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Record W2955208925 · doi:10.1002/mds.27775

Evolution and clustering of prodromal parkinsonian features in <i>GBA1</i> carriers

2019· article· en· W2955208925 on OpenAlexfundaboutno aff
Stephen Mullin, Michelle Beavan, Jonathan P. Bestwick, Alisdair McNeill, Christos Proukakis, Timothy M. Cox, Derralynn Hughes, Atul Mehta, Henrik Zetterberg, Anthony H.V. Schapira

Bibliographic record

VenueMovement Disorders · 2019
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsnot available
FundersMedical Research CouncilUniversity College London Hospitals NHS Foundation TrustMedical Research Council CanadaVetenskapsrådetNational Institute for Health and Care ResearchEU Joint Programme – Neurodegenerative Disease ResearchKnut och Alice Wallenbergs StiftelseWellcome Trust
KeywordsCluster analysisNeurosciencePsychologyMedicineArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Five to 25% of patients with PD carry glucocerebrosidase gene mutations, and 10% to 30% of glucocerebrosidase carriers will develop PD by age 80. Stratification of PD risk in glucocerebrosidase carriers provides an opportunity to target disease-modifying therapies. OBJECTIVE: Cross-sectional and longitudinal survey of prodromal PD signs among glucocerebrosidase carriers. DESIGN: Prospective assessment of 82 glucocerebrosidase mutation carriers and 35 controls over 4 to 5 years for prodromal clinical PD features. RESULTS: At all time points, olfactory (measured using University of Pennsylvania Smell Identification Test) and cognitive (Montreal Cognitive Assessment) function and the International Parkinson and Movement Disorder Society UPDRS parts II and III scores were significantly worse amongst glucocerebrosidase mutation carriers. Progression to microsmia (odds ratio: 8.5; 95% confidence interval: 2.6-28.2; P < 0.05) and mild cognitive impairment (odds ratio: 4.2; 95% confidence interval: 1.1-16.6; P < 0.05) were more rapid compared to controls. Those with worse olfaction also had worse cognition (OR, 1.5; 95% CI: 0.0-2.8; P < 0.05) and depression (OR, 1.3; 95% CI: 0.6-2.8; P < 0.05). No participants reached the MDS prodromal PD diagnostic criteria before PD diagnosis. One participant developed PD. He did not fulfill the International Parkinson and Movement Disorder Society prodromal PD criteria before diagnosis. CONCLUSION: Assessment of individual and clustered PD prodromal features may serve as a useful tool to identify high-risk subjects for conversion to PD. As a result of the low conversion rate in our glucocerebrosidase mutation carriers to date, prospective validation is needed in larger cohorts to establish the profile of these features in PD convertors. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. 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 score0.008
Threshold uncertainty score0.508

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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

Citations46
Published2019
Admission routes2
Has abstractyes

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