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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| Published in: | Journal of stroke and cerebrovascular diseases Vol. 31; no. 6; p. 106441 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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United States
Elsevier Inc
01.06.2022
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| ISSN: | 1052-3057, 1532-8511, 1532-8511 |
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| Abstract | 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. |
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| AbstractList | 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. 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.OBJECTIVESTo 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.MATERIALS AND METHODSWe 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.RESULTSThe 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.CONCLUSIONSToileting 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. |
| ArticleNumber | 106441 |
| Author | Imura, Takeshi Inoue, Yu Tanaka, Ryo Harada, Kazuhiro Matsuba, Junji |
| Author_xml | – sequence: 1 givenname: Yu surname: Inoue fullname: Inoue, Yu email: y.inoue@kiui.ac.jp organization: Research Institute of Health and Welfare, Kibi International University, Takahashi, Japan – sequence: 2 givenname: Takeshi surname: Imura fullname: Imura, Takeshi organization: Graduate School of Humanities and Social Sciences, Hiroshima University, Higashi-Hiroshima, Japan – sequence: 3 givenname: Ryo surname: Tanaka fullname: Tanaka, Ryo organization: Graduate School of Humanities and Social Sciences, Hiroshima University, Higashi-Hiroshima, Japan – sequence: 4 givenname: Junji surname: Matsuba fullname: Matsuba, Junji organization: Department of Tokyo Physical Therapy, Teikyo University of Science, Tokyo, Japan – sequence: 5 givenname: Kazuhiro surname: Harada fullname: Harada, Kazuhiro organization: Research Institute of Health and Welfare, Kibi International University, Takahashi, Japan |
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| Keywords | Stroke Toileting Clinical prediction rule Gait CPR RW CHAID Independence ROC ADL FIM Decision-tree algorithm analysis AUC QOL NLR PLR 95% CI |
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| SubjectTerms | Algorithms Clinical Decision Rules Clinical prediction rule Decision Trees Decision-tree algorithm analysis Delirium Disability Evaluation Gait Humans Independence Patient Discharge Stroke Stroke - diagnosis Stroke - psychology Stroke - therapy Stroke Rehabilitation Toileting |
| Title | Developing a Clinical Prediction Rule for Gait Independence at Discharge in Patients with Stroke: A Decision-Tree Algorithm Analysis |
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