| Unique ID issued by UMIN | UMIN000060150 |
|---|---|
| Receipt number | R000068796 |
| Scientific Title | Item and network analysis for functional independence measure in patients after acute stroke |
| Date of disclosure of the study information | 2025/12/22 |
| Last modified on | 2025/12/21 13:11:27 |
Item and network analysis for functional independence measure in patients after acute stroke
Item and network analysis for functional independence measure in patients after acute stroke
Item and network analysis for functional independence measure in patients after acute stroke
FIM-CogNet
| Japan |
Stroke, ischemic stroke and intracerebral hemorrhage
| Neurology | Rehabilitation medicine | Adult |
Others
NO
The purpose of this study is to characterise discharge Functional Independence Measure(FIM) cognition in patients with acute stroke by, 1)describing item attainability(difficulty) and discrimination using binary item analysis based on a clinically interpretable threshold(FIM>=5, modified independence or better), and 2)estimating the conditional dependency structure among the five cognitive items using ordinal network analysis that preserves the original 7-point ratings.
Others
To examine item characteristics(difficulty and discrimination) and interrelationships among the five discharge FIM cognitive items in patients with acute stroke.
Exploratory
Pragmatic
Not applicable
Edge weights (regularised partial correlations) and node strength centrality in a partial correlation network estimated from the 7-point ordinal discharge FIM cognitive item ratings (comprehension, expression, social interaction, problem solving, and memory).
Attainment rates using a clinically interpretable threshold (FIM>=5) and corrected item-total correlations based on dichotomised item scores for item analysis. As a sensitivity analysis, we compare the primary ordinal-based network with a network estimated using Pearson correlations treating item scores as approximately continuous.
Observational
| 20 | years-old | <= |
| Not applicable |
Male and Female
Patients admitted to the Stroke Care Unit at Kitasato University Hospital.
Primary diagnosis of ischemic stroke or intracerebral hemorrhage.
Received in-hospital rehabilitation services, including occupational, physical, and/or speech therapy.
Discharge FIM cognition was assessed, with complete data available for all five cognitive items, comprehension, expression, social interaction, problem solving, and memory.
Study period, April 2019 to November 2023.
Missing data for any of the five discharge FIM cognitive items.
Missing key demographic or clinical variables, such as age, sex, or stroke subtype.
In-hospital death.
1000
| 1st name | Satoru |
| Middle name | |
| Last name | Amano |
Kitasato University
Department of Rehabilitation
252-0329
1-15-1, Kitasato, Minami-ku, Sagamihara Kanagawa
(042)-778-9849
s-amano@kitasato-u.ac.jp
| 1st name | Satoru |
| Middle name | |
| Last name | Amano |
Kitasato University
Department of Rehabilitation
252-0329
1-15-1, Kitasato, Minami-ku, Sagamihara Kanagawa
0427789849
s-amano@kitasato-u.ac.jp
Kitasato University
Kitasato University
Self funding
Kitasato University
1-15-1, Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, JAPAN
+81-42-778-9849
s-amano@kitasato-u.ac.jp
NO
| 2025 | Year | 12 | Month | 22 | Day |
Unpublished
Preinitiation
| 2025 | Year | 12 | Month | 01 | Day |
| 2020 | Year | 03 | Month | 10 | Day |
| 2025 | Year | 12 | Month | 21 | Day |
| 2025 | Year | 12 | Month | 31 | Day |
| 2026 | Year | 01 | Month | 05 | Day |
| 2026 | Year | 01 | Month | 06 | Day |
| 2026 | Year | 01 | Month | 07 | Day |
Two analyses are performed using the five discharge FIM cognitive items. 1)For item analysis, each item is dichotomised using a clinically interpretable threshold(FIM>=5, modified independence or better), and item properties are summarised using CTT indices, including attainment rates(difficulty) and corrected item-total correlations(discrimination). 2)For network analysis, the original 7-point ordinal ratings are retained and treated as ordered factors. A network is estimated based on a polychoric correlation matrix to characterise conditional dependencies among items. Uncertainty is evaluated using bootstrap procedures, including 95% confidence intervals for edge weights and centrality stability. A sensitivity analysis is conducted using Pearson correlations treating item scores as approximately continuous.
| 2025 | Year | 12 | Month | 21 | Day |
| 2025 | Year | 12 | Month | 21 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000068796