Literature DB >> 24728337

A multimodal approach to understanding motor impairment and disability after stroke.

Erin Burke1, Lucy Dodakian, Jill See, Alison McKenzie, Jeff D Riley, Vu Le, Steven C Cramer.   

Abstract

Many different measures have been found to be related to behavioral outcome after stroke. Preclinical studies emphasize the importance of brain injury and neural function. However, the measures most important to human outcomes remain uncertain, in part because studies often examine one measure at a time or enroll only mildly impaired patients. The current study addressed this by performing multimodal evaluation in a heterogeneous population. Patients (n = 36) with stable arm paresis 3-6 months post-stroke were assessed across 6 categories of measures related to stroke outcome: demographics/medical history, cognitive/mood status, genetics, neurophysiology, brain injury, and cortical function. Multivariate modeling identified measures independently related to an impairment-based outcome (arm Fugl-Meyer motor score). Analyses were repeated (1) identifying measures related to disability (modified Rankin Scale score), describing independence in daily functions and (2) using only patients with mild deficits. Across patients, greater impairment was related to measures of injury (reduced corticospinal tract integrity) and neurophysiology (absence of motor evoked potential). In contrast, (1) greater disability was related to greater injury and poorer cognitive status (MMSE score) and (2) among patients with mild deficits, greater impairment was related to cortical function (greater contralesional motor/premotor cortex activation). Impairment after stroke is most related to injury and neurophysiology, consistent with preclinical studies. These relationships vary according to the patient subgroup or the behavioral endpoint studied. One potential implication of these results is that choice of biomarker or stratifying variable in a clinical stroke study might vary according to patient characteristics.

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Year:  2014        PMID: 24728337     DOI: 10.1007/s00415-014-7341-8

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   4.849


  57 in total

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Authors:  Petr Hlustík; Michal Mayer
Journal:  Cogn Behav Neurol       Date:  2006-03       Impact factor: 1.600

3.  Cerebral vascular accidents in patients over the age of 60. II. Prognosis.

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Journal:  Scott Med J       Date:  1957-05       Impact factor: 0.729

4.  The case for modality-specific outcome measures in clinical trials of stroke recovery-promoting agents.

Authors:  Steven C Cramer; Walter J Koroshetz; Seth P Finklestein
Journal:  Stroke       Date:  2007-03-01       Impact factor: 7.914

5.  Genetic variant of BDNF (Val66Met) polymorphism attenuates stroke-induced angiogenic responses by enhancing anti-angiogenic mediator CD36 expression.

Authors:  Luye Qin; Eunhee Kim; Rajiv Ratan; Francis S Lee; Sunghee Cho
Journal:  J Neurosci       Date:  2011-01-12       Impact factor: 6.167

6.  Functional potential in chronic stroke patients depends on corticospinal tract integrity.

Authors:  Cathy M Stinear; P Alan Barber; Peter R Smale; James P Coxon; Melanie K Fleming; Winston D Byblow
Journal:  Brain       Date:  2007-01       Impact factor: 13.501

7.  Correlation between genetic polymorphisms and stroke recovery: analysis of the GAIN Americas and GAIN International Studies.

Authors:  S C Cramer; V Procaccio
Journal:  Eur J Neurol       Date:  2012-01-04       Impact factor: 6.089

8.  Post-stroke depression: relationships to functional impairment, coping strategies, and rehabilitation outcome.

Authors:  D Sinyor; P Amato; D G Kaloupek; R Becker; M Goldenberg; H Coopersmith
Journal:  Stroke       Date:  1986 Nov-Dec       Impact factor: 7.914

9.  Microstructural status of ipsilesional and contralesional corticospinal tract correlates with motor skill in chronic stroke patients.

Authors:  Judith D Schaechter; Zachary P Fricker; Katherine L Perdue; Karl G Helmer; Mark G Vangel; Douglas N Greve; Nikos Makris
Journal:  Hum Brain Mapp       Date:  2009-11       Impact factor: 5.038

10.  Impact of diabetes and prediabetes on the short-term prognosis in patients with acute ischemic stroke.

Authors:  Ryota Tanaka; Yuji Ueno; Nobukazu Miyamoto; Kazuo Yamashiro; Yasutaka Tanaka; Hideki Shimura; Nobutaka Hattori; Takao Urabe
Journal:  J Neurol Sci       Date:  2013-06-28       Impact factor: 3.181

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  27 in total

1.  Electroencephalography Measures are Useful for Identifying Large Acute Ischemic Stroke in the Emergency Department.

Authors:  Lauren Shreve; Arshdeep Kaur; Christopher Vo; Jennifer Wu; Jessica M Cassidy; Andrew Nguyen; Robert J Zhou; Thuong B Tran; Derek Z Yang; Ariana I Medizade; Bharath Chakravarthy; Wirachin Hoonpongsimanont; Erik Barton; Wengui Yu; Ramesh Srinivasan; Steven C Cramer
Journal:  J Stroke Cerebrovasc Dis       Date:  2019-06-04       Impact factor: 2.136

2.  Validity of Robot-Based Assessments of Upper Extremity Function.

Authors:  Alison McKenzie; Lucy Dodakian; Jill See; Vu Le; Erin Burke Quinlan; Claire Bridgford; Daniel Head; Vy L Han; Steven C Cramer
Journal:  Arch Phys Med Rehabil       Date:  2017-05-05       Impact factor: 3.966

3.  Dorsal premotor activity and connectivity relate to action selection performance after stroke.

Authors:  Jill Campbell Stewart; Pritha Dewanjee; Umar Shariff; Steven C Cramer
Journal:  Hum Brain Mapp       Date:  2016-02-15       Impact factor: 5.038

4.  Neuroimaging Identifies Patients Most Likely to Respond to a Restorative Stroke Therapy.

Authors:  Jessica M Cassidy; George Tran; Erin B Quinlan; Steven C Cramer
Journal:  Stroke       Date:  2018-01-10       Impact factor: 7.914

5.  Connectivity measures are robust biomarkers of cortical function and plasticity after stroke.

Authors:  Jennifer Wu; Erin Burke Quinlan; Lucy Dodakian; Alison McKenzie; Nikhita Kathuria; Robert J Zhou; Renee Augsburger; Jill See; Vu H Le; Ramesh Srinivasan; Steven C Cramer
Journal:  Brain       Date:  2015-06-11       Impact factor: 13.501

6.  Neural function, injury, and stroke subtype predict treatment gains after stroke.

Authors:  Erin Burke Quinlan; Lucy Dodakian; Jill See; Alison McKenzie; Vu Le; Mike Wojnowicz; Babak Shahbaba; Steven C Cramer
Journal:  Ann Neurol       Date:  2014-12-04       Impact factor: 10.422

7.  Neural Correlates of Passive Position Finger Sense After Stroke.

Authors:  Morgan L Ingemanson; Justin R Rowe; Vicky Chan; Jeff Riley; Eric T Wolbrecht; David J Reinkensmeyer; Steven C Cramer
Journal:  Neurorehabil Neural Repair       Date:  2019-07-18       Impact factor: 3.919

8.  Low-Frequency Oscillations Are a Biomarker of Injury and Recovery After Stroke.

Authors:  Jessica M Cassidy; Anirudh Wodeyar; Jennifer Wu; Kiranjot Kaur; Ashley K Masuda; Ramesh Srinivasan; Steven C Cramer
Journal:  Stroke       Date:  2020-04-17       Impact factor: 7.914

9.  Increased Brain Sensorimotor Network Activation after Incomplete Spinal Cord Injury.

Authors:  Kelli G Sharp; Robert Gramer; Stephen J Page; Steven C Cramer
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10.  Finger strength, individuation, and their interaction: Relationship to hand function and corticospinal tract injury after stroke.

Authors:  Eric T Wolbrecht; Justin B Rowe; Vicky Chan; Morgan L Ingemanson; Steven C Cramer; David J Reinkensmeyer
Journal:  Clin Neurophysiol       Date:  2018-02-03       Impact factor: 3.708

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