| Autor: |
Güp, Asalet Aybüke, Ipek Dongaz, Özge, Özen Oruk, Dilara, Deveci, Emrah Emre, Bayar, Banu, Bayar, Kılıçhan |
| Předmět: |
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| Zdroj: |
Neurological Research; Oct2023, Vol. 45 Issue 10, p947-956, 10p |
| Abstrakt: |
The objective of this study was to develop predictive models for estimating the length of stay (LOS) with standardized clinical outcome measures (Functional Independence Measure, Trunk Impairment Scale, Postural Assessment Scale for Stroke Patients, Fugl Meyer Assessment Scale, and Functional Ambulation Category) during acute care setting. One hundred sixty-nine patients were included in the retrospective study. Predictors chosen for the LOS included scores of functional outcome measures at admission. We used Spearman's rank correlation coefficients to calculate correlations among clinical outcome measures and LOS, stepwise multiple regression analysis to develop a predictive model, and receiver operating characteristics curve to analyze the predictive value of explanatory factors obtained from the previous model for discharge Functional Independence Measure score. The predictive equation explained 81% of the variance in LOS. The most important predictors were trunk impairment, motor function of the upper extremity, walking ability, and independence level at admission. The receiver operating characteristic curve was obtained with a cut-off score of 13 points for the Trunk Impairment Scale, 47 points for Fugl Meyer Assessment-Upper Extremity, and 2 points for Functional Ambulation Category, demonstrating the highest percentage of the accurately predicted ability of independence level at discharge. The models presented in this study could help clinicians and researchers to predict the LOS and discharge independence level of clinical outcomes for patients with acute stroke enrolled in an acute care setting. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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