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Updated: Oct 1, 2026

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury
Published on: October 6, 2020
A Bedside Score Predicts One-Year Walking Recovery in AIS C Spinal Cord Injury: A Multisite Cohort Study
Andrew C Smith1, Jeffrey Kepple1, Kenneth A Weber2
1University of Colorado School of Medicine, Department of Physical Medicine and Rehabilitation, Aurora, Colorado.
Background:
Walking recovery after American Spinal Injury Association Impairment Scale (AIS) C spinal cord injury (SCI) remains difficult to predict.
Objectives:
This study aimed to validate the prognostic value of quadriceps strength for future walking and to develop and test a simplified bedside clinical prediction rule (CPR) for walking recovery in AIS C SCI.
Methods:
We conducted a retrospective cohort study using Spinal Cord Injury Model Systems data. Neurological examinations were performed at rehabilitation admission. Predictors included binary indicators of ≥3/5 muscle strength for key myotomes (L2, L3, L4, S1) and age cutoffs (≥50, ≥65 years). Logistic regression coefficients were scaled into an integer-based bedside score with 3 categories: likely walk, likely no walk, and uncertain. Model performance was evaluated using a random 20% holdout test set. A total of 1414 adults initially classified as AIS C were included; 40% achieved walking recovery at 1 year.
Results:
Quadriceps strength ≥3/5 was significantly associated with walking recovery (P < .0001) but demonstrated modest diagnostic accuracy when considered alone. In the CPR training set, 9% were categorized as likely walk and 7% as likely no walk, with accuracy 81%, sensitivity 92%, specificity 72%, positive predictive value 72%, and negative predictive value 92%, with similar performance in the test set. A large proportion of patients remained uncertain.
Conclusion:
A simple bedside score combining lower extremity strength and age offers clinically useful early risk stratification for individuals with AIS C SCI. Prospective validation and refinement are needed to improve classification of indeterminate cases. The CPR is available at: aiscwalkingcpr.org.
