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Record W1937033430 · doi:10.1001/jamaneurol.2015.0703

New Clinical Subtypes of Parkinson Disease and Their Longitudinal Progression

2015· article· en· W1937033430 on OpenAlexaffabout
Seyed‐Mohammad Fereshtehnejad, Silvia Ríos Romenets, Julius Anang, Véronique Latreille, Jean‐François Gagnon, Ronald B. Postuma

Bibliographic record

VenueJAMA Neurology · 2015
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversité du Québec à MontréalHôpital du Sacré-Cœur de MontréalMontreal General HospitalMcGill University
Fundersnot available
KeywordsMedicineParkinson's diseaseCohortREM sleep behavior disorderDiseaseDepression (economics)Rating scaleAnxietyNeurocognitiveMovement disordersProspective cohort studyNatural history studyPhysical medicine and rehabilitationInternal medicinePsychologyCognitionPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

IMPORTANCE: There is increasing evidence that Parkinson disease (PD) is heterogeneous in its clinical presentation and prognosis. Defining subtypes of PD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies. OBJECTIVES: To identify clinical subtypes of PD, compare the prognosis and progression rate between PD phenotypes, and compare the ability to predict prognosis in our subtypes and those from previously published clustering solutions. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study. The cohorts were from 2 movement disorders clinics in Montreal, Quebec, Canada (patients were enrolled during the period from 2005 to 2013). A total of 113 patients with idiopathic PD were enrolled. A comprehensive spectrum of motor and nonmotor features (motor severity, motor complications, motor subtypes, quantitative motor tests, autonomic and psychiatric manifestations, olfaction, color vision, sleep parameters, and neurocognitive testing) were assessed at baseline. After a mean follow-up time of 4.5 years, 76 patients were reassessed. In addition to reanalysis of baseline variables, a global composite outcome was created by merging standardized scores for motor symptoms, motor signs, cognitive function, and other nonmotor manifestations. MAIN OUTCOMES AND MEASURES: Changes in the quintiles of the global composite outcome and its components were compared between different subtypes. RESULTS: The best cluster solution found was based on orthostatic hypotension, mild cognitive impairment, rapid eye movement sleep behavior disorder (RBD), depression, anxiety, and Unified Parkinson's Disease Rating Scale Part II and Part III scores at baseline. Three subtypes were defined as mainly motor/slow progression, diffuse/malignant, and intermediate. Despite similar age and disease duration, patients with the diffuse/malignant phenotype were more likely to have mild cognitive impairment, orthostatic hypotension, and RBD at baseline, and at prospective follow-up, they showed a more rapid progression in cognition (odds ratio [OR], 8.7 [95% CI, 4.0-18.7]; P < .001), other nonmotor symptoms (OR, 10.0 [95% CI, 4.3-23.2]; P < .001), motor signs (OR, 4.1 [95% CI, 1.8-9.1]; P = .001), motor symptoms (OR, 2.9 [95% CI, 1.3-6.2]; P < .01), and the global composite outcome (OR, 8.0 [95% CI, 3.7-17.7]; P < .001). CONCLUSIONS AND RELEVANCE: It is recommended to screen patients with PD for mild cognitive impairment, orthostatic hypotension, and RBD even at baseline visits. These nonmotor features identify a diffuse/malignant subgroup of patients with PD for whom the most rapid progression rate could be expected.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.341
Teacher spread0.286 · 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".

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Citations607
Published2015
Admission routes2
Has abstractyes

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