Neural Function, Injury, and Stroke Subtype Predict Treatment Gains After Stroke

作者: Erin Burke Quinlan , Lucy Dodakian , Jill See , Alison McKenzie , Vu Le

DOI: 10.1002/ANA.24309

关键词:

摘要: Objective This 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, injury, and clinical status each influence treatment gains; therefore, current hypothesized a multivariate approach incorporating these 3 measures would have greatest predictive value. Methods Patients 6 months poststroke underwent battery of assessments before receiving weeks standardized upper extremity robotic therapy. Candidate predictors included brain injury (including gray white matter), function (cortical cortical connectivity), (demographics/medical history, cognitive/mood, impairment). Results Among all 29 patients, gains identified (smaller corticospinal tract [CST] injury), (greater ipsilesional motor cortex [M1] activation), connectivity interhemispheric M1–M1 connectivity). Multivariate modeling found best prediction achieved using both CST (r2 = 0.44, p = 0.002), result confirmed Lasso regression. A threshold defined whereby no subject >63% clinically significant gains. Results differed according stroke subtype; patients lacunar were predicted by measure intrahemispheric connectivity. Interpretation Response therapy after is model includes function. Neuroimaging may an ascendant role decision making for rehabilitation, which remains largely reliant on behavioral assessments. across subtypes, suggesting utility lesion-specific strategies. ANN NEUROL 2015;77:132–145

参考文章(101)
Robert Tibshirani, Trevor Hastie, Jerome H. Friedman, The Elements of Statistical Learning ,(2001)
Steven C. Cramer, Issues in clinical trial methodology for brain repair after stroke Brain Repair After Stroke. pp. 173- 182 ,(2010) , 10.1017/CBO9780511777547.017
Jeffrey A. Kleim, Theresa A. Jones, Principles of Experience-Dependent Neural Plasticity: Implications for Rehabilitation After Brain Damage Journal of Speech Language and Hearing Research. ,vol. 51, ,(2008) , 10.1044/1092-4388(2008/018)
Hirofumi Nakayama, Henrik Stig Jørgensen, Hans Otto Raaschou, Tom Skyhøj Olsen, Recovery of upper extremity function in stroke patients: The Copenhagen stroke study Archives of Physical Medicine and Rehabilitation. ,vol. 75, pp. 394- 398 ,(1994) , 10.1016/0003-9993(94)90161-9
Beth Han, William E. Haley, Family caregiving for patients with stroke. Review and analysis Stroke. ,vol. 30, pp. 1478- 1485 ,(1999) , 10.1161/01.STR.30.7.1478
Sharon K. Ostwald, Paul R. Swank, Myrna M. Khan, Predictors of Functional Independence and Stress Level of Stroke Survivors at Discharge From Inpatient Rehabilitation The Journal of Cardiovascular Nursing. ,vol. 23, pp. 371- 377 ,(2008) , 10.1097/01.JCN.0000317435.29339.5D
Jerzy Krupinski, Mark Slevin, Emerging molecular targets for brain repair after stroke. Stroke Research and Treatment. ,vol. 2013, pp. 473416- 473416 ,(2013) , 10.1155/2013/473416
Anna Bacon Moore, Mark W. Bondi, David P. Salmon, Claire Murphy, Eyeblink classical conditioning to auditory and olfactory stimuli : Performance among older adults with and without the apolipoprotein E ε4 allele Neuropsychology (journal). ,vol. 19, pp. 437- 445 ,(2005) , 10.1037/0894-4105.19.4.437
Christian Grefkes, Dennis A. Nowak, Ling E. Wang, Manuel Dafotakis, Simon B. Eickhoff, Gereon R. Fink, Modulating cortical connectivity in stroke patients by rTMS assessed with fMRI and dynamic causal modeling NeuroImage. ,vol. 50, pp. 233- 242 ,(2010) , 10.1016/J.NEUROIMAGE.2009.12.029