Snickars Jenny, Persson Hanna C, Sunnerhagen Katharina S
Department of Clinical Neuroscience and Rehabilitation, Institute of Neuroscience and PhysiologyUniversity of Gothenburg, 41346 Gothenburg, Sweden.
J Rehabil Med. 2017 Mar 6;49(3):216-222. doi: 10.2340/16501977-2205.
To investigate factors within 3 days post-stroke that could predict severe impairment in motor function in the upper extremity at one month post-stroke.
This cross-sectional study included 104 patients with first-ever stroke and impaired motor function in the upper extremity. Initial impairment in motor function, demographic data, type of stroke and stroke risk factors were chosen as possible predictors. Severe impairment in motor function was defined as ≤ 31p according to the Fugl-Meyer Assessment for Upper Extremity (FMA-UE). Logistic regression was used to predict severe impairment in motor function at one month post-stroke.
Three possible prediction models were found, comprising stroke severity combined with grip strength and sex, finger extension or shoulder abduction. Models including grip strength or finger extension gave the most accurate predictions, with overall predictive ability 90.4% (95% confidence interval (95% CI) 0.847-0.961) and sensitivity 92.9% (95% CI 0.851-1.0) and 90.5% (95% CI 0.816-0.979), respectively.
Within 3 days post-stroke, severe impairment in motor function in the upper extremity at one month can be predicted using assessment of stroke severity in combination with grip strength, finger extension or shoulder abduction. This may facilitate early planning of rehabilitation for patients with impaired upper extremity in the stroke unit.
研究卒中后3天内可预测卒中后1个月上肢运动功能严重受损的因素。
这项横断面研究纳入了104例首次发生卒中且上肢运动功能受损的患者。将运动功能的初始损伤、人口统计学数据、卒中类型和卒中危险因素作为可能的预测因素。根据上肢Fugl-Meyer评估量表（FMA-UE），将运动功能严重受损定义为≤31分。采用逻辑回归分析预测卒中后1个月运动功能严重受损情况。
发现了三种可能的预测模型，包括卒中严重程度结合握力、性别、手指伸展或肩关节外展。包含握力或手指伸展的模型预测最为准确，总体预测能力为90.4%（95%置信区间（95%CI）0.847 - 0.961），敏感性分别为92.9%（95%CI 0.8
