Prediction of Post-stroke Motor Recovery (PREP-AVC)

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

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.

Study Overview

• Status: Recruiting
• Conditions: Stroke; Upper Limb Motor Deficit
• Intervention / Treatment: 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)

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 Type: Observational
• Enrollment (Estimated): 200

Contacts and Locations

• Study Contact: Name: Charlotte ROSSO, MD; Phone Number: +33 1 42 16 21 03; Email: charlotte.rosso@aphp.fr

Study Locations

• France
  • Paris, France, 75013
    • Recruiting
    • Service des Urgences Cérébro-Vasculaires, Hôpital Pitié Salpêtrière
    • Contact: Charlotte Rosso, MD; Phone Number: +33 01 42 16 21 03/18 54; Email: charlotte.rosso@aphp.fr

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 14 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Stroke patients with upper limb motor deficits

Description

Inclusion criteria:

• age ≥ 18 y-o,
• admitted in the Pitié-Salpêtrière stroke unit,
• stroke with a upper limb motor deficit,
• agree to participate;

Exclusion criteria:

• contra-indication to MRI or TMS,
• patients under legal guardianship ,
• patients without healthcare insurance

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Retrospective

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

follow up of stroke patients with a upper limb deficit; 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); 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.

What is the study measuring?

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

Collaborators and Investigators

• Sponsor: Assistance Publique - Hôpitaux de Paris

Study record dates

Study Major Dates

• Study Start (Actual): April 21, 2021
• Primary Completion (Estimated): October 1, 2027
• Study Completion (Estimated): October 1, 2027

Study Registration Dates

• First Submitted: September 28, 2020
• First Submitted That Met QC Criteria: September 28, 2020
• First Posted (Actual): October 5, 2020

Study Record Updates

• Last Update Posted (Estimated): February 5, 2024
• Last Update Submitted That Met QC Criteria: February 2, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Keywords: stroke; prediction; motor
• Additional Relevant MeSH Terms: Cardiovascular Diseases; Vascular Diseases; Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Stroke
• Other Study ID Numbers: APHP 200863

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No