Neurorehabilitation and Neural Repair Inter-individual Variability in the Capacity for Motor Recovery after Ischemic Stroke Neurorehabilitation and Neural Repair Additional Services and Information for Inter-individual Variability in the Capacity for Motor Recovery after Ischemic Stroke
Neurorehabilitation and Neural Repair Inter-individual Variability in the Capacity for Motor Recovery after Ischemic Stroke Neurorehabilitation and Neural Repair Additional Services and Information for Inter-individual Variability in the Capacity for Motor Recovery after Ischemic Stroke
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J. Krakauer;S. Prabhakaran;E. Zarahn;C. Riley;Allison E Speizer;J. Chong;R. Lazar;R. Marshall
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作者：
J. Krakauer;S. Prabhakaran;E. Zarahn;C. Riley;Allison E Speizer;J. Chong;R. Lazar;R. Marshall
背景中风后的运动恢复仅能通过临床变量进行适度预测，这意味着在恢复过程中仍存在大量无法解释的、具有生物学意义的变异性。回归诊断可以指示这是否仅仅与高斯误差相关联，或者与多个亚群相关联，这些亚群与临床变量的关系不同。objective.对恢复与临床预测因子的线性模型进行回归诊断。方法.研究了41例缺血性卒中患者。使用上肢Fugl-Meyer运动评分评估损伤。运动恢复定义为卒中后24 - 72小时至3或6个月后上肢Fugl-Meyer运动评分的变化。模型中的临床预测因素为年龄、性别、梗死部位（皮质下vs皮质）、弥散加权成像梗死体积、重新评估时间和急性上肢Fugl-Meyer运动评分。回归诊断包括高斯误差的Kolmogorov-Smirnov检验和使用学生化删除残差的离群值检验。结果在随机样本中，临床变量仅解释了47%的恢复方差。在初始损伤最严重的患者中，有一组回归离群值恢复得非常差。去除离群值后，恢复率的解释方差增加至89%，恢复率与初始损伤呈比例关系（恢复率≥ 0.70 ×初始损伤）。结论.临床变量只能适度预测运动恢复。回归诊断表明，存在一个亚群的离群值与严重的初始减值谁显示很少恢复。当这些离群值被删除，临床变量是很好的预测恢复其余患者，显示出一个紧密的比例关系，以最初的损害。
Background. Motor recovery after stroke is predicted only moderately by clinical variables, implying that there is still a substantial amount of unexplained, biologically meaningful variability in recovery. Regression diagnostics can indicate whether this is associated simply with Gaussian error or instead with multiple subpopulations that vary in their relationships to the clinical variables. Objective. To perform regression diagnos-tics on a linear model for recovery versus clinical predictors. Methods. Forty-one patients with ischemic stroke were studied. Impairment was assessed using the upper extremity Fugl-Meyer Motor Score. Motor recovery was defined as the change in the upper extremity Fugl-Meyer Motor Score from 24 to 72 hours after stroke to 3 or 6 months later. The clinical predictors in the model were age, gender, infarct location (subcortical vs corti-cal), diffusion weighted imaging infarct volume, time to reassessment, and acute upper extremity Fugl-Meyer Motor Score. Regression diagnostics included a Kolmogorov-Smirnov test for Gaussian errors and a test for outliers using Studentized deleted residuals. Results. In the random sample, clinical variables explained only 47% of the variance in recovery. Among the patients with the most severe initial impairment, there was a set of regression outliers who recovered very poorly. With the outliers removed, explained variance in recovery increased to 89%, and recovery was well approximated by a proportional relationship with initial impairment (recovery ≅ 0.70 × initial impairment). Conclusions. Clinical variables only moderately predict motor recovery. Regression diagnostics demonstrated the existence of a subpopulation of outliers with severe initial impairment who show little recovery. When these outliers were removed, clinical variables were good predictors of recovery among the remaining patients, showing a tight proportional relationship to initial impairment.