ArticleEuropean journal of physical and rehabilitation medicine2025
Simplified assessment of upper limb dysfunction after stroke: decision tree analysis based on the International Classification of Functioning, Disability and Health.
Article in European journal of physical and rehabilitation medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe International Classification of Functioning, Disability and Health (ICF) provides a comprehensive framework for evaluating stroke patients across four key domains. However, due to the large number of ICF items and the complexity of its classification system, its practical application is often time-consuming, and requires substantial training for evaluators.
aimTo generate and validate a decision tree model based on ICF items for assessing upper limb dysfunction after stroke.
designA cross-sectional study.
settingRehabilitation department of five hospitals. POPULATION: This study included stroke patients (including ischemic or hemorrhagic; first-ever or recurrent), who were stratified according to disease phase: acute (1-7 days, 1.94%), subacute (8-180 days, 53.02%), and chronic (>180 days, 41.38%). All patients had CT/MRI-confirmed diagnosis, stable vital signs, and upper limb dysfunction.
methodsAll participants completed the 56 items of the comprehensive ICF Core Set for stroke. The decision tree model of ICF items significantly associated with the Fugl-Meyer Upper Extremity Scale (FM-UE) was constructed by using the R package rpart.
resultsA total of 464 participants after stroke were recruited. Ten ICF items that were strongly correlated with the FM-UE and P<0.05, and the items were "d4400," "d4401," "d4402," "d4403," "d4450," "d4451," "d4452," "d4453," "d4454," "d4455". Finally, the decision tree model included: "d4401: grasping," "d4553: turning or twisting the hands or arms" and "d4551: pushing". The statistical significant accuracy of the model confusion matrix in validation was 0.7381 (P=5.008e-13), and the AUC was 0.8406.
conclusionsThis study identified ICF items highly correlated with the FMA-UE and developed a statistically significant decision tree model for the assessing of upper limb dysfunction after stroke. CLINICAL REHABILITATION IMPACT: The decision tree model based on key ICF items, substantially reduces evaluation time. It simplifies upper limb dysfunction assessment, enhances ICF application, and provides a simpler and more efficient assessment tool that represents a valuable addition to the clinical tool for stroke rehabilitation.
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