Inter-individual variability in the capacity for motor recovery after ischemic stroke.
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 diagnostics 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 cortical), 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 congruent with 0.70 x 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.
Prabhakaran
Shyam
S
Neurological Institute, Columbia University, Stroke and Critical Care Division, New York, New York 10032, USA.
Zarahn
Eric
E
Riley
Claire
C
Speizer
Allison
A
Chong
Ji Y
JY
Lazar
Ronald M
RM
Marshall
Randolph S
RS
Krakauer
John W
JW
D017677:Age Distribution; D000368:Aged; D002545:Brain Ischemia / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009069:Movement Disorders / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D015588:Observer Variation; D010291:Paresis / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D011237:Predictive Value of Tests; D020127:Recovery of Function; D015203:Reproducibility of Results; D020521:Stroke / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology