Journal
ANNALS OF NEUROLOGY
Volume 77, Issue 1, Pages 132-145Publisher
WILEY
DOI: 10.1002/ana.24309
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Funding
- NIH National Institute of Neurological Disorders and Stroke [R01 NS059909]
- NIH National Center for Research Resources [UL1 TR000153]
- NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development [K24 HD074722 01]
- EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [K24HD074722] Funding Source: NIH RePORTER
- NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UL1TR000153] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS059909] Funding Source: NIH RePORTER
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ObjectiveThis study was undertaken to better understand the high variability in response seen when treating human subjects with restorative therapies poststroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains; therefore, the current study hypothesized that a multivariate approach incorporating these 3 measures would have the greatest predictive value. MethodsPatients 3 to 6 months poststroke underwent a battery of assessments before receiving 3 weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment). ResultsAmong all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract [CST] injury), cortical function (greater ipsilesional motor cortex [M1] activation), and cortical connectivity (greater interhemispheric M1-M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1-M1 connectivity (r(2)=0.44, p=0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype; gains in patients with lacunar stroke were best predicted by a measure of intrahemispheric connectivity. InterpretationResponse to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision making for poststroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting the utility of lesion-specific strategies. ANN NEUROL 2015;77:132-145
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