Identification of motor and nonmotor wearing‐off in Parkinson's disease: Comparison of a patient questionnaire versus a clinician assessment
Bibliographic record
Abstract
This study compares the sensitivity of a Patient Questionnaire versus information gathered by clinicians at a routine clinic visit in recognizing symptoms of wearing-off in early Parkinson's disease (PD). This Patient Questionnaire, containing 32 items representing a wide spectrum of motor and nonmotor wearing-off symptoms, was administered to subjects attending two PD clinics. The Patient Questionnaire results were compared to the information gathered by the clinician from the Unified Parkinson's Disease Rating Scale (UPDRS) Part IV, Question 36 and from a specific Clinical Assessment Question regarding loss of medication efficacy, wearing-off, sleepiness, dyskinesias, psychiatric complications, morning akinesia, other dopaminergic side effects, or none of the above. Examiners were blinded to study hypothesis and survey contents. Three hundred consecutive subjects with PD of <5 years duration were evaluated; the mean subject age was 72 +/- 9.6 years and 60.2% were men. Subjects reporting wearing-off were significantly younger (69.9 vs. 74.7 years) and differed regarding duration of PD symptoms (3.7 vs. 3.1 years). Wearing-off was found in 181 subjects (62.6%) by one or more of the three measures. The most sensitive tool was the Patient Questionnaire, with 165 subjects (57.1%) indicating symptoms of wearing-off. Question 36 of the UPDRS was positive in 127 subjects (43.9%), and the Clinical Assessment Question identified 85 subjects (29.4%) as experiencing wearing-off. All of these results were found to differ significantly. The mean number of wearing-off symptoms reported by the 165 subjects indicating wearing-off on the clinical survey was 6.25, with tremor being the most common motor feature and tiredness the most common nonmotor feature.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".