Department for Neurology & Stroke, University Hospital of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
Hertie Institute for Clinical Brain Research, Ottfried-Müller-Straße 25, 72076, Tübingen, Germany.
BMC Neurol. 2022 Jun 30;22(1):238. doi: 10.1186/s12883-022-02759-2.
Stroke is one of the most frequent diseases, and half of the stroke survivors are left with permanent impairment. Prediction of individual outcome is still difficult. Many but not all patients with stroke improve by approximately 1.7 times the initial impairment, that has been termed proportional recovery rule. The present study aims at identifying factors predicting motor outcome after stroke more accurately than before, and observe associations of rehabilitation treatment with outcome.
The study is designed as a multi-centre prospective clinical observational trial. An extensive primary data set of clinical, neuroimaging, electrophysiological, and laboratory data will be collected within 96 h of stroke onset from patients with relevant upper extremity deficit, as indexed by a Fugl-Meyer-Upper Extremity (FM-UE) score ≤ 50. At least 200 patients will be recruited. Clinical scores will include the FM-UE score (range 0-66, unimpaired function is indicated by a score of 66), Action Research Arm Test, modified Rankin Scale, Barthel Index and Stroke-Specific Quality of Life Scale. Follow-up clinical scores and applied types and amount of rehabilitation treatment will be documented in the rehabilitation hospitals. Final follow-up clinical scoring will be performed 90 days after the stroke event. The primary endpoint is the change in FM-UE defined as 90 days FM-UE minus initial FM-UE, divided by initial FM-UE impairment. Changes in the other clinical scores serve as secondary endpoints. Machine learning methods will be employed to analyze the data and predict primary and secondary endpoints based on the primary data set and the different rehabilitation treatments.
If successful, outcome and relation to rehabilitation treatment in patients with acute motor stroke will be predictable more reliably than currently possible, leading to personalized neurorehabilitation. An important regulatory aspect of this trial is the first-time implementation of systematic patient data transfer between emergency and rehabilitation hospitals, which are divided institutions in Germany.
This study was registered at ClinicalTrials.gov ( NCT04688970 ) on 30 December 2020.
中风是最常见的疾病之一，一半的中风幸存者会留下永久性损伤。个体预后的预测仍然很困难。许多但不是所有中风患者的初始损伤都会改善约 1.7 倍，这被称为比例恢复规律。本研究旨在更准确地识别中风后运动预后的预测因素，并观察康复治疗与预后的关系。
该研究设计为多中心前瞻性临床观察性试验。将从具有相关上肢缺陷的患者（以上肢 Fugl-Meyer 评分（FM-UE）≤50 为指标）中风发作后 96 小时内收集临床、神经影像学、电生理学和实验室数据的广泛原始数据集。将招募至少 200 名患者。临床评分将包括 FM-UE 评分（范围 0-66，功能正常的评分为 66）、动作研究上肢测试、改良 Rankin 量表、巴氏指数和中风特定生活质量量表。康复医院将记录随访临床评分和应用的康复治疗类型和数量。中风事件 90 天后进行最终随访临床评分。主要终点是 FM-UE 的变化，定义为 90 天 FM-UE 减去初始 FM-UE，除以初始 FM-UE 损伤。其他临床评分的变化作为次要终点。将采用机器学习方法分析数据，并根据原始数据集和不同的康复治疗预测主要和次要终点。
如果成功，急性运动性中风患者的预后及其与康复治疗的关系将比目前更可靠地预测，从而实现个性化神经康复。该试验的一个重要监管方面是首次在德国的急诊和康复医院之间实施系统的患者数据传输，这两个医院是分开的机构。
该研究于 2020 年 12 月 30 日在 ClinicalTrials.gov （NCT04688970）注册。
