Predictive factors of home discharge in elderly stroke patients hospitalized in a convalescent rehabilitation ward

Sato, Ken

doi:10.11336/jjcrs.11.43

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…In a previous Japanese study on the likelihood of discharge to home for patients admitted to a convalescent ward using a logistic regression analysis, the accuracy was 87.8% 2) , 88.3% 20) , and the AUC–ROC was reported to be 0.827–0.866 12) , 0.891 21) . The accuracy and AUC–ROC in these previous studies were higher in comparison to the present study.…”

Section: Discussionmentioning

confidence: 95%

“…The results suggest that if a patient possesses the capability of performing grooming activities with light assistance at the time of convalescent ward admission, the likelihood of being discharged home is higher. Subsequent branching points, the duration of acute hospitalization, have been reported in a study as factors influencing the discharge destination 21) . For the duration of acute hospitalization, shorter stays have been reported to increase the likelihood of home discharge.…”

Section: Discussionmentioning

confidence: 96%

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Development and Validation of a Decision Tree Analysis Model for Predicting Home Discharge in a Convalescent Ward: A Single Institution Study

NAKAIZUMI,

MIYATA,

UCHIYAMA

et al. 2024

Phys Ther Res

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Objectives: Accurately predicting the likelihood of inpatients’ home discharge in a convalescent ward is crucial for assisting patients and families in decision-making. While logistic regression analysis has been commonly used, its complexity limits practicality in clinical settings. We focused on decision tree analysis, which is visually straightforward. This study aimed to develop and validate the accuracy of a prediction model for home discharge for inpatients in a convalescent ward using a decision tree analysis. Methods: The cohort consisted of 651 patients admitted to our convalescent ward from 2018 to 2020. We collected data from medical records, including disease classification, sex, age, duration of acute hospitalization, discharge destination (home or nonhome), and Functional Independence Measure (FIM) subitems at admission. We divided the cohort data into training and validation sets and developed a prediction model using decision tree analysis with discharge destination as the target and other variables as predictors. The model’s accuracy was validated using the validation data set. Results: The decision tree model identified FIM grooming as the first single discriminator of home discharge, diverging at four points and identifying subsequent branching for the duration of acute hospitalization. The model’s accuracy was 86.7%, with a sensitivity of 0.96, specificity of 0.52, positive predictive accuracy of 0.88, and negative predictive accuracy of 0.80. The area under the receiver operating characteristic curve was 0.75. Conclusion: The predictive model demonstrated more than moderate predictive accuracy, suggesting its utility in clinical practice. Grooming emerged as a variable with the highest explanatory power for determining home discharge.

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Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 96%

Development and Validation of a Decision Tree Analysis Model for Predicting Home Discharge in a Convalescent Ward: A Single Institution Study

NAKAIZUMI,

MIYATA,

UCHIYAMA

et al. 2024

Phys Ther Res

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Outcome measures for older adults in rehabilitation wards: a systematic review

Suzumura,

Takano,

Teranishi

et al. 2024

F1000Res

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Purpose Detailed reports of the assessments used in rehabilitation wards are lacking. This study aimed to examine the common evaluations used in rehabilitation wards and discuss the necessary assessments for treatment plans and patient management. Methods We conducted a comprehensive literature search of PubMed, Web of Science, MEDLINE, and Ichushi Web for articles published between June 2013 and June 2023. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and registered with PROSPERO. Data extraction and blind selection were performed, and a consensus was reached among experts in case of conflicts. Results We identified 220 studies, 31 meeting the inclusion criteria post-screening. The Functional Independence Measure was the most used assessment (96.8%), followed by grip strength (32.3%) and the 10-m walk test (9.7%). Other assessments included the Stroke Impairment Assessment Set, Short Physical Performance Battery, and Timed Up and Go Test. Although fall-related incidents are frequent, significantly affecting patient outcomes in rehabilitation units, balance assessments were underutilized. Conclusions Although the FIM is an extensively used assessment in rehabilitation wards, balance assessments critical for fall prevention are significantly underused. Therefore, these assessment tools should be evaluated in future research and clinical practice.

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Interaction between Self-Care and Caregiving Ability on Home Discharged Stroke Patients Based on Motor Functional Independence Measure Score in Recovery Ward

Kimura¹

2021

OJTR

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Background: A correlation has been found between self-care and caregiving ability in home discharged stroke patients. However, few studies have explored the interaction between individual self-care and caregiving ability. Purpose: This study aimed to investigate the interaction between individual self-care and caregiving ability in home discharged stroke patients. Participants and Methods: A total of 2688 stroke patients registered in the Japanese Rehabilitation Database (JRD) were retrospectively analyzed. Patients were classified into two groups based on their discharge destination (home discharge, non-home discharge), and the data were modified as mean-centered values. After a correlation analysis was performed between all the collected data, a hierarchical multiple regression analysis evaluated the interaction using discharge destination as the dependent variable. Model 1 used two independent variables (Rankin scale and cognitive functional independence measure score), model 2 used two independent variables (caregiving ability and individual self-care), and model 3 used a mean-centering value, which was added to model 2. A simple slope was used for further analysis. Results: Self-care showed an interaction with caregiving ability. The R 2 changes in models 1 and 2 were significant in the following: grooming, bathing, gait, and climbing stairs (p < 0.01). Additionally, the results of the simple slope analysis were significant for all areas. Conclusion: Based on the JRD, this study suggested that a focus on improving these areas, especially climbing stairs, is effective in preparing for home discharge and should be positively considered for stroke patients.

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Predictive factors of home discharge in elderly stroke patients hospitalized in a convalescent rehabilitation ward

Abstract: Sato K: Predictive factors of home discharge in elderly stroke patients hospitalized in a convalescent rehabilitation ward.

Cited by 3 publications

References 11 publications

Development and Validation of a Decision Tree Analysis Model for Predicting Home Discharge in a Convalescent Ward: A Single Institution Study

Development and Validation of a Decision Tree Analysis Model for Predicting Home Discharge in a Convalescent Ward: A Single Institution Study

Outcome measures for older adults in rehabilitation wards: a systematic review

Interaction between Self-Care and Caregiving Ability on Home Discharged Stroke Patients Based on Motor Functional Independence Measure Score in Recovery Ward

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