Article

There is inherent heterogeneity within individuals suffering from
cervical spinal cord injury (SCI), and early prediction of upper limb function
and self-care is challenging. As a result, considerable uncertainty exists
regarding the prediction of functional outcome following cervical SCI within 1
year of injury. OBJECTIVE: To evaluate the value of Graded Redefined Assessment
of Strength, Sensibility, and Prehension (GRASSP) in predicting upper limb
function and self-care outcomes in individuals with cervical SCI. METHOD: A
prospective longitudinal multicenter study was performed. Data from the GRASSP,
the Spinal Cord Independence Measure (SCIM III), and the American Spinal Injury
Association (ASIA) Impairment Scale were recorded at 1, 6, and 12 months after
cervical SCI. For prediction of functional outcome at 6 and 12 months, a logistic
regression model, receiver operating characteristics (ROC), and unbiased
recursive partitioning conditional inference tree (URP-CTREE) were used with 8
different predictor variables. RESULTS: Logistic regression analysis, ROC
analysis, and URP-CTREE all revealed that the strength subtest within GRASSP is
the strongest predictor for upper limb function and self-care outcomes. URP-CTREE
provides useful information on the distribution of different outcomes in acute
cervical SCI and can be used to predict cohorts with homogeneous outcomes.
CONCLUSION: The GRASSP at 1 month can accurately predict upper limb function and
self-care outcomes even in a heterogeneous group of individuals across a wide
spectrum of neurological recovery. The application of URP-CTREE can reveal the
distribution of outcome categories and, based on this, inform trial protocols
with respect to outcomes analysis and patient stratification.
CI - (c) The Author(s) 2014.

Langue : ANGLAIS