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Vascular parkinsonism: what makes it different?

2011· review· en· W2312341779 on OpenAlexaff
Deepak Gupta, Abraham Kuruvilla

Bibliographic record

VenuePostgraduate Medical Journal · 2011
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParkinsonismMedicineLevodopaParkinson's diseaseDementiaPhysical medicine and rehabilitationPopulationDiseaseNeurosciencePathologyPsychology

Abstract

fetched live from OpenAlex

Vascular parkinsonism (VP) accounts for 2.5-5% of all cases of parkinsonism in various population based and clinical cohort studies. VP develops as a result of ischaemic cerebrovascular disease, so aetiologically it is classified as secondary parkinsonism. It has been variably referred to in the literature as arteriosclerotic parkinsonism, vascular pseudo-parkinsonism, and lower body parkinsonism. The most important consideration while making a diagnosis of VP should be to differentiate VP from Parkinson's disease (PD) because of prognostic and therapeutic implications. The salient clinical features in VP which differentiate it from PD are presentation with postural instability and falls rather than with upper limb rest tremor or bradykinesia; short shuffling parkinsonian gait in VP is accompanied by a wider base of stance and variable stride length (parkinsonian-ataxic gait), absence of festination, frequent occurrence of pyramidal signs, and early subcortical dementia. In a patient where the clinical features are suggestive of VP the clinical diagnosis can be supported by demonstration of diffuse white matter lesions and/or strategic subcortical infarcts in the MRI of the brain. The therapeutic options in VP are limited to levodopa, and a poor or non-sustained response to levodopa is another differentiating feature between VP and PD.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.075
GPT teacher head0.340
Teacher spread0.265 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations68
Published2011
Admission routes1
Has abstractyes

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