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The use of prisms for vision rehabilitation after macular function loss: an evidence‐based review

2012· review· en· W2048160905 on OpenAlexaff
Samuel N. Markowitz, Sophia V. Reyes, Sheng Li

Bibliographic record

VenueActa Ophthalmologica · 2012
Typereview
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsVisual acuityMedicineRehabilitationOptometryVision rehabilitationOphthalmologyPhysical therapy

Abstract

fetched live from OpenAlex

To determine the efficacy of prisms used for redirection of incoming images towards the peripheral retina in cases with macular function loss. Meta-analysis of published work reporting outcomes from interventions using prisms was performed. The primary outcome measure selected for analysis was visual acuity (VA) used for viewing distance targets. Pooled data from 449 cases where prisms were prescribed for wearing in distance glasses were analysed. Visual acuity was better after using prisms (1.05 versus 0.89 logMAR units, p < 0.044). Mean effect size for improving VA was 79 bigger than the effect size calculated for the control group (0.158 versus 0.002). Most patients (76%) reported compliance with the therapy and also reported other benefits directly derived from the realized VA improvement. Published studies collectively offer positive evidence in support of using prisms for low vision rehabilitation after macular function loss. Further research is required to reach definitive binding conclusions.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.268
GPT teacher head0.463
Teacher spread0.195 · 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.

Study designNot applicable
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

Citations17
Published2012
Admission routes1
Has abstractyes

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