Prediction of Post-stroke Motor Recovery

Recruiting

• Conditions: Upper Limb Motor Deficit; Stroke
• Interventions: 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)

• Registration Number: NCT04574037
• Lead Sponsor: Assistance Publique - Hôpitaux de Paris

Brief 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.

Detailed Description

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.

Study Timeline

• Study First Submitted: 2020-09-28
• Study First Submitted QC: 2020-09-28
• Study First Posted: 2020-10-05
• Study Start: 2021-04-21
• Status Verified: 2024-02
• Last Update Submitted: 2024-02-02
• Last Update Posted: 2024-02-05
• Primary Completion: 2027-10-01
• Study Completion: 2027-10-01

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 200

Inclusion Criteria

Not provided

Exclusion Criteria

Not provided

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
follow up 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)	Usual follow up of stroke patients with a upper limb deficit

Primary Outcome Measures

Name	Time	Method
Accuracy of classification with the PREP2 decision tree	6 months	Proportion of patients well classified in their group of recovery

Trial Locations

Locations (1)

Service des Urgences Cérébro-Vasculaires, Hôpital Pitié Salpêtrière; 🇫🇷 Paris, France