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Record W1778609717 · doi:10.3233/jpd-140470

Abnormal Visual Contrast Acuity in Parkinson's Disease

2015· article· en· W1778609717 on OpenAlexaff
Tanya Lin, Heather Rigby, Jennifer S. Adler, Joseph G. Hentz, Laura J. Balcer, Steven Galetta, Steve Devick, Richard Cronin, Charles H. Adler

Bibliographic record

VenueJournal of Parkinson s Disease · 2015
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsDalhousie University
FundersNational Institute of Neurological Disorders and StrokeNational Institute on Aging
KeywordsContrast (vision)Visual acuityMedicineLow visionParkinson's diseaseOphthalmologyOptometryVernier acuityDiseasePathologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Low-contrast vision is thought to be reduced in Parkinson's disease (PD). This may have a direct impact on quality of life such as driving, using tools, finding objects, and mobility in low-light condition. Low-contrast letter acuity testing has been successful in assessing low-contrast vision in multiple sclerosis. We report the use of a new iPad application to measure low-contrast acuity in patients with PD. OBJECTIVE: To evaluate low- and high-contrast letter acuity in PD patients and controls using a variable contrast acuity eye chart developed for the Apple iPad. METHODS: Thirty-two PD and 71 control subjects were studied. Subjects viewed the Variable Contrast Acuity Chart on an iPad with both eyes open at two distances (40 cm and 2 m) and at high contrast (black and white visual acuity) and 2.5% low contrast. Acuity scores for the two groups were compared. RESULTS: PD patients had significantly lower scores (indicating worse vision) for 2.5% low contrast at both distances and for high contrast at 2 m (p < 0.003) compared to controls. No significant difference was found between the two groups for high contrast at 40 cm (p = 0.12). CONCLUSIONS: Parkinson's disease patients have reduced low and high contrast acuity compared to controls. An iPad app, as used in this study, could serve as a quick screening tool to complement more formal testing of patients with PD and other neurologic disorders.

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)0.001
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 score0.026
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.045
GPT teacher head0.365
Teacher spread0.320 · 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

Citations50
Published2015
Admission routes1
Has abstractyes

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