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Record W4317867311 · doi:10.1111/ene.15692

White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease: results from the Ontario Neurodegenerative Diseases Research Initiative

2023· article· en· W4317867311 on OpenAlexafffundabout
Daniela Cristina Carvalho de Abreu, Frederico Pieruccini‐Faria, Yanina Sarquis‐Adamson, Alanna Black, Julia Fraser, Karen Van Ooteghem, Benjamin Cornish, David A. Grimes, Mandar Jog, Mario Masellis, Thomas Steeves, Nuwan D. Nanayakkara, Joel Ramirez, Christopher J.M. Scott, Melissa F. Holmes, Miracle Ozzoude, Courtney Berezuk, Sean Symons, Seyyed Mohammad Hassan Haddad, Stephen R. Arnott, Malcolm A. Binns, Stephen C. Strother, Derek Beaton, Kelly M. Sunderland, Athena Theyers, Brian Tan, Mojdeh Zamyadi, Brian Levine, J. B. Orange, Angela Roberts, Wendy Lou, Sujeevini Sujanthan, David P. Breen, Connie Marras, Donna Kwan, Sabrina Adamo, Alicia Peltsch, Angela K. Troyer, Sandra E. Black, Paula McLaughlin, Anthony E. Lang, William E. McIlroy, Robert Bartha

Bibliographic record

VenueEuropean Journal of Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsNova Scotia Health AuthorityThe Scarborough HospitalToronto Western HospitalPublic Health OntarioBaycrest HospitalQueen's UniversitySunnybrook HospitalOttawa HospitalHealth Sciences CentreWestern UniversityUniversity of TorontoMcGill University Health CentreUniversity of OttawaUniversity of WaterlooParkwood InstituteSt. Michael's HospitalSunnybrook Health Science CentreLawson Health Research Institute
FundersFundação de Amparo à Pesquisa do Estado de São PauloLondon Health Sciences FoundationFaculty of Health Sciences, Queen's UniversityBruyère Research InstituteCentre for Addiction and Mental Health FoundationMcMaster UniversityTemerty Family FoundationUniversity of OttawaOntario Brain InstituteGovernment of Ontario
KeywordsMedicineHyperintensityParkinson's diseaseCognitive declineDiseaseCognitionPhysical medicine and rehabilitationPsychiatryGerontologyDementiaMagnetic resonance imagingPathology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years. METHODS: Ninety-eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3-8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2-year follow-up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial-temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale. RESULTS: Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline. CONCLUSION: White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid-stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.

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)0.002
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 score0.106
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.076
GPT teacher head0.303
Teacher spread0.227 · 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

Citations23
Published2023
Admission routes3
Has abstractyes

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