Derivation and Validation of an Algorithm to Detect Stroke Using Arm Accelerometry Data.

ABSTRACT: Background Early diagnosis is essential for effective stroke therapy. Strokes in hospitalized patients are associated with worse outcomes compared with strokes in the community. We derived and validated an algorithm to identify strokes by monitoring upper limb movements in hospitalized patients. Methods and Results A prospective case-control study in hospitalized patients evaluated bilateral arm accelerometry from patients with acute stroke with lateralized weakness and controls without stroke. We derived a stroke classifier algorithm from 123 controls and 77 acute stroke cases and then validated the performance in a separate cohort of 167 controls and 33 acute strokes, measuring false alarm rates in nonstroke controls and time to detection in stroke cases. Faster detection time was associ

SUBMITTER: Messe SR 

PROVIDER: S-EPMC9973644 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature