Algorithms and Scales for The Prehospital Diagnosis of Acute Cerebrovascular Accident
Abstract
The article presents an analysis of current approaches to the prehospital diagnosis of acute cerebrovascular accident. The main algorithms and clinical scales used for the early recognition of stroke are reviewed, including FAST, CPSS and NIHSS, as well as specialized scales for detecting large vessel occlusion (LAMS, RACE, FAST-ED). Issues of diagnostic accuracy, the limitations of the prehospital stage and the role of telemedicine technologies are discussed. It is shown that the use of standardized algorithms and scales makes it possible to increase diagnostic accuracy, reduce the rate of diagnostic errors and optimize patient routing. It is concluded that an algorithm-based approach plays a key role in improving the effectiveness of medical care for patients with stroke.
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References
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