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Record W2066674357 · doi:10.1093/brain/aws093

How does parkinsonism start? Prodromal parkinsonism motor changes in idiopathic REM sleep behaviour disorder

2012· article· en· W2066674357 on OpenAlexafffund
Ronald B. Postuma, Anthony E. Lang, Jean Gagnon, Amélie Pelletier, Jacques Montplaisir

Bibliographic record

VenueBrain · 2012
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversité de MontréalMcGill University Health CentreUniversité du Québec à MontréalToronto Western HospitalMcGill UniversityCanadian Sleep & Circadian NetworkHôpital du Sacré-Cœur de MontréalUniversity of TorontoMontreal General Hospital
FundersCanadian Institutes of Health ResearchServierSanofiGlaxoSmithKline
KeywordsParkinsonismREM sleep behavior disorderRating scalePsychologyAudiologyMovement disordersPhysical medicine and rehabilitationMedicinePediatricsDiseasePsychiatryElectroencephalographyInternal medicinePolysomnographyDevelopmental psychology

Abstract

fetched live from OpenAlex

Parkinsonism, as a gradually progressive disorder, has a prodromal interval during which neurodegeneration has begun but cardinal manifestations have not fully developed. A systematic direct assessment of this interval has never been performed. Since patients with idiopathic REM sleep behaviour disorder are at very high risk of parkinsonism, they provide a unique opportunity to observe directly the development of parkinsonism. Patients with idiopathic REM sleep behaviour disorder in an ongoing cohort study were evaluated annually with several quantitative motor measures, including the Unified Parkinson's Disease Rating Scale, Purdue Pegboard, alternate-tap test and timed up-and-go. Patients who developed parkinsonism were identified from this cohort and matched according to age to normal controls. Their results on motor testing from the preceding years were plotted, and then assessed with regression analysis, to determine when markers first deviated from normal values. Sensitivity and specificity of quantitative motor markers for diagnosing prodromal parkinsonism were assessed. Of 78 patients, 20 developed parkinsonism. On regression analysis, the Unified Parkinson's Disease Rating Scale first intersected normal values at an estimated 4.5 years before diagnosis. Voice and face akinesia intersected earliest (estimated prodromal interval = 9.8 years), followed by rigidity (4.4 years), gait abnormalities (4.4 years) and limb bradykinesia (4.2 years). Quantitative motor tests intersected normal values at longer prodromal intervals than subjective examination (Purdue Pegboard = 8.6 years, alternate-tap = 8.2, timed up-and-go = 6.3). Using Purdue Pegboard and the alternate-tap test, parkinsonism could be detected with 71-82% sensitivity and specificity 3 years before diagnosis, whereas a Unified Parkinson's Disease Rating Scale score >4 identified prodromal parkinsonism with 88% sensitivity and 94% specificity 2 years before diagnosis. Removal of action tremor scores improved sensitivity to 94% and specificity to 97% at 2 years before diagnosis (cut-off >3). Although distinction between conditions was often difficult, prodromal dementia with Lewy bodies appeared to have a slower progression than Parkinson's disease (prodromal interval = 6.0 versus 3.8 years). Using a cut-off of Unified Parkinson's Disease Rating Scale >3 (excluding action tremor), 25% of patients with 'still-idiopathic' REM sleep behaviour disorder demonstrated evidence of possible prodromal parkinsonism. Therefore, using direct assessment of motor examination before parkinsonism in a REM sleep behaviour disorder, we have estimated a prodromal interval of ∼4.5 years on the Unified Parkinson's Disease Rating Scale; other quantitative markers may detect parkinsonism earlier. Simple quantitative motor measures may be capable of reliably detecting parkinsonism, even before a clinical diagnosis can be made by experienced movement disorders neurologists.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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

Citations338
Published2012
Admission routes2
Has abstractyes

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