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Record W4390914104 · doi:10.1002/mds.29701

Herpes Zoster and Risk of Incident Parkinson's Disease in <scp>US</scp> Veterans: A Matched Cohort Study

2024· article· en· W4390914104 on OpenAlexaff
Louis Tunnicliffe, Rimona S. Weil, Judith Breuer, Maria C. Rodriguez‐Barradas, Liam Smeeth, Christopher T. Rentsch, Charlotte Warren‐Gash

Bibliographic record

VenueMovement Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsInstitute of Infection and Immunity
FundersRaymond and Beverly Sackler Institute for Biological, Physical and Engineering Sciences, Yale UniversityWellcome TrustNational Institute on Alcohol Abuse and AlcoholismYale UniversityU.S. Department of Veterans Affairs
KeywordsInterquartile rangeMedicineCohortParkinson's diseaseProportional hazards modelCohort studyInternal medicineVeterans AffairsDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Although some systemic infections are associated with Parkinson's disease (PD), the relationship between herpes zoster (HZ) and PD is unclear. OBJECTIVE: The objective is to investigate whether HZ is associated with incident PD risk in a matched cohort study using data from the US Department of Veterans Affairs. METHODS: We compared the risk of PD between individuals with incident HZ matched to up to five individuals without a history of HZ using Cox proportional hazards regression. In sensitivity analyses, we excluded early outcomes. RESULTS: Among 198,099 individuals with HZ and 976,660 matched individuals without HZ (median age 67.0 years (interquartile range [IQR 61.4-75.7]); 94% male; median follow-up 4.2 years [IQR 1.9-6.6]), HZ was not associated with an increased risk of incident PD overall (adjusted HR 0.95, 95% CI 0.90-1.01) or in any sensitivity analyses. CONCLUSION: We found no evidence that HZ was associated with increased risk of incident PD in this cohort. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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 score0.022
Threshold uncertainty score0.593

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 head0.007
GPT teacher head0.259
Teacher spread0.252 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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