Actigraphic Measurement of the Upper Limbs for the Prediction of Ischemic Stroke Prognosis: An Observational Study

It is often challenging to formulate a reliable prognosis for patients with acute ischemic stroke. The most accepted prognostic factors may not be sufficient to predict the recovery process. In this view, describing the evolution of motor deficits over time via sensors might be useful for strengthen...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-04, Vol.21 (7), p.2479
Main Authors: Reale, Giuseppe, Giovannini, Silvia, Iacovelli, Chiara, Castiglia, Stefano Filippo, Picerno, Pietro, Zauli, Aurelia, Rabuffetti, Marco, Ferrarin, Maurizio, Maccauro, Giulio, Caliandro, Pietro
Format: Article
Language:English
Subjects:
Actigraphy
Asymmetry
Brain Ischemia - diagnosis
cerebrovascular diseases
Clinical medicine
Hirsch index
Human motion
Humans
inertial sensors
Intensive care
Ischemic Stroke
Medical prognosis
Observational studies
Parameter sensitivity
Patients
Prognosis
Sensors
Stroke
Stroke - diagnosis
Symmetry
Upper Extremity
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Summary:It is often challenging to formulate a reliable prognosis for patients with acute ischemic stroke. The most accepted prognostic factors may not be sufficient to predict the recovery process. In this view, describing the evolution of motor deficits over time via sensors might be useful for strengthening the prognostic model. Our aim was to assess whether an actigraphic-based parameter (Asymmetry Rate Index for the 24 h period (AR2_24 h)) obtained in the acute stroke phase could be a predictor of a 90 d prognosis. In this observational study, we recorded and analyzed the 24 h upper limb movement asymmetry of 20 consecutive patients with acute ischemic stroke during their stay in a stroke unit. We recorded the motor activity of both arms using two programmable actigraphic systems positioned on patients' wrists. We clinically evaluated the stroke patients by NIHSS in the acute phase and then assessed them across 90 days using the modified Rankin Scale (mRS). We found that the AR2_24 h parameter positively correlates with the 90 d mRS (r = 0.69, < 0.001). Moreover, we found that an AR2_24 h > 32% predicts a poorer outcome (90 d mRS > 2), with sensitivity = 100% and specificity = 89%. Sensor-based parameters might provide useful information for predicting ischemic stroke prognosis in the acute phase.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21072479