Parkinsonism in Ontario
Bibliographic record
Abstract
BACKGROUND: PD was associated with increased mortality before levodopa therapy became available. There have been conflicting reports of PD mortality in the modern era. OBJECTIVE: To assess current mortality rates in a large unselected population receiving treatment for parkinsonism (PKM) followed for up to 6 years. METHODS: Cases were identified using linked administrative databases, including physician service and prescription drug claims, generated in Ontario's universal health insurance system. Control subjects were identified from the provincial registry of citizens and age and sex matched to cases. Comparative mortality was evaluated over the 6-year period of the study (1993/94 to 1998/99). The sensitivity of the findings was tested with differing case definitions. RESULTS: In 1993, 15,304 patients with PKM were identified and were age and sex matched to 30,608 control subjects (1:2 ratio). Over the study period, 50.8% (7,779) of the cases with PKM died compared with 29.1% (8,899) of the control subjects. The cases with PKM had an overall mortality odds ratio of 2.5 (95% CI: 2.4, 2.6) compared with the control group. Results were consistent whether cases were defined by physician diagnosis, use of anti-PD drugs, or both criteria. CONCLUSION: Despite modern drug therapy, PKM continues to confer a sharply increased mortality on unselected patients followed for several years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".