Stroke and Coronary Artery Disease Are Associated With Parkinson’s Disease
Bibliographic record
Abstract
BACKGROUND: The relationship between vascular disease and Parkinson's disease (PD) is controversial. We performed a cross-sectional study to investigate the association of two common vascular diseases (stroke and coronary artery disease [CAD]) with Parkinson's disease. METHODS: We identified 63 and 62 PD cases in two population-based cohorts (Malu rural community and Wuliqiao urban community) and collected information of PD and non-PD by means of questionnaires. Logistic regression analysis was used to investigate the association between stroke, coronary artery disease and PD, after adjusting for age, sex, hypertension, diabetes mellitus, hypercholesterolemia, smoking status, alcohol consumption, tea consumption and body mass index. RESULTS: After adjustment for potential confounders, we found that CAD and stroke were associated with PD in the Malu rural community (CAD: odds ratio [OR]=7.11, 95% confidence intervals [CI]: 3.09-16.40, p<0.001; stroke: OR=6.77, 95% CI: 3.09-14.81, p<0.001) and stroke was associated with PD in the Wuliqiao urban community (OR=2.58, 95% CI: 1.36-4.89, p=0.004), especially in women. In a subgroup analysis of PD with age- and sex-matched controls, the results were similar in the Malu rural community (CAD: OR=12.72, 95% CI: 2.92-55.32, p=0.001; stroke: OR=6.26, 95% CI: 1.83-21.42, p=0.003), whereas in the Wuliqiao urban community the results were different in that CAD (but not stroke) was found to be associated with PD (CAD: OR=2.44, 95% CI: 1.09-5.47, p=0.03; stroke: OR=1.79, 95% CI: 0.77-4.17, p=0.18). CONCLUSIONS: Our study suggested that stroke and CAD are associated with PD in two Chinese population-based cohorts, indicating a probable vascular component in the pathogenesis of PD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".