43 * PATIENTS' AND PHYSICIANS' REPORTING OF NON-MOTOR SYMPTOMS IN PARKINSON'S DISEASE CLINIC ATTENDEES
Bibliographic record
Abstract
Background: Non-motor symptoms (NMS) in Parkinson's disease (PD) are associated with poor quality of life yet they are poorly recognised by physicians. The primary aim of this project was to assess the prevalence and recognition of NMS in our PD patient population. Sampling methods: Between June and November 2012 we prospectively surveyed 100 idiopathic PD patients via the movement disorder clinic. Patients or their carers completed the 30 item Non Motor Symptom Questionnaire (NMSQ). A trained assessor performed the Montreal Cognitive Assessment (MoCA). We retrospectively reviewed the clinic letters for reported NMS identified by the clinic physicians. Results: The patients' average age was 78.8 years (range 63-91) and age at onset was 72.6 years (range 53-87). 67% were males. On average patients reported 11 NMS and physicians reported 2. The most common NMS reported by patients were nocturia (66%), memory impairment (57%), urgency (54%), dribbling of saliva (52%), constipation (50%) and depression (50%); and by the physicians were hallucinations (49%), sleep disturbance (43%), falls (34%), memory impairment (25%) and autonomic symptoms (20%). Sexual problems were reported by 33/100 of whom half were over the age of 80. Cognitive impairment (MoCA < 26) was noted in 90% of patients with average MoCA of 17.9. Conclusions: Physicians under-reported urinary incontinence, constipation and depression but over-emphasised psychotic symptoms. NMS including sexual problems were reported as frequently in the older patient population as with their younger counterparts. Despite the high prevalence of cognitive impairment, this was under-reported by both patients and physicians and, importantly, it did not correlate with age or duration of illness.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.005 | 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".