Predicting FIM gain in stroke patients by adding median FIM gain stratified by FIM score at hospital admission to the explanatory variables in multiple regression analysis—An analysis of the Japan Rehabilitation Database—

Abstract

Tokunaga M, Mori Y, Ogata Y, Tanaka Y, Uchino K, Maeda Y, Kamiyoshi M. Predicting FIM gain in stroke patients by adding median FIM gain stratified by FIM score at hospital admission to the explanatory variables in multiple regression analysis —An analysis of the Japan Rehabilitation Database—. Jpn J Compr Rehabil Sci 2016; 7: 13-18.Objective: To clarify whether the accuracy of predicting motor Functional Independence Measure (FIM) gain in stroke patients can be improved by calculating median values of motor FIM gain (median mFIM gain) stratified by motor FIM score at hospital admission, then inserting these standard gain values in multiple regression analysis.Methods: The subjects were 2,542 stroke patients registered in the Japan Rehabilitation Database. Motor FIM score at admission was stratified into 39 groups at 2-point intervals and “median mFIM gain” was calculated for each group. With motor FIM gain as the objective variable, multiple regression analysis was performed with and without median mFIM gain in the explanatory variables. Then, correlations were examined between measured values and predicted values of motor FIM gain.Results: Adding median mFIM gain to the explanatory variables increased the correlation coefficient of measured values and predicted values of motor FIM gain from 0.507 to 0.638.Conclusion: Adding median mFIM gain to the explanatory variables can improve the accuracy of multiple regression analyses to predict motor FIM gain.