Unique ID issued by UMIN | UMIN000056696 |
---|---|
Receipt number | R000064809 |
Scientific Title | Prognostic Prediction for Stroke Patients Using Machine Learning |
Date of disclosure of the study information | 2025/01/13 |
Last modified on | 2025/01/13 00:39:11 |
Validation of a Prognostic Model for Discharge Functional Independence Measure in Stroke Patients Considering the Impact of Aging
Validation of a Prognostic Model for Discharge Functional Independence Measure in Stroke Patients Considering the Impact of Aging
Prognostic Prediction for Stroke Patients Using Machine Learning
Prognostic Prediction for Stroke Patients Using Machine Learning
Japan |
Ischemic Stroke and Hemorrhagic Stroke
Rehabilitation medicine |
Others
NO
The purpose of this study was to develop and validate a prognostic model to predict discharge Functional Independence Measure , focusing on variables that are observable and compatible with the aging stroke population in Japan.
Efficacy
Prediction Accuracy of Functional Independence Measure (FIM) at Discharge
Observational
Not applicable |
Not applicable |
Male and Female
Patients diagnosed with ischemic or hemorrhagic stroke who were admitted to a convalescent rehabilitation ward for 30 days or more between January 2018 and December 2020.
Those who experienced recurrence or worsening of their condition during hospitalization
Those who suffered a stroke (cerebral infarction or cerebral hemorrhage) while being hospitalized in another hospital
Those with a history of neurological diseases other than stroke
Those with a history of mental illness or developmental disorders
Those who developed epilepsy or hydrocephalus at the time of stroke onset
Those who experienced a stroke due to Moyamoya disease
Those who required restrictions on rehabilitation in the convalescent rehabilitation ward
Those with a history of blindness
Those who died during hospitalization
Those with missing data
300
1st name | Ryo |
Middle name | |
Last name | Matsuda |
Hokkaido University of Science
Department of Physical Therapy Faculty of Health Sciences
006-8585
15-4-1, Maeda 7-jo, Teine-ku, Sapporo-shi, Hokkaido, Japan
+81-11-688-7197
matsuda-r@hus.ac.jp
1st name | Ryo |
Middle name | |
Last name | Matsuda |
Hokkaido University of Science
Department of Physical Therapy Faculty of Health Sciences
006-8585
15-4-1, Maeda 7-jo, Teine-ku, Sapporo-shi, Hokkaido, Japan
+81-11-688-7197
matsuda-r@hus.ac.jp
Hokkaido University of Science
Ryo Matsuda
Self-funding
Self funding
Japan
Shinsapporo Neurosurgical Hospital
None
Shinsapporo Neurosurgical Hospital Ethics Committee
6-2-10, Atsubetsu Chuo 1-jo, Atsubetsu-ku, Sapporo-shi, Hokkaido, Japan
+81-11-891-2500
regalw4910@gmail.com
NO
北海道科学大学(北海道)、新さっぽろ脳神経外科病院(北海道)
2025 | Year | 01 | Month | 13 | Day |
Unpublished
299
No longer recruiting
2022 | Year | 03 | Month | 07 | Day |
2022 | Year | 03 | Month | 07 | Day |
2022 | Year | 03 | Month | 07 | Day |
2024 | Year | 03 | Month | 10 | Day |
We collected data at admission and discharge from the medical records of patients diagnosed with cerebral infarction or cerebral hemorrhage who were admitted to a convalescent rehabilitation ward for 30 days or more between January 2018 and December 2020.
2025 | Year | 01 | Month | 13 | Day |
2025 | Year | 01 | Month | 13 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000064809