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Clinical Algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury


Zoerner, B; Blanckenhorn, Wolf U; Dietz, V; Curt, A (2010). Clinical Algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury. Journal of Neurotrauma, 27(1):241-252.

Abstract

The extent of ambulatory recovery after motor incomplete spinal cord injury (miSCI) differs considerably amongst affected persons. This makes individual outcome prediction difficult and leads to increased within-group variation in clinical trials. The aim of this study on subjects with miSCI was (1) to rank the strongest single predictors and predictor combinations of later walking capacity, (2) to develop a reliable algorithm for clinical prediction, and (3) to identify subgroups with only limited recovery of walking function. Correlation and logistic regression analyses were performed on a dataset of 90 subjects, with tetra- or paraparesis, recruited in a prospective European multicenter study. Eleven measures obtained in the subacute injury period, including clinical examination, tibial somato-sensory evoked potentials (tSSEP) and demographic factors, were related to ambulatory outcome (WISCI II, 6minWT) 6 months after injury. The lower extremity motor score (LEMS) alone and in combination was identified as most predictive for later walking capacity in miSCI. Ambulatory outcome of subjects with tetraparesis was correctly predicted for 92% (WISCI II) or 100% (6minWT) of the cases when LEMS was combined with either tSSEP or the ASIA Impairment Scale, respectively. For individuals with paraparesis, prediction was less distinct mainly due to low prediction rates for individuals with poor walking outcome. A clinical algorithm was generated that allowed for the identification of a subgroup composed of individuals with tetraparesis and poor ambulatory recovery. These data provide evidence that a combination of predictors enables a reliable prediction of walking function and early patient stratification for clinical trials in miSCI.

Abstract

The extent of ambulatory recovery after motor incomplete spinal cord injury (miSCI) differs considerably amongst affected persons. This makes individual outcome prediction difficult and leads to increased within-group variation in clinical trials. The aim of this study on subjects with miSCI was (1) to rank the strongest single predictors and predictor combinations of later walking capacity, (2) to develop a reliable algorithm for clinical prediction, and (3) to identify subgroups with only limited recovery of walking function. Correlation and logistic regression analyses were performed on a dataset of 90 subjects, with tetra- or paraparesis, recruited in a prospective European multicenter study. Eleven measures obtained in the subacute injury period, including clinical examination, tibial somato-sensory evoked potentials (tSSEP) and demographic factors, were related to ambulatory outcome (WISCI II, 6minWT) 6 months after injury. The lower extremity motor score (LEMS) alone and in combination was identified as most predictive for later walking capacity in miSCI. Ambulatory outcome of subjects with tetraparesis was correctly predicted for 92% (WISCI II) or 100% (6minWT) of the cases when LEMS was combined with either tSSEP or the ASIA Impairment Scale, respectively. For individuals with paraparesis, prediction was less distinct mainly due to low prediction rates for individuals with poor walking outcome. A clinical algorithm was generated that allowed for the identification of a subgroup composed of individuals with tetraparesis and poor ambulatory recovery. These data provide evidence that a combination of predictors enables a reliable prediction of walking function and early patient stratification for clinical trials in miSCI.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center
07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
610 Medicine & health
Language:English
Date:January 2010
Deposited On:29 Sep 2009 14:24
Last Modified:17 Feb 2018 16:47
Publisher:Mary Ann Liebert
ISSN:0897-7151
Additional Information:This is a copy of an article published in the Journal of Neurotrauma © 2010 copyright Mary Ann Liebert, Inc.; Journal of Neurotrauma is available online at: http://www.liebertonline.com.
OA Status:Green
Publisher DOI:https://doi.org/10.1089/neu.2009.0901
PubMed ID:19645527

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