卒中后运动功能结局的逐步回归和潜在剖面分析。
Stepwise Regression and Latent Profile Analyses of Locomotor Outcomes Poststroke.
机构信息
Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, Indianapolis. (T.G.H., C.E.H.).
Rehabilitation Hospital of Indiana, Indianapolis (T.G.H., C.E.H.).
出版信息
Stroke. 2020 Oct;51(10):3074-3082. doi: 10.1161/STROKEAHA.120.031065. Epub 2020 Sep 4.
BACKGROUND AND PURPOSE
Previous data suggest patient demographics and clinical presentation are primary predictors of motor recovery poststroke, with minimal contributions of physical interventions. Other studies indicate consistent associations between the amount and intensity of stepping practice with locomotor outcomes. The goal of this study was to determine the relative contributions of these combined variables to locomotor outcomes poststroke across a range of patient demographics and baseline function.
METHODS
Data were pooled from 3 separate trials evaluating the efficacy of high-intensity training, low-intensity training, and conventional interventions. Demographics, clinical characteristics, and training activities from 144 participants >1-month poststroke were included in stepwise regression analyses to determine their relative contributions to locomotor outcomes. Subsequent latent profile analyses evaluated differences in classes of participants based on their responses to interventions.
RESULTS
Stepwise regressions indicate primary contributions of stepping activity on locomotor outcomes, with additional influences of age, duration poststroke, and baseline function. Latent profile analyses revealed 2 main classes of outcomes, with the largest gains in those who received high-intensity training and achieved the greatest amounts of stepping practice. Regression and latent profile analyses of only high-intensity training participants indicated age, baseline function, and training activities were primary determinants of locomotor gains. Participants with the smallest gains were older (≈60 years), presented with slower gait speeds (<0.40 m/s), and performed 600 to 1000 less steps/session.
CONCLUSIONS
Regression and cluster analyses reveal primary contributions of training interventions on mobility outcomes in patients >1-month poststroke. Age, duration poststroke, and baseline impairments were secondary predictors. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02507466 and NCT01789853.
背景与目的
既往数据表明，患者的人口统计学特征和临床表现是卒中后运动功能恢复的主要预测因素，而物理干预的贡献较小。其他研究表明，踏步行走练习的数量和强度与运动功能结局之间存在一致的关联。本研究的目的是确定这些综合变量在一系列患者人口统计学特征和基线功能下对卒中后运动功能结局的相对贡献。
方法
对 3 项评估高强度训练、低强度训练和常规干预效果的独立试验的数据进行了汇总。纳入了 144 例卒中后>1 个月的患者的人口统计学特征、临床特征和训练活动，进行逐步回归分析，以确定其对运动功能结局的相对贡献。随后的潜在剖面分析评估了基于干预反应的不同类别的参与者之间的差异。
结果
逐步回归表明，踏步行走活动对运动功能结局的贡献最大，年龄、卒中后时间和基线功能也有额外的影响。潜在剖面分析显示存在 2 个主要的结局类别，其中接受高强度训练并实现最大踏步行走练习量的患者获益最大。仅对高强度训练参与者的回归和潜在剖面分析表明，年龄、基线功能和训练活动是运动功能增益的主要决定因素。获益最小的患者年龄较大（约 60 岁），表现为较慢的步行速度（<0.40 m/s），且每次训练的踏步行走量为 600-1000 次。
结论
回归和聚类分析揭示了训练干预对>1 个月的卒中患者移动能力结局的主要贡献。年龄、卒中后时间和基线损伤是次要预测因素。注册：网址：https://www.clinicaltrials.gov。唯一标识符：NCT02507466 和 NCT01789853。
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