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Prediction of Post-stroke Motor Recovery
Sponsor: Assistance Publique - Hôpitaux de Paris
Summary
The prediction of motor recovery in the acute phase of stroke is crucial for several clinical reasons: (i) informing the patient and his relatives, (ii) helping to identify the patient's endorsement (return home or rehabilitation) as well as the adaptation of the rehabilitation program to what can be expected from it. To date, an algorithm (decision tree) proposed by C. Stinear's team named PREP2 is the best predictive tool with 75% of patients well classified at 3 months. It predicts the functional recovery of the upper limb after stroke 3 months before the episode by categorizing recovery as "excellent", "good", "limited" as well as "minor" (poor). With two data (SAFE score, age) or three (SAFE score, Motor evoked potential, NIHSS), the prediction is effective three times out of 4. In the study the team is proposing "PREP-UCV", it would like to validate this algorithm as it is with patients in the active file who are victims of stroke. The expected accuracy is 75% or more. As a secondary objective, the team would like to confirm that it find the same algorithm starting from the initial data from PREP 2 (side of the stroke, type of stroke (ischemic and / or hemorrhagic), involvement of the corticospinal tract on MRI, sex at birth ) as well as two other factors which are also very important: cognitive status (dysexecutive / aphasia / neglect), as well as the neutrophils on lymphocytes ratio.
Official title: Prediction of Post-stroke Motor Recovery: the PREP-AVC Algorithm
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
200
Start Date
2021-04-21
Completion Date
2027-10-01
Last Updated
2024-02-05
Healthy Volunteers
No
Conditions
Interventions
Clinical scores such as SAFE score, NIHSS; demographic data such as age and electrophysiological data (such as the absence/presence of Motor evoked potential)
Clinical scores such as SAFE score, NIHSS; demographic data such as age and electrophysiological data (such as the absence/presence of Motor evoked potential) will determine the predictive functional outcome of the upper limb deficit according to the PREP2 algorithm.
Locations (1)
Service des Urgences Cérébro-Vasculaires, Hôpital Pitié Salpêtrière
Paris, France