Evaluación de síntomas no motores y descontrol de impulsos en usuarios con enfermedad de Parkinson por el médico en atención primaria
Bibliographic record
Abstract
BACKGROUND: Nonmotor symptoms of Parkinson disease significantly hamper the quality of life of patients and have prognostic significance. AIM: To evaluate the presence of nonmotor symptoms in patients with Parkinson disease. MATERIAL AND METHODS: A structured interview was carried out in 32 patients aged 74 ± 9 years (53% men) with Parkinson disease asking specifically for impulse control disorders and dopaminergic dysregulation. The following scales were also applied: Hoehn & Yahr scale, Montreal Cognitive Assessment, Geriatric depression scale, Nonmotor symptom scale and REM sleep scale. RESULTS: A high frequency of nonmotor symptoms was recorded, specially mood, sleep, urinary and gastrointestinal problems and impulse control disorders. CONCLUSIONS: Nonmotor symptoms must be actively sought and managed in patients with Parkinson disease.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".