A Study on the Correlation Between General Characteristics, Cognitive Function, and Physical Function in Chronic Stroke Patients With Community Ambulation
Bibliographic record
Abstract
This study aimed to use basic data to develop a comprehensive intervention program to effectively improve cognitive and physical functions in individuals ≥ 60 years of age who experienced chronic stroke and are capable of independent walking in the community. This study analyzed the general characteristics of and correlations between cognitive and physical functions to develop the program. Subjects included individuals who voluntarily expressed their willingness to participate in the clinical trial from the recruitment notice posted at N institution (Seoul, South Korea) and fulfilled the following selection criteria: age≥60 years and diagnosed with stroke, with an onset of at least 2 years; Modified Barthel Index score≥75, indicating that a mild level of assistance was required and capable of independent mobility in the community; and absence of neglect in the line bisection test and able to follow test instructions. As a result, of the 23 individuals recruited, 16 were ultimately included. The Korean version of the Montreal Cognitive Assessment (i.e., “K-MoCA”) was used to assess cognitive function. Physical function was assessed using static balance tests, including the Romberg, semi-Romberg, and tandem Romberg tests. Dynamic balance tests included a 4 m walking speed test, a 5-time chair stand test, and Timed Up and Go (TUG) test. Data analysis was performed using SPSS version 22.0 (IBM Corporation, Armonk, NY, USA), and Spearman's rank-order correlation was used for correlation analysis. The cognitive function of patients with stroke exhibited a slight correlation with 4 m walking speed (r=-.564), while 4 m walking speed and TUG exhibited a negative correlation (r=-.787) (p<.05). Based on these findings, when presenting a comprehensive cognitive-physical intervention program for community-dwelling stroke patients, it may be inferred that there is a correlation between cognitive function and dynamic balance ability. This can serve as evidence supporting the development of detailed programs for comprehensive intervention(s).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".