Developing a Clinical Prediction Rule for Gait Independence at Discharge in Patients with Stroke: A Decision-Tree Algorithm Analysis

To develop a clinical prediction rule (CPR) for gait independence at discharge in patients with stroke, using the decision-tree algorithm and to investigate the usefulness of CPR at admission to the rehabilitation ward. We included 181 subjects with stroke during the postacute phase. The Chi-squared...

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Vydané v:Journal of stroke and cerebrovascular diseases Ročník 31; číslo 6; s. 106441
Hlavní autori: Inoue, Yu, Imura, Takeshi, Tanaka, Ryo, Matsuba, Junji, Harada, Kazuhiro
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States Elsevier Inc 01.06.2022
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ISSN:1052-3057, 1532-8511, 1532-8511
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Shrnutí:To develop a clinical prediction rule (CPR) for gait independence at discharge in patients with stroke, using the decision-tree algorithm and to investigate the usefulness of CPR at admission to the rehabilitation ward. We included 181 subjects with stroke during the postacute phase. The Chi-squared automatic interaction detection analysis method with 10-fold cross-validation was used to develop two CPRs; CPR 1 using easily obtainable data available at admission; CPR 2 using easily obtainable data available 1 month after admission, for prediction of gait independence at discharge. The degree of independence of toileting was extracted as a first node in the development of two CPRs to predict gait independence at discharge. CPR 1 included the presence of delirium. CPR 2 included problem-solving abilities. The accuracy and area under the curve of CPR 1 were 84.5% and 0.911, respectively; those of CPR 2 were 89.0% and 0.958, respectively. Toileting independence is a key factor in predicting the gait independence for the discharge of patients with stroke during the postacute phase. Early intervention, during the acute phase, for delirium and cognitive decline, as well as for toileting, increases the possibility of gait independence at discharge.
Bibliografia:ObjectType-Article-1
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ISSN:1052-3057
1532-8511
1532-8511
DOI:10.1016/j.jstrokecerebrovasdis.2022.106441