[OES-1-2] Predictive factor of activities of daily living at discharge on rehabilitation phase stroke patients
Background
Establishing an early therapeutic strategy is essential to provide patients with effective rehabilitation services. In recovery phase after stroke, multiple regression models are often used to predict ADL independence at discharge based on various admission data. When comparing predictive and measured values in our hospital data, the multiple regression model indicates overall good predictive accuracy, however, accuracy is not satisfied in some patients. We assume it is because that the level of ADL independence on admission is not considered in the model. The aim of this study was to identify factors affecting discharge ADL independence, when the patients were divided into low ADL independence and high ADL independence groups.
Method
The study sample included a total of 186 stroke patients who were admitted at our rehabilitation ward unit from December 2018 to February 2022. The study sample were divided into two groups according to Functional Independence Measure motor score (FIM-M) on admission; low FIM-M group (13-39 points, n=85) and high FIM-M group (40-91 points, n=101). Patients’ data on admission including age, sex, onset days, hand dominance of disability side (dominance hand had paresis/ non-dominance hand had paresis), Fugl Meyer Assessment Upper extremity (FMA), both arm grip force, cognitive impairment (yes/no), FIM-M, and FIM-C, and then discharge FIM-M were collected. A stepwise multiple regression analysis was performed in each group with discharge FIM-M as the dependent variable and data on admission as the independent variable. Ethics approval was obtained from the Clinical Research Ethics Committee of the authors’ hospital.
Result
In the low FIM-M group multiple regression analysis, FIM-C (β = 1.369, p < 0.001), age (β = -0.457, p < 0.001) and hand dominance of disability side (β = 13.092, p < 0.01) were identified predicting FIM-M at discharge (adjusted R2: 0.368). On the other hand, in high FIM-M group, age (β = -0.318, p < 0.001) and onset days (β = -0.73, p < 0.05) predicted FIM-M at discharge (adjusted R2: 0.188).
Conclusion
While age was extracted as a factor common in both groups, FIM-C and hand dominance of disability side were extracted as unique factors in the low FIM-M group, and onset days were extracted as unique factors in the high FIM-M group. The results indicate that different abilities on admission may affect ADL at discharge. We suggest that therapists should consider the different factor on admission to predict ADL independence at discharge in order to establish optimal early therapeutic strategy.
Establishing an early therapeutic strategy is essential to provide patients with effective rehabilitation services. In recovery phase after stroke, multiple regression models are often used to predict ADL independence at discharge based on various admission data. When comparing predictive and measured values in our hospital data, the multiple regression model indicates overall good predictive accuracy, however, accuracy is not satisfied in some patients. We assume it is because that the level of ADL independence on admission is not considered in the model. The aim of this study was to identify factors affecting discharge ADL independence, when the patients were divided into low ADL independence and high ADL independence groups.
Method
The study sample included a total of 186 stroke patients who were admitted at our rehabilitation ward unit from December 2018 to February 2022. The study sample were divided into two groups according to Functional Independence Measure motor score (FIM-M) on admission; low FIM-M group (13-39 points, n=85) and high FIM-M group (40-91 points, n=101). Patients’ data on admission including age, sex, onset days, hand dominance of disability side (dominance hand had paresis/ non-dominance hand had paresis), Fugl Meyer Assessment Upper extremity (FMA), both arm grip force, cognitive impairment (yes/no), FIM-M, and FIM-C, and then discharge FIM-M were collected. A stepwise multiple regression analysis was performed in each group with discharge FIM-M as the dependent variable and data on admission as the independent variable. Ethics approval was obtained from the Clinical Research Ethics Committee of the authors’ hospital.
Result
In the low FIM-M group multiple regression analysis, FIM-C (β = 1.369, p < 0.001), age (β = -0.457, p < 0.001) and hand dominance of disability side (β = 13.092, p < 0.01) were identified predicting FIM-M at discharge (adjusted R2: 0.368). On the other hand, in high FIM-M group, age (β = -0.318, p < 0.001) and onset days (β = -0.73, p < 0.05) predicted FIM-M at discharge (adjusted R2: 0.188).
Conclusion
While age was extracted as a factor common in both groups, FIM-C and hand dominance of disability side were extracted as unique factors in the low FIM-M group, and onset days were extracted as unique factors in the high FIM-M group. The results indicate that different abilities on admission may affect ADL at discharge. We suggest that therapists should consider the different factor on admission to predict ADL independence at discharge in order to establish optimal early therapeutic strategy.