Unique ID issued by UMIN | UMIN000054230 |
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Receipt number | R000061923 |
Scientific Title | A Study of the Relationship between Multiple Factors and Prognosis of Ability to Perform Activities of Daily Living in Patients with Proximal Femur Fracture |
Date of disclosure of the study information | 2024/04/23 |
Last modified on | 2024/04/23 12:24:53 |
A Study of the Relationship between Multiple Factors and Prognosis of Ability to Perform Activities of Daily Living in Patients with Proximal Femur Fracture
A Study of the Relationship between Multiple Factors and Prognosis of Ability to Perform Activities of Daily Living in Patients with Proximal Femur Fracture
A Study of the Relationship between Multiple Factors and Prognosis of Ability to Perform Activities of Daily Living in Patients with Proximal Femur Fracture
A Study of the Relationship between Multiple Factors and Prognosis of Ability to Perform Activities of Daily Living in Patients with Proximal Femur Fracture
Japan |
Proximal Femur Fracture
Geriatrics | Orthopedics | Rehabilitation medicine |
Others
NO
Falls are the most common non-bone-related risk factor in patients with proximal femur fractures. Risk factors for falls include mental and motor dysfunction due to cranial nerve disease, musculoskeletal disease, and medications. In conventional physical therapy, the risk of falls has been assessed based on questionnaires and evaluation of physical function and motor skills. However, in the elderly, the aforementioned physical and biological dysfunctions are intricately intertwined, making prediction and prevention by a single assessment difficult. Therefore, the purpose of this study is to establish an objective and reliable fall prediction tool based on the assessment of biological functions, focusing on nerve conduction velocity. The results obtained will enable us to ensure the safety of patients during hospitalization, shorten the length of hospital stay, and guarantee the health of the elderly.
Safety,Efficacy
Presence or absence of fall events during hospitalization
Age, gender, diagnosis, medical history, length of hospitalization, destination, independence of daily living score, Functional Independence Measure score, blood and biochemical data, and medications data
Observational
Not applicable |
Not applicable |
Male and Female
Patients admitted to the recovery phase rehabilitation ward of Tsurugi Public Hospital on or after April 1, 2020 and discharged by March 31, 2022
Death and Discharge, Acute Additions
90
1st name | Akira |
Middle name | |
Last name | Kimura |
Gunma Paz University Graduate School
Medical Science
370-0006
1-7-1 Toiyacho, Takasaki City, Gunma Prefecture
027-365-3366
kimuaki@nifty.com
1st name | Eisuke |
Middle name | |
Last name | Takeshima |
Hokuriku University
Faculty of Medical and Health Sciences, Department of Physical Therapy
920-1180
1-1 Taiyougaoka, Kanazawa City, Ishikawa Prefecture
076-229-1161
e-takeshima@hokuriku-u.ac.jp
Gunma Paz University Graduate School
Gunma Paz University Graduate School
Other
Gunma Paz University Graduate School
1-7-1 Toiyacho, Takasaki City, Gunma Prefecture
027-365-3366
kimuaki@nifty.com
NO
2024 | Year | 04 | Month | 23 | Day |
Unpublished
96
No longer recruiting
2023 | Year | 04 | Month | 06 | Day |
2023 | Year | 04 | Month | 25 | Day |
2023 | Year | 04 | Month | 26 | Day |
2025 | Year | 03 | Month | 31 | Day |
Study design: Backward-looking observational study, analytical study
Study subjects: Subjects for the retrospective observational study will be patients who sustained a proximal femur fracture and were admitted to the recovery rehabilitation ward of Tsurugi Public Hospital on or after April 1, 2020, and discharged by March 31, 2022. In addition, for the cross-sectional study, patients with proximal femur fracture who were admitted to the Recovery and Rehabilitation Unit of the hospital between the approval of the ethics application and December 2023 will be included. The number of subjects for the retrospective observational study was 96.
DATA CONTENT: The backward-looking observational study will collect data currently measured in the medical record. Data to be collected will include age, gender, diagnosis, medical history, length of hospitalization (pre-admission period and admission period), destination, independence of daily living score (on admission and on discharge), functional independence assessment method score (on admission and on discharge), blood and biochemical data (on admission), and medications taken (on admission and during hospitalization).
Data collection method: The above data of the subjects will be collected from within their electronic medical records.
Method of analysis: The subjects will be divided into groups based on their history of fracture, history of previous medical history, multiple drug use, presence or absence of oral steroids, and good or bad blood biochemistry data, etc. The comparison of two groups will be statistically analyzed using t-test and Man-Whitney, the comparison of three or more groups will be analyzed using analysis of variance and kruskal-wallis, and the association will be analyzed using simple regression and multiple regression analysis. The association is statistically analyzed by using single regression or multiple regression analysis.
2024 | Year | 04 | Month | 23 | Day |
2024 | Year | 04 | Month | 23 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000061923
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