Prediction of Post-stroke Motor Recovery

Study Overview
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Brief Summary
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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 we are proposing PREP-UCV, we would like to validate this algorithm as it is with patients in our active file who are victims of stroke. The expected accuracy is 75% or more. As a secondary objective, we would like to confirm that we 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.

Detailed Description
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Retrospective cohort of stroke patients with a upper limb deficit.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. The accuracy of this prediction will be verified according to the actual state of the patient at 3-6 months. Second, another algorithm will be built taking in account cognitive deficits and biological data to determine if the accuracy is higher. All data will be acquired during the clinical routine work-up.

Official Title
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Prediction of Post-stroke Motor Recovery: the PREP-AVC Algorithm

Conditions
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Stroke Patients With a Upper Limb Motor Deficit

Intervention / Treatment
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* Other: Clinical scores such as SAFE score, NIHSS; demographic data such as age and electrophysiological data (such as the absence/presence of Motor evoked potential)


Participation Criteria
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Eligibility Criteria
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Inclusion criteria: (i) age ≥ 18 y-o, (ii) admitted in the Pitié-Salpêtrière stroke unit, (iii) stroke with a upper limb motor deficit, (iv) agree to participate; Exclusion criteria: (i) contra-indication to MRI or TMS, (ii) patients under legal guardianship , (iii) patients without healthcare insurance

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| follow up of stroke patients with a upper limb deficit<br>Usual follow up of stroke patients with a upper limb deficit | Other: Clinical scores such as SAFE score, NIHSS; demographic data such as age and electrophysiological data (such as the absence/presence of Motor evoked potential)<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Accuracy of classification with the PREP2 decision tree | Proportion of patients well classified in their group of recovery | 6 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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stroke, motor, prediction