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Record W4283393497 · doi:10.1080/2576117x.2022.2083745

The Impact of Occlusion Therapy on Amblyopia Success Outcomes

2022· article· en· W4283393497 on OpenAlexaff
Emily White, Leah Walsh

Bibliographic record

VenueJournal of Binocular Vision and Ocular Motility · 2022
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsMedicineOcclusionVisual acuityCompliance (psychology)Retrospective cohort studyOutcome (game theory)OphthalmologySurgeryPsychology

Abstract

fetched live from OpenAlex

PURPOSE: The recommended amount of occlusion therapy and amblyopia treatment success rates remains controversial. This study explores rates of occlusion therapy success and attempts to address limitations of previous literature. METHODS: A retrospective chart review was performed on patients with occlusion therapy outcomes from 2012 to 2019. Equal visual acuity (VA) or stable VA for three consecutive clinical visits, despite reported good compliance defined outcome VA. RESULTS: Results showed 90.3% of subjects obtained outcome distance VA of 0.3logMAR, 76% ≥0.3logMAR, 35% ≥0.2logMAR, and 6% ≥0.1logMAR in the amblyopic eye following treatment. Sixty-nine percent of the study population obtained equal vision following occlusion therapy. Only initial VA (amblyopic eye) and initial interocular visual optotype difference at distance predicted post-treatment success. CONCLUSION: These results support the conclusion that occlusion therapy, both PTO and FTO, can be effective in treating amblyopia when good compliance is maintained based on parental reports of compliance. Additionally, as VA gain was higher than in previous literature, it is important to continue treatment until VA is equal or three consecutive cycles of stable VA are obtained to ensure maximum VA improvement.

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)0.000
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 score0.009
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.399
Teacher spread0.373 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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