Makoto Tokunaga, MD, PhD, Kenichi Tori, RPT, Hiroshi Eguchi, RPT, Youko Kado, RPT,
Yuki Ikejima, RPT, Miyuki Ushijima, RPT, Shinko Miyabe, OTR, Shinya Tsujimoto, RPT,
Emiko Fukuda, OTR
Jpn J Compr Rehabil Sci 8: 21-29, 2017
Objective: The aim of our study was to stratify the
contributing factors in order to increase the prediction
accuracy of the multiple linear regression analysis
with motor FIM gain as the objective variable.
Methods: The subjects for our study were 2,542
stroke patients. In the multiple linear regression
analysis with motor FIM gain as the objective variable,
eight contributing factors were stratified. Prediction
formulas were created and the correlation between the
measured motor FIM gain values and the predicted
values was investigated.
Results: The correlation coefficient was higher with
the stratification of gender (0.509), stroke type (0.512),
number of hospital days (0.516), days from onset to
admission (0.518), modified Rankin Scale before
onset (0.520), age (0.541), cognitive FIM at admission
(0.588) and motor FIM at admission (0.641), than with
the use of one prediction formula (0.507), and it was
0.653 with stratification into four groups with the two
factors of motor FIM and cognitive FIM at admission.
Conclusion: By stratifying the contributing factors,
we were able to increase the prediction accuracy of
motor FIM gain.
Key words: Functional Independence Measure, FIM gain, multiple linear regression analysis, stratification, stroke