The influence of vascular risk factors on cognitive function in early Parkinson's disease
Bibliographic record
Abstract
OBJECTIVES: Hypertension, dyslipidemia, diabetes, and obesity are well-established risk factors for cognitive impairment and dementia in older adults. In contrast, previous studies that have assessed the impact of vascular risk factors (VRFs) on cognition in Parkinson's disease (PD) have had methodological limitations and reported conflicting findings. We address this question in a large well-characterized cohort of de novo PD patients. METHODS: A total of 367 untreated and non-demented patients aged 50 years and older with early PD (H&Y = 1.0-2.0) underwent a comprehensive clinical and neuropsychological assessment at baseline and 24 months later. A series of linear mixed models were used to determine the effects of VRFs on cognition while controlling for patient and disease characteristics. The outcomes included norm-referenced Z-scores of global cognition, visuospatial skills, verbal episodic memory, semantic verbal fluency, attention, and working memory tests. RESULTS: A longer history of hypertension and a higher pulse pressure were significant predictors of lower Z-scores on immediate and delayed free recall, recognition, and verbal fluency tests. On average, every 10 mmHg increase in pulse pressure was associated with a 0.08 reduction on the cognitive Z-scores. The effects were independent of age, education, disease duration, motor impairment, medication, and depressive symptoms. Other VRFs were not associated with cognitive outcomes. CONCLUSIONS: Our results are consistent with previous studies suggesting that hypertension exerts a detrimental effect on memory and verbal fluency in early PD. Management of blood pressure and cardiovascular health may be important to reduce risk of cognitive decline in PD. Copyright © 2017 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".