Prediction of Post-stroke Motor Recovery

Официальное название

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

Обзор

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.

Подробное описание

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.

Вмешательства

• Другое 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.

Первичные конечные точки

• Accuracy of classification with the PREP2 decision tree [Срок оценки: 6 months]

Критерии участия

Критерии включения

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

Критерии исключения

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

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Франция · 1 центр

• Service des Urgences Cérébro-Vasculaires, Hôpital Pitié Salpêtrière — Paris

Идентификаторы

NCT: NCT04574037 · APHP 200863

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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