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Published on: January 15, 2017
Changing Demographics of Stroke Mimics in Present Day Stroke Code Era: Need of a Streamlined Clinical Assessment for
Kaushik Sundar1, Ajay Panwar2, Lomesh Bhirud3
1Department of Neurology, Rabindranath International Institute of Cardiac Sciences, Kolkata, West Bengal, India.
Insights
Stroke mimics are common in rapid response stroke care. Identifying predictors like female gender, consciousness impairment, and dysarthria helps emergency physicians avoid misdiagnosis.
Area of Science:
- Neurology
- Emergency Medicine
Background:
- High incidence of stroke mimics observed in the current stroke code era.
- Intense time pressure in stroke management contributes to potential misdiagnosis.
Purpose of the Study:
- To determine the incidence of stroke mimics.
- To identify clinical predictors for differentiating stroke from mimics.
Main Methods:
- Retrospective analysis of 314 stroke code activations over 6 months (April-September 2019).
- Logistic regression analysis to identify predictors of stroke and mimics.
Main Results:
- 18.5% of stroke codes were mimics; functional disorders and epilepsy were most common.
- Female gender, impaired consciousness, and dysarthria predicted mimics.
- Hemiparesis strongly predicted actual stroke.
Conclusions:
- Streamlined assessment using clinical predictors can reduce misdiagnosis of stroke mimics.
- Emergency physicians can improve diagnostic accuracy in rapid response stroke care.
Abstract:
Background There is an apparently high incidence of stroke mimics in the present-day stroke code era. The reason being is the intense pressure to run with time to achieve the "time is brain"-based goals. Methods The present study was a retrospective analysis of the data collected over a duration of 6 months from April 2019 to September 2019. We observed the incidence of stroke mimics among the patients for whom rapid response stroke code was activated during the study period. We also performed a logistic regression analysis to identify the clinical features which can act as strong predictors of stroke and mimics. Results A total of 314 stroke codes were activated of which 256 (81.5%) were stroke and 58 (18.5%) were the mimics. Functional disorders and epilepsy were the most common mimics (24.1% each). Female gender ( p = 0.04; odds ratio [OR] 2.9[1.0-8.8]), isolated impairment of consciousness ( p < 0.01; OR 4.3[1.5-12.6]), and isolated dysarthria ( p < 0.001) were the strong independent predictors for a stroke mimic. Hemiparesis was the strong independent predictor for a stroke ( p < 0.001; OR 0.0[0.0-0.1]). Conclusion In the present epoch of rapid response stroke management, a streamlined assessment by the emergency physicians based on the above clinical predictors may help in avoiding the misdiagnosis of a mimic as stroke.
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