预测恢复潜力2算法在中国卒中患者上肢功能预后分层中的应用

关键词：脑卒中  预测恢复潜力2算法  预后预测  运动诱发电位

Keywords:stroke  predict recovery potential 2 algorithm  prognostic prediction  motor evoked potential

摘要：

      摘要 目的：探讨预测恢复潜力（PREP）2算法整合至中国脑卒中临床路径后，对急性期上肢功能预后分层的价值。并纵向分析不同亚组功能恢复情况。 方法：采用前瞻性纵向研究设计，选取2023年3月—2024年1月在温州医科大学附属第一医院住院期间发病3天内的脑卒中患者65例，在发病3天内完成SAFE评分，发病10天内（T1）进行TMS-MEP评估，根据评估结果参考PREP2算法进行预后分层。分别在T1、发病后1个月（T2）及3个月（T3）时采用上肢Fugl-Meyer评分量表（UE-FMA）、美国国立卫生研究院卒中量表（NIHSS）及改良Barthel指数（MBI）进行评估。所有患者均接受标准化的综合康复治疗。 结果：PREP2预测分层与基于UE-FMA恢复率定义的3个月结局等级具有一致性（加权Kappa=0.785，P<0.001）。重复测量方差分析显示，UE-FMA和MBI评分的时间主效应及时间×分层的交互效应均显著（P<0.001），表明不同分层组的功能恢复轨迹存在显著差异。多元线性回归显示，控制T1时UE-FMA后，SAFE评分（β=0.407，P<0.001）与MEP状态（β=0.304，P<0.001）仍是T3时UE-FMA评分的独立正向预测因子，年龄（β=﹣0.181，P<0.001）与T1时NIHSS评分（β=﹣0.205，P<0.001）为负向预测因子。 结论：在中国临床现实条件下，于发病早期（10天内）应用PREP2算法，其分层结果能用于有效区分不同恢复趋势的患者亚组。

Abstract:

      Abstract Objective： To investigate the value of the predict recovery potential（PREP）2 algorithm for prognostic stratification in the acute phase of stroke and to longitudinally analyze functional recovery trajectories across different prognostic subgroups in a Chinese stroke population. Method： In this prospective longitudinal study， 65 stroke patients admitted to the First Affiliated Hospital of Wenzhou Medical University within 3 days of onset between March 2023 and January 2024 were enrolled. The Shoulder Abduction and Finger Extension （SAFE） score was assessed within 3 days post-stroke， and transcranial magnetic stimulation-motor evoked potential （TMS-MEP） assessment was performed within 10 days （T1） for prognostic stratification. Prognostic stratification was subsequently conducted using the PREP2 algorithm. Functional assessments， including the upper limb Fugl-Meyer assessment （UE-FMA）， national institutes of health stroke scale （NIHSS）， and modified Barthel index （MBI）， were conducted at T1， 1 month （T2）， and 3 months （T3） post-stroke. All patients received standardized comprehensive rehabilitation therapy. Result： The PREP2-predicted stratification showed agreement with the 3-month outcome levels defined by UE-FMA recovery rate （weighted Kappa=0.785，P<0.001）. Repeated-measures ANOVA revealed significant main effects of time and significant time-by-stratification interaction effects for both UE-FMA and MBI scores （P<0.001）， indicating distinct functional recovery trajectories among the prognostic subgroups. Multiple linear regression identified the SAFE score （β=0.407，P<0.001） and MEP status （β=0.304，P<0.001） as independent positive predictors of UE-FMA scores at T3， whereas age （β=﹣0.181，P<0.001） and NIHSS score at T1（β=﹣0.205，P<0.001） were negative predictors. Conclusion：Under real-world clinical conditions in China， the application of the PREP2 algorithm in the early post-stroke phase（within 10 days）enables effective stratification to distinguish patient subgroups with different recovery trends.