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Record W2161277679 · doi:10.1002/mds.25319

Caffeine consumption and risk of dyskinesia in <scp>CALM</scp>‐<scp>PD</scp>

2013· article· en· W2161277679 on OpenAlexaff
Anne‐Marie Wills, Shirley Eberly, Marsha Tennis, Anthony E. Lang, Susan Messing, Daniel M. Togasaki, Caroline M. Tanner, Cornelia Kamp, Jiang‐Fan Chen, David Oakes, Michael McDermott, Michael A. Schwarzschild

Bibliographic record

VenueMovement Disorders · 2013
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Institute of Neurological Disorders and Stroke
KeywordsDyskinesiaPramipexoleHazard ratioMedicineParkinson's diseaseParoxysmal dyskinesiaLevodopaCohortInternal medicineAnesthesiaPsychologyConfidence intervalDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Adenosine A2A receptor antagonists reduce or prevent the development of dyskinesia in animal models of levodopa-induced dyskinesia. METHODS: We examined the association between self-reported intake of the A2A receptor antagonist caffeine and time to dyskinesia in the Comparison of the Agonist Pramipexole with Levodopa on Motor Complications of Parkinson's Disease (CALM-PD) and CALM Cohort extension studies, using a Cox proportional hazards model adjusting for age, baseline Parkinson's severity, site, and initial treatment with pramipexole or levodopa. RESULTS: For subjects who consumed >12 ounces of coffee/day, the adjusted hazard ratio for the development of dyskinesia was 0.61 (95% CI, 0.37-1.01) compared with subjects who consumed <4 ounces/day. For subjects who consumed between 4 and 12 ounces/day, the adjusted hazard ratio was 0.73 (95% CI, 0.46-1.15; test for trend, P = .05). CONCLUSIONS: These results support the possibility that caffeine may reduce the likelihood of developing dyskinesia.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.234
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2013
Admission routes1
Has abstractyes

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