Predicting Motor Decline and Disability in Parkinson Disease
Bibliographic record
Abstract
CONTEXT: The clinical course of Parkinson disease (PD) varies from patient to patient. A number of studies investigating predictors of prognosis in patients with PD have been performed. OBJECTIVE: To summarize evidence on predicting the rate of motor decline and increasing disability in early PD. DATA SOURCES: English-language and French-language literature cited in the MEDLINE database (1966-2002). STUDY SELECTION: Cohort and case-control studies investigating associations between clinical features and subsequent motor impairment or disability were selected. DATA EXTRACTION: Study methods and results were abstracted by a single reviewer. DATA SYNTHESIS: The results of 13 studies were summarized qualitatively. Study methods were highly variable, particularly regarding the choice of outcome measure. Baseline motor impairment and cognitive impairment are probable predictors of more rapid motor decline and disability. A lack of tremor at onset and older age both appear to be predictive of increasing disability, but conflicting results exist for their association with the rate of change of motor impairment. Family history of PD does not appear to be prognostically important. The prognostic value of many other factors studied is uncertain owing to conflicting or unconfirmed results. CONCLUSIONS: Uncertainty remains about the prognostic importance of many baseline clinical features in PD. Greater baseline impairment, early cognitive disturbance, older age, and lack of tremor at onset appear to be adverse prognostic factors.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".