2020 年 11 巻 p. 102-108
Tokunaga M, Sannomiya K. Explanatory variables to use in a multiple regression analysis to predict stroke patients' motor FIM score at discharge from convalescent rehabilitation wards: an investigation of patients with a motor FIM score of less than 40 points at admission. Jpn J Compr Rehabil Sci 2020; 11: 102-108.
Objective: This study aimed to clarify the explanatory variables to use in a multiple regression analysis to predict improvement in the motor Functional Independence Measure (FIM) during the hospitalization of patients with severe stroke in a convalescent rehabilitation ward.
Methods: The subjects of this study were 230 patients with stroke with a motor FIM score of less than 40 points at admission. In total, 17 factors were stratified and those with a significant difference in motor FIM effectiveness between stratified groups were used as the explanatory variables of a stepwise regression analysis, which employed the motor FIM score at discharge as the objective variable.
Results: There were significant differences in motor FIM effectiveness among the 12 factors. The 10 factors selected through a stepwise regression analysis were age, cognitive FIM score at admission, motor FIM score at admission, number of days from onset to admission, modified Rankin Scale before onset, Brunnstrom stage of paralyzed lower limb, body mass index, sitting stability, Japan Coma Scale, and hemispatial neglect.
Conclusion: It is desirable to use these 10 factors as explanatory variables in multiple regression analyses.
