Smoking history is associated to cognitive impairment in Parkinson's disease
Bibliographic record
Abstract
INTRODUCTION: Patients with Parkinson's disease (PD) are more likely to suffer from cognitive impairment and dementia than healthy older adults. The aim of this study was to investigate smoking history as a risk factor for cognitive decline in PD. METHOD: One hundred thirty-nine PD patients aged 50 years and older (Hoehn and Yahr = 1-3) were recruited from a clinical database. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE) and smoking history was investigated as part of a standard clinical interview. A multiple linear regression analysis was used to develop a model for predicting participants' MMSE scores from age, education, Hoehn and Yahr stage, disease duration, the number of vascular risk factors and the number of smoking pack-years. RESULTS: The regression model significantly accounted for 22.9% of the variance in MMSE scores. Significant predictors were education (β = .312, p < .001), age (β = -.215, p = .013) and total smoking pack-years (β = -.180, p = .029). In former smokers, the number of years since quitting had no effect on global cognition and there were no significant difference between patients who had quit smoking more than 10 years ago and those who had quit less than 10 years ago, F(1, 63) = 1.72, p = .195. CONCLUSION: Smoking history was associated to global cognitive impairment in PD even in patients who had quit smoking. These results are in line with findings in healthy older adults that have linked smoking to cognitive impairment, global brain atrophy and functional changes. Future studies should consider a broader assessment of cognitive functions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".