Tremor in Patients with <scp>Relapsing‐Remitting</scp> Multiple Sclerosis: Clinical Characteristics and Impact on Quality of Life
Bibliographic record
Abstract
Abstract Background Little is known about the prevalence and clinical characteristics of tremors in patients with multiple sclerosis (MS), their associated clinical disability, and their impact on quality of life (QoL). Objective This study aimed to investigate the frequency and types of tremors in patients with relapsing remitting MS (RRMS) in remission, and their impact on patients’ QoL. Methods A total of 250 patients with RRMS in remission were examined for tremors. All patients were assessed using the Expanded Disability Status Scale (EDSS). Patients with tremors underwent further assessment using the Fahn‐Tolosa‐Marin Tremor Rating Scale (FTMTRS), the Beck Depression Inventory (BDI), the Montreal Cognitive Assessment (MoCA) scale, and the Short Form 36 Health Survey Questionnaire (SF‐36). Brain MRI was obtained for a subgroup of patients. Results Tremors were detected in 36 patients (14.4%) and were associated with significantly worse EDSS scores, BDI ( P = 0.021), MoCA, most SF‐36 domains, higher total and last year relapses ( P < 0.001) and longer disease duration ( P = 0.027). Patients with tremors showed higher lesion load ( P = 0.007), more infratentorial ( P ≤ 0.001), cerebellar and diencephalic lesions ( P = 0.024), and cortical atrophy ( P = 0.012). Total FTMTRS was significantly correlated to age, EDSS, and physical functioning. Dystonia was associated with tremors in 17 patients (6.8% of total RRMS patients and 47.2% of patients with tremors). Conclusion The current study confirms the common occurrence of tremors and their subtypes among patients with RRMS with mild disability and demonstrates their association with increased disability and impaired QoL.
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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 | 0.003 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".