Defining Parkinsonism in the Canadian Study of Health and Aging
Bibliographic record
Abstract
This study sought an operational definition of parkinsonism in elderly people (n = 2,914) who underwent a clinical examination in the Canadian Study of Health and Aging (CSHA). Parkinsonism was defined as having two of the following features: (1) bradykinesia of face or limbs, (2) resting tremor, (3) rigidity, and (4) abnormality of gait and posture. The association of parkinsonism with other parkinsonian-related features (prior diagnosis of Parkinson's disease, use of drugs with extrapyramidal side effects, and use of antiparkinsonian medications) and variables not expected to be related to parkinsonism (stroke and Hachinski score > 5) was determined. Parkinsonism was identified in 337 people (11.6%). It was significantly more likely with other parkinsonian-related characteristics, and was not associated with a history of stroke, but was slightly higher among those subjects with a Hachinski score > 5. Posture and gait abnormalities were significantly associated with other parkinsonian-related variables, but were also more common among subjects with stroke-related features. When the gait and posture disturbance category was excluded as a parkinsonian sign, the narrower definition was more specific but less sensitive in detecting cases with a clinical diagnosis of Parkinson's disease. Despite limitations, the approach presented in this article is a valid method to operationalize parkinsonism from the dataset.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".