Related Experiment Video
Updated: Jul 28, 2025
The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors
Published on: May 2, 2021
Predicting models for arm impairment: External validation of the Scandinavian models and identification of new
Alejandro García-Rudolph1,2,3, Ignasi Soriano1,2,3, Helard Becerra4
1Department of Research and Innovation, Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Barcelona, Spain.
Background:
Post-stroke arm impairment at rehabilitation admission as predictor of discharge arm impairment was consistently reported as extremely useful. Several models for acute prediction exist (e.g. the Scandinavian), though lacking external validation and larger time-window admission assessments.
Objectives:
(1) use the 33 Fugl-Meyer Assessment-Upper Extremity (FMA-UE) individual items to predict total FMA-UE score at discharge of patients with ischemic stroke admitted to rehabilitation within 90 days post-injury, (2) use eight individual items (seven from the Scandinavian study plus the top predictor item from objective 1) to predict mild impairment (FMA-UE≥48) at discharge and (3) adjust the top three models from objective 2 with known confounders.
Methods:
This was an observational study including 287 patients (from eight settings) admitted to rehabilitation (2009-2020). We applied regression models to candidate predictors, reporting adjusted R2, odds ratios and ROC-AUC using 10-fold cross-validation.
Results:
We achieved good predictive power for the eight item-level models (AUC: 0.70-0.82) and for the three adjusted models (AUC: 0.85-0.88). We identified finger mass flexion as new item-level top predictor (AUC:0.88) and time to admission (OR = 0.9(0.9;1.0)) as only common significant confounder.
Conclusion:
Scandinavian item-level predictors are valid in a different context, finger mass flexion outperformed known predictors, days-to-admission predict discharge mild arm impairment.
