Caffeine and Progression of Parkinson Disease
Bibliographic record
Abstract
OBJECTIVE: Increased caffeine intake is associated with a lower risk of Parkinson disease (PD) and is neuroprotective in mouse models of PD. However, in a previous study, an exploratory analysis suggested that, in patients taking creatine, caffeine intake was associated with a faster rate of progression. In the current study, we investigated the association of caffeine with the rate of progression of PD and the interaction of this association with creatine intake. METHODS: Data were analyzed from a large phase 3 placebo-controlled clinical study of creatine as a potentially disease-modifying agent in PD. Subjects were recruited for this study from 45 movement disorders centers across the United States and Canada. A total of 1741 subjects with PD participated in the primary clinical study, and caffeine intake data were available for 1549 of these subjects. The association of caffeine intake with rate of progression of PD as measured by the change in the total Unified Parkinson Disease Rating Scale score and the interaction of this association with creatine intake were assessed. RESULTS: Caffeine intake was not associated with the rate of progression of PD in the main analysis, but higher caffeine intake was associated with significantly faster progression among subjects taking creatine. CONCLUSIONS: This is the largest and longest study conducted to date that addresses the association of caffeine with the rate of progression of PD. These data indicate a potentially deleterious interaction between caffeine and creatine with respect to the rate of progression of PD.
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 | 0.002 |
| 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 | 0.000 | 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 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".