TY - JOUR
T1 - Stroke outcome prediction using reciprocal number of initial activities of daily living status
AU - Sonoda, Shigeru
AU - Saitoh, Eiichi
AU - Nagai, Shota
AU - Okuyama, Yuko
AU - Suzuki, Toru
AU - Suzuki, Miho
PY - 2005/1
Y1 - 2005/1
N2 - Multiple regression analysis was performed in 87 stroke patients who were admitted to a rehabilitation hospital to predict the total motor subscore of the Functional Independence Measure (FIM) at discharge. In addition to the total cognitive subscore of the FIM at admission, age, and days from stroke onset to admission, the total motor subscore of the FIM at admission or its reciprocal number was added to independent variables. The correlation coefficients between the predicted and actual values were. 88 (ordinary regression) and. 93 (reciprocal regression) in the validation group (44 stroke patients). The median of the residuals (i.e, absolute values of subtraction of predicted motor-FIM from actual motor-FIM at discharge) of the reciprocal prediction (4.57) was significantly smaller than that of the ordinary prediction (6.26). In conclusion, the reciprocal prediction of regression analysis provided a more precise prediction without additional complex calculations.
AB - Multiple regression analysis was performed in 87 stroke patients who were admitted to a rehabilitation hospital to predict the total motor subscore of the Functional Independence Measure (FIM) at discharge. In addition to the total cognitive subscore of the FIM at admission, age, and days from stroke onset to admission, the total motor subscore of the FIM at admission or its reciprocal number was added to independent variables. The correlation coefficients between the predicted and actual values were. 88 (ordinary regression) and. 93 (reciprocal regression) in the validation group (44 stroke patients). The median of the residuals (i.e, absolute values of subtraction of predicted motor-FIM from actual motor-FIM at discharge) of the reciprocal prediction (4.57) was significantly smaller than that of the ordinary prediction (6.26). In conclusion, the reciprocal prediction of regression analysis provided a more precise prediction without additional complex calculations.
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U2 - 10.1016/j.jstrokecerebrovasdis.2004.10.001
DO - 10.1016/j.jstrokecerebrovasdis.2004.10.001
M3 - Article
C2 - 17903990
AN - SCOPUS:11844283261
SN - 1052-3057
VL - 14
SP - 8
EP - 11
JO - Journal of Stroke and Cerebrovascular Diseases
JF - Journal of Stroke and Cerebrovascular Diseases
IS - 1
ER -