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Updated: Sep 23, 2026

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
Published on: July 14, 2023
Item-level analysis and network analysis of the functional independence measure cognitive items at discharge after
Satoru Amano1, Sora Kurosaki2, Kayoko Takahashi1
1Occupational Therapy Course, Department of Rehabilitation, Kitasato University, Sagamihara, Japan.
Purpose:
This study characterized item-level profiles and inter-item relationships of the five Functional Independence Measure (FIM) cognitive items at discharge after acute stroke, using clinically anchored coding and network analysis.
Methods:
Discharge FIM cognition scores were retrospectively analyzed in 974 consecutive patients. Items were dichotomized into supervision-or-better (scores 5-7) versus requiring assistance beyond supervision (scores 1-4). Attainment rates, item-rest correlations, and conditional response probability curves were described. Original 7-point scores were used for supplementary item-level and dimensionality analyses and ordinal partial-correlation network estimation. Edge-weight accuracy and centrality stability were assessed by bootstrapping, with Pearson-based sensitivity analysis.
Results:
Supervision-or-better attainment ranged from 67.0% to 77.7%, and item-rest correlations ranged from 0.79 to 0.91. Analyses supported a dominant common dimension. The ordinal network showed two major conditional associations: comprehension-expression (r = 0.71) and memory-problem solving (r = 0.55). Comprehension showed the highest strength centrality, with good stability (CS coefficient = 0.677). Stronger edges were estimated more precisely, with a comparable Pearson-based pattern.
Conclusion:
Discharge FIM cognition profiles demonstrated clinically interpretable item-level heterogeneity and a conditional association structure dominated by two edges. These findings provide a discharge-oriented descriptive framework warranting replication and longitudinal validation against external outcomes.