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Comparison of prediction accuracy of the total score of FIM motor items at discharge in post-stroke patients in a Kaifukuki rehabilitation ward

Wada Y, Sonoda S, Okamoto S, Watanabe M, Okazaki H, Okuyama Y. Comparison of prediction accuracy of the total score of FIM motor items at discharge in poststroke patients in a Kaifukuki rehabilitation ward. Jpn J Compr Rehabil Sci 2019; 10: 71-76. Objective: We compared the accuracy of formulas for predicting ADL outcome constructed by multiple regression analysis in post-stroke patients admitted to a Kaifukuki rehabilitation ward. Methods: We divided 1,502 post-stroke patients into a construction group used to generate prediction formulas, and a validation group used to confirm the prediction accuracy. Prediction formula S was constructed by conventional multiple regression analysis using Functional Independence Measure– motor score (mFIM) at discharge as the dependent variable. Prediction formula R was constructed by reciprocal multiple regression analysis. Prediction equation E was constructed by calculating mFIM at discharge via mFIM effectiveness. In the validation group, predicted mFIM at discharge was calculated, and intraclass correlation coefficient and absolute value of residual were compared. Results: Intraclass correlation coefficients were 0.86 using prediction formula S, 0.90 using prediction formula R, and 0.89 using prediction formula E. Absolute values of residual were 9.38±6.62 using prediction formula S, 7.30±6.56 using prediction formula R, and 7.56±6.45 using prediction formula E. The Steel-Dwass test detected a significant difference between prediction formulas S and R, and between prediction formulas S and E (both p<0.05). Conclusion: The prediction accuracy of formulas for predicting ADL outcome constructed by multiple regression analysis is improved by adding a transformation that brings the model toward linearity.