Multiple Sclerosis Walking Scale-12 (MSWS-12) and its Relationship With Fatigue in People With Multiple Sclerosis
Bibliographic record
Abstract
Background and Objectives: Walking disorder is one of the most important manifestations of multiple sclerosis (MS), and indicates the progression of the disease. Fatigue and walking are considered as key symptoms affecting the patient’s quality of life. Therefore, this study aimed to investigate the relationship between walking status and fatigue, in people with MS. Methods: A total number of 60 Iranian patients with MS completed the Persian version of the Multiple Sclerosis Walking Scale-12 (MSWS-12), the Modified Fatigue Impact Scale, and the Hospital Anxiety and Depression Scale. Data were analyzed using SPSS V. 20 software. The multivariate correlation and linear regression analyses were conducted to investigate the relationship between fatigue, anxiety, depression, demographic characteristics, and MSWS-12 scores. Results: Gait problems were observed in 46.7% of the study participants. Also, the MSWS-12 scores were significantly associated with fatigue severity (P=0.001), in these patients. Moreover, depression, cognitive status, anxiety, and gait status were the most important factors affecting fatigue. Conclusion: According to the present results, the presence of depression, cognitive problems, anxiety, and gait disorders are the most important factors affecting fatigue, in patients with MS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".