J Zariffa1,2,3, A Curt4, M C Verrier1,3,5, M G Fehlings6,7, S Kalsi-Ryan5,6. 1. Toronto Rehabilitation Institute-University Health Network, Toronto, Ontario, Canada. 2. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada. 3. Rehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada. 4. Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland. 5. Department of Physical Therapy, University of Toronto, Toronto, Ontario, Canada. 6. Krembil Neuroscience Centre-University Health Network, Toronto, Ontario, Canada. 7. Department of Surgery, University of Toronto, Ontario, Canada.
Abstract
BACKGROUND: Automated sensor-based assessments of upper extremity (UE) function after cervical spinal cord injury (SCI) could provide more detailed tracking of individual recovery profiles than is possible with existing assessments, and optimize the delivery and assessment of new interventions. The design of reliable automated assessments requires identifying the key variables that need to be measured to meaningfully quantify UE function. An unanswered question is to what extent measures of sensorimotor impairment can quantitatively predict performance on functional tasks. OBJECTIVE: The objective was to define the predictive value of impairment measures for concurrent functional task performance in traumatic cervical SCI, as measured by the Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP). SETTING: Retrospective analysis. METHODS: A data set of 138 GRASSP assessments was analyzed. The Strength and Sensation modules were used as measures of impairment, whereas the concurrent Prehension Performance module was used as the surrogate measure of function. Classifiers were trained to predict the scores on each of the six individual tasks in the Prehension Performance module. The six scores were added to obtain a total score. RESULTS: The Spearman's ρ between predicted and actual total Prehension Performance scores was 0.84. Predictions using both the Strength and Sensation scores were not found to be superior to predictions using the Strength scores alone. CONCLUSIONS: Measures of UE motor impairment are highly predictive of functional task performance after cervical SCI. Automated sensor-based assessments of UE motor function after SCI can rely on measuring only impairment and estimating functional performance accordingly.
BACKGROUND: Automated sensor-based assessments of upper extremity (UE) function after cervical spinal cord injury (SCI) could provide more detailed tracking of individual recovery profiles than is possible with existing assessments, and optimize the delivery and assessment of new interventions. The design of reliable automated assessments requires identifying the key variables that need to be measured to meaningfully quantify UE function. An unanswered question is to what extent measures of sensorimotor impairment can quantitatively predict performance on functional tasks. OBJECTIVE: The objective was to define the predictive value of impairment measures for concurrent functional task performance in traumatic cervical SCI, as measured by the Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP). SETTING: Retrospective analysis. METHODS: A data set of 138 GRASSP assessments was analyzed. The Strength and Sensation modules were used as measures of impairment, whereas the concurrent Prehension Performance module was used as the surrogate measure of function. Classifiers were trained to predict the scores on each of the six individual tasks in the Prehension Performance module. The six scores were added to obtain a total score. RESULTS: The Spearman's ρ between predicted and actual total Prehension Performance scores was 0.84. Predictions using both the Strength and Sensation scores were not found to be superior to predictions using the Strength scores alone. CONCLUSIONS: Measures of UE motor impairment are highly predictive of functional task performance after cervical SCI. Automated sensor-based assessments of UE motor function after SCI can rely on measuring only impairment and estimating functional performance accordingly.
Authors: Milos R Popovic; Naaz Kapadia; Vera Zivanovic; Julio C Furlan; B Cathy Craven; Colleen McGillivray Journal: Neurorehabil Neural Repair Date: 2011-02-08 Impact factor: 3.919
Authors: J Zariffa; N Kapadia; J L K Kramer; P Taylor; M Alizadeh-Meghrazi; V Zivanovic; R Willms; A Townson; A Curt; M R Popovic; J D Steeves Journal: Spinal Cord Date: 2011-09-13 Impact factor: 2.772
Authors: Sukhvinder Kalsi-Ryan; Dorcas Beaton; Armin Curt; Susan Duff; Milos R Popovic; Claudia Rudhe; Michael G Fehlings; Mary C Verrier Journal: J Neurotrauma Date: 2011-08-12 Impact factor: 5.269
Authors: Robert G Grossman; Michael G Fehlings; Ralph F Frankowski; Keith D Burau; Diana S L Chow; Charles Tator; Angela Teng; Elizabeth G Toups; James S Harrop; Bizhan Aarabi; Christopher I Shaffrey; Michele M Johnson; Susan J Harkema; Maxwell Boakye; James D Guest; Jefferson R Wilson Journal: J Neurotrauma Date: 2013-10-11 Impact factor: 5.269
Authors: Ana de los Reyes-Guzmán; Iris Dimbwadyo-Terrer; Fernando Trincado-Alonso; Félix Monasterio-Huelin; Diego Torricelli; Angel Gil-Agudo Journal: Clin Biomech (Bristol, Avon) Date: 2014-06-26 Impact factor: 2.063
Authors: Fernando Trincado-Alonso; Iris Dimbwadyo-Terrer; Ana de los Reyes-Guzmán; Patricia López-Monteagudo; Alberto Bernal-Sahún; Ángel Gil-Agudo Journal: Biomed Res Int Date: 2014-04-23 Impact factor: 3.411
Authors: Joo Hwan Jung; Hye Jin Lee; Duk Youn Cho; Jung-Eun Lim; Bum Suk Lee; Seung Hyun Kwon; Hae Young Kim; Su Jeong Lee Journal: Ann Rehabil Med Date: 2019-08-31