Assessment Tool Helps Predict Risk of Early Recurrent Stroke

MedicalResearch.com Interview with:

Hakan Ay MD, FAHA Associate Professor of Neurology and Radiology Stroke Service, Department of Neurology

Dr. Hakan Ay

Hakan Ay MD, FAHA
Associate Professor of Neurology and Radiology
Stroke Service, Department of Neurology
Director of Stroke Research,
A.A. Martinos Center, Department of Radiology
Massachusetts General Hospital
Harvard Medical School
Boston MA, USA

Medical Research: What is the background for this study? What are the main findings?

Dr. Ay: Recurrent stroke is an important public health problem. One quarter of all strokes are recurrent strokes. Approximately one out of every 10 patients with stroke develops a second stroke within the next 2 years. The most critical period for recurrence after stroke is the first 90 days; approximately half of recurrent strokes that occur within 2 years occur within the first 90 days. The RRE tool was developed at the Massachusetts General Hospital in 2010 to assess the 90-day risk of recurrent stroke. The RRE was subsequently tested in a separate cohort of patients with transient stroke symptoms (mini strokes) admitted to the Massachusetts General Hospital in 2011. The current study expands upon prior two studies by showing that the RRE tool provides reliable risk estimates when tested in cohorts of patients recruited from different academic centers in various parts of the world. The study reports that the RRE can stratify approximately one-half of patients with stroke either at high-risk or at low-risk with a reasonable accuracy.

Medical Research: What should clinicians and patients take away from your report?

Dr. Ay: An interesting observation in this study is that conventional risk factors for stroke in the long-term such as smoking, diabetes, high cholesterol, and hypertension do not appear to confer an important risk in the short-term. The most important predictor of stroke risk in the short-term appears to be the underlying mechanism of stroke such as embolism from the heart or critical stenosis of a proximal artery. Currently, the RRE is the only tool for predicting short-term risk of recurrent stroke.

The RRE exploits the etiology information along with other predictive information, mainly coming from the patient’s brain scans, to differentiate the etiology that has potential to cause another stroke (unstable etiology) in the short-term from an etiology that does not (stable etiology). The concept of unstable etiology that the RRE advocates is important because those who have a second stroke are more likely to die or suffer from severe disability. The RRE can be used to develop stroke management algorithms that are based on individual patient characteristics. For instance, admission to specialized stroke centers for prompt etiologic investigation and emergent preventive treatment may offer greater benefit in high-risk patients whereas elective evaluation and management may be justified in low-risk patients, particularly in settings where resources are limited. There may be some research implications as well. The risk and cost of preventive treatments that provide a modest reduction in stroke risk may not outweigh the benefit in low risk populations whereas treatments with a small effect size could provide clinically meaningful benefit in high-risk populations. Randomization based on baseline recurrence risk obtained from the RRE can reduce effective sample size in future prevention trials and thus help facilitate discovery of new targeted treatments.

Medical Research: What recommendations do you have for future research as a result of this study?

Dr. Ay: Although the RRE exhibits good discrimination, its predictive value as defined by the area under the ROC curve is 0.76 (1.0 indication a perfect prediction and 0.5 indicating predictions no better than chance alone). In addition, the positive predictive value for the high risk subset is only 16%. Although this risk value is still approximately 4 times greater than the population average and 16 times higher than the average risk in the low-risk subset, there is clearly much room for improvement. Future prognostic tools that incorporate new markers of stability of underlying stroke etiologies could provide risk predictions with higher accuracy.  

Medical Research: Is there anything else you would like to add?

Dr. Ay: A major advantage of the RRE, in my opinion, is that it is simple; it can be employed by physicians based on information typically available after initial line of investigations in the emergency department. The RRE does not require any sophisticated input from neuro-images that requires post-processing. 

Citation:

Arsava E, Kim G, Oliveira-Filho J, et al. Prediction of Early Recurrence After Acute Ischemic Stroke. JAMA Neurol. Published online February 29, 2016. doi:10.1001/jamaneurol.2015.4949.

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Hakan Ay MD, FAHA (2016). Assessment Tool Helps Predict Risk of Early Recurrent Stroke 

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