Incidence of Parkinson disease in North America
Bibliographic record
Abstract
Parkinson disease (PD) is the second most common age-related neurodegenerative condition diagnosed in North America. We recently demonstrated, using multiple epidemiological data sources, that the prevalence of PD diagnoses was greater than previously reported and currently used for clinical, research, and policy decision-making. Prior PD incidence estimates have varied, for unclear reasons. There is a need for improved estimates of PD incidence, not only for care delivery planning and future policy but also for increasing our understanding of disease risk. The objective of this study was thus to investigate the incidence of Parkinson disease across five epidemiological cohorts in North America in a common year, 2012. The cohorts contained data on 6.7 million person-years of adults ages 45 and older, and 9.3 million person-years of adults ages 65 and older. Our estimates of age-sex-adjusted incidence of PD ranged from 108 to 212 per 100,000 among persons ages 65 and older, and from 47 to 77 per 100,00 among persons ages 45 and older. PD incidence increased with age and was higher among males. We also found persistent spatial clustering of incident PD diagnoses in the U.S. PD incidence estimates varied across our data sources, in part due to case ascertainment and diagnosis methods, but also possibly due to the influence of population factors (prevalence of genetic risk factors or protective markers) and geographic location (exposure to environmental toxins). Understanding the source of these variations will be important for health care policy, research, and care planning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".