardiac MRI to Find a Hidden Clot in ESUS

Kevin S. Attenhofer, MD

Takasugi J, Yamagami H, Noguchi T, Morita Y, Tanaka T, Okuno Y, et al. Detection of Left Ventricular Thrombus by Cardiac Magnetic Resonance in Embolic Stroke of Undetermined Source. Stroke. 2017.

As has been reviewed in this blog many times before, embolic stroke of undetermined source (ESUS) is a novel clinical construct that is a hot topic for emerging diagnostic and therapeutic strategies. While many studies are evaluating methods to increase the detection rate of covert atrial fibrillation in this population, the authors of this paper demonstrate improved detection of left ventricular (LV) thrombi in ESUS patients using cardiac MRI versus TTE.

Currently, echocardiography is the test of choice when evaluating for intra-cardiac thrombus. Transesophageal echocardiography (TEE) is the gold standard technique for detecting left atrial or left atrial appendage thrombi. Transthoracic echocardiography (TTE) is used to evaluate the presence of LV thrombus, patent foramen ovale, depressed ejection fraction, etc. Recently, contrast enhanced cardiac magnetic resonance imaging (CE-CMR) has shown significantly better sensitivity than TTE for the diagnosis of LV thrombus (cardiac studies suggesting sensitivity of TTE was 40%, compared with 88% for CE-CMR) in patients with a history of myocardial infarction (MI) or LV dysfunction (LVEF < 30%).

Author Interview: Ramin Zand, MD, and Vida Abedi, PhD

A conversation with Ramin Zand, MD, Neurology Director of Clinical Stroke Operations, Northeastern Regional Stroke Director, Geisinger Health System, and Associate Professor of Neurology, University of Tennessee Health Science Center, and Vida Abedi, PhD, Research Scientist, Geisinger Health System, and Adjunct Professor, Virginia Tech, about using an artificial neural network to screen for stroke.

Interviewed by José G. Merino, MD, Associate Professor of Neurology, University of Maryland School of Medicine.

They will be discussing the paper “Novel Screening Tool for Stroke Using Artificial Neural Network,” published in the June issue of Stroke.

Dr. Merino: Could you please briefly summarize the key findings and put them in context of what was known before you did the study (i.e. an “elevator pitch” about your research)?

Vida Abedi, PhD

Vida Abedi, PhD

Drs. Zand and Abedi: We have developed ​a new computational method based on artificial intelligence to screen for the stroke in an emergency setting. Previous studies have shown that up to 25% of strokes can be initially misdiagnosed in the emergency department. The failure to recognize stroke in the emergency department is a missed opportunity for intervention. The goal of our study was to test if a supervised learning method could recognize and differentiate stroke from stroke mimics based on the patient demographics, risk factors, and certain clinical elements. Our results showed that in 6 out of the 10 data sets, the precision of our tool for the diagnosis of stroke was >90%. We believe that these methods can serve as a clinical decision support system and assist the emergency providers with early recognition of stroke.

Ramin Zand, MD

Ramin Zand, MD