Bibliographic record
Abstract
Introduction: Essential tremor (ET) is the most common movement disorder, and studies suggest that in addition to motor symptoms, there may also be non-motor symptoms.In this study, we aimed to investigate the clinical characteristics and the impact of disease severity on daily life in Turkish patients with ET.Methods: Thirty patients with ET and 30 gender-matched healthy controls were included.The Montreal Cognitive Assessment (MoCA), Pittsburgh Sleep Quality Index (PSQI), Non-Motor Symptoms Questionnaire (NMSQ), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) were utilized to assess and compare psychiatric and cognitive status and sleep disturbances, and to investigate whether these symptoms are related to the severity of motor symptoms.Tremor severity was evaluated by the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS).Results: The average BDI, BAI, and NMSQ scores were significantly higher in the patient group (p<0.005).A positive correlation was observed between disease duration and PSQI, BAI, and NMSQ scores (p=0.028,p=0.041, p=0.047, respectively).FTM-TRS scores showed a negative correlation with MoCA and a positive correlation with PSQI, BDI, BAI, and NMSQ scores (p=0.005,p<0.001, p=0.005, p=0.004).The average MoCA score in patients over 45 years old was significantly lower (p=0.008).Discussion and Conclusion: Our results indicated that non-motor symptoms such as anxiety, decreased sleep quality, and impaired cognitive functions accompanying ET significantly affect patients' quality of life.Therefore, evaluating and treating non-motor symptoms should be considered essential for the rehabilitation of patients with ET.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".