Song Simeng, Wang Shiliang, Zeng Shanshan, Wu Wenqing, Wu Lingying, Tang Xukun, Sun Xiongxing, Wu Dahua, Xie Le
Graduate School, Hunan University of Traditional Chinese Medicine, Changsha, China.
Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (Hunan Academy of Chinese Medicine Affiliated Hospital), Changsha, China.
JMIR Res Protoc. 2025 Aug 5;14:e65829. doi: 10.2196/65829.
Poststroke spasticity (PSS) is a frequent sequela in patients who have experienced stroke. This form of paralysis is more prevalent compared to other poststroke sequelae and is among the most challenging and complex symptoms to manage. Surface electromyography (sEMG) can reflect the physiological information of muscles in real time and is highly beneficial in diagnosing neuromuscular diseases in clinical medicine.
This study aimed to investigate the timing of poststroke limb spasms using a nested case-control study combined with sEMG and to identify and predict factors of PSS at an early stage.
This was a nested case-control study. Participants were assessed within 24 hours of the onset of hospitalization using a standardized case report form to evaluate general patient information and clinical data related to cerebral infarction and imaging. Upon inclusion, patients were assessed after 1, 2, 4, 8, and 12 weeks, using the Modified Ashworth Scale (MAS) for spasticity severity, root mean square values from sEMG for limb spasm severity, and the simplified Fugl-Meyer (S-FM) Assessment for limb motor function. Patients who experienced spasticity within 12 weeks were assigned to the spasticity group, whereas those who did not experience spasticity were assigned to the control group. Unmatched case grouping was implemented. Data with normal distribution were analyzed using the t test, while data with nonnormal distribution were analyzed using the rank-sum test; categorical data were analyzed using the chi-square test, rank-sum test, or Fisher exact test. Logistic regression analysis was used to investigate factors affecting treatment outcomes. Data processing, analysis, and visualization were conducted using Statistical Package for the Social Sciences software (version 26.0; IBM Corp).
This study is funded by the Chinese Association of Ethnic Medicine and began participant recruitment and registration in November 2023. The study is currently ongoing, with 66 participants enrolled as of March 2025.
This study selected a diagnostic method combining sEMG and subjective scales to determine PSS, aiming to eliminate diagnostic errors caused by subjective assessments. This study adopted a nested case-control study method, which has minimal information bias, allowing for the inference of causal relationships between exposure and disease.
Chinese Clinical Trial Registry ChiCTR2300077121; https://www.chictr.org.cn/showproj.html?proj=205037.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/65829.
中风后痉挛（PSS）是中风患者常见的后遗症。与其他中风后遗症相比，这种瘫痪形式更为普遍，也是最难管理且最复杂的症状之一。表面肌电图（sEMG）可以实时反映肌肉的生理信息，在临床医学中对诊断神经肌肉疾病非常有益。
本研究旨在采用巢式病例对照研究结合sEMG来调查中风后肢体痉挛的发生时间，并在早期识别和预测PSS的相关因素。
这是一项巢式病例对照研究。参与者在住院发病24小时内使用标准化病例报告表进行评估，以评估患者的一般信息以及与脑梗死和影像学相关的临床数据。纳入研究后，在1、2、4、8和12周对患者进行评估，使用改良Ashworth量表（MAS）评估痉挛严重程度，使用sEMG的均方根值评估肢体痉挛严重程度，使用简化Fugl-Meyer（S-FM）评估法评估肢体运动功能。在12周内出现痉挛的患者被分配到痉挛组，未出现痉挛的患者被分配到对照组。采用非匹配病例分组。正态分布的数据使用t检验进行分析，非正态分布的数据使用秩和检验进行分析；分类数据使用卡方检验、秩和检验或Fisher确切检验进行分析。采用逻辑回归分析来研究影响治疗结果的因素。使用社会科学统计软件包（版本26.0；IBM公司）进行数据处理、分析和可视化。
本研究由中国民族医药协会资助，于2023年11月开始招募和登记参与者。该研究目前正在进行中，截至2025年3月已有66名参与者入组。
本研究选择了结合sEMG和主观量表的诊断方法来确定PSS，旨在消除主观评估导致的诊断误差。本研究采用巢式病例对照研究方法，信息偏倚最小，能够推断暴露与疾病之间的因果关系。
中国临床试验注册中心ChiCTR2300077121；https://www.chictr.org.cn/showproj.html?proj=205037。
国际注册报告识别码（IRRID）：DERR1-10.2196/65829。
