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Record W2994908519 · doi:10.3233/jpd-191775

The Quebec Parkinson Network: A Researcher-Patient Matching Platform and Multimodal Biorepository

2019· article· en· W2994908519 on OpenAlexafffundabout
Ziv Gan‐Or, Trisha Rao, Etienne Léveillé, Clotilde Degroot, Sylvain Chouinard, Francesca Cicchetti, Alain Dagher, Samir Das, Alex Désautels, Janelle Drouin‐Ouellet, Thomas M. Durcan, Jean‐François Gagnon, Angela Genge, Jason Karamchandani, Anne‐Louise Lafontaine, Sonia Lai Wing Sun, Mélanie Langlois, Martin Lévesque, Calvin Melmed, Michel Panisset, Martin Parent, Jean‐Baptiste Poline, Ronald B. Postuma, Emmanuelle Pourcher, Guy A. Rouleau, Madeleine Sharp, Oury Monchi, Nicolas Dupré, Edward A. Fon

Bibliographic record

VenueJournal of Parkinson s Disease · 2019
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsJewish General HospitalMcGill University Health CentreUniversité du Québec à MontréalCanadian Sleep & Circadian NetworkCentre hospitalier universitaire de QuébecUniversity of CalgaryCentre Hospitalier de l’Université de MontréalMcGill UniversityUniversité de MontréalUniversité LavalMontreal Neurological Institute and Hospital
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute on Drug AbuseNational Institute of Mental HealthFonds de Recherche du Québec - SantéParkinson CanadaCanadian Institutes of Health ResearchNational Institutes of HealthFondation Brain CanadaMcGill University
KeywordsMedicineParkinson's diseaseCohortDyskinesiaMovement disordersDiseaseInternal medicinePhysical medicine and rehabilitationPediatricsPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Genetic, biologic and clinical data suggest that Parkinson's disease (PD) is an umbrella for multiple disorders with clinical and pathological overlap, yet with different underlying mechanisms. To better understand these and to move towards neuroprotective treatment, we have established the Quebec Parkinson Network (QPN), an open-access patient registry, and data and bio-samples repository. OBJECTIVE: To present the QPN and to perform preliminary analysis of the QPN data. METHODS: A total of 1,070 consecutively recruited PD patients were included in the analysis. Demographic and clinical data were analyzed, including comparisons between males and females, PD patients with and without RBD, and stratified analyses comparing early and late-onset PD and different age groups. RESULTS: QPN patients exhibit a male:female ratio of 1.8:1, an average age-at-onset of 58.6 years, an age-at-diagnosis of 60.4 years, and average disease duration of 8.9 years. REM-sleep behavior disorder (RBD) was more common among men, and RBD was associated with other motor and non-motor symptoms including dyskinesia, fluctuations, postural hypotension and hallucinations. Older patients had significantly higher rates of constipation and cognitive impairment, and longer disease duration was associated with higher rates of dyskinesia, fluctuations, freezing of gait, falls, hallucinations and cognitive impairment. Since QPN's creation, over 60 studies and 30 publications have included patients and data from the QPN. CONCLUSIONS: The QPN cohort displays typical PD demographics and clinical features. These data are open-access upon application (http://rpq-qpn.ca/en/), and will soon include genetic, imaging and bio-samples. We encourage clinicians and researchers to perform studies using these resources.

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)0.001
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 score0.230
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.276
Teacher spread0.260 · 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

Citations67
Published2019
Admission routes3
Has abstractyes

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