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Record W2123245922 · doi:10.5539/gjhs.v8n5p205

A Retrospective Study of Causes of Low Vision in Saud Arabia, A Case of Eye World Medical Complex in Riyadh

2015· article· en· W2123245922 on OpenAlexvenueno aff
Abdullah M. Alotaibi

Bibliographic record

VenueGlobal Journal of Health Science · 2015
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLow visionMedicineOptometryVisual acuityMacular degenerationDiabetic retinopathyBlindnessRetinitis pigmentosaOphthalmologyDiabetes mellitusRetinal

Abstract

fetched live from OpenAlex

Vision is the ability of seeing with a definite understanding of features, color and contrast, and to distinguish between objects visually. In the year 1999, the World Health Organization (WHO) and the International Agency for the Prevention of Blindness formulated a worldwide project for the eradication of preventable loss of sight with the subject of "Vision 2020: the Right to Sight". This global program aims to eradicate preventable loss of sight by the year 2020. This study was conducted to determine the main causes of low vision in Saudi Arabia and also to assess their visual improvement after using low vision aids (LVD).The study is a retrospective study and was conducted in low vision clinic at Eye World Medical Complex in Riyadh, Saudi Arabia. The file medical record of 280 patients attending low vision clinics from February 2008 to June 2010 was included. A data sheet was filled which include: age, gender, cause of low vision, unassisted visual acuity for long distances and short distances, low vision devices needed for long distances and short distances that provides best visual acuity. The result shows that the main cause of low vision was Optic atrophy (28.9%). Retinitis pigmentosa was the second cause of low vision, accounting for 73 patients (26%) followed by Diabetic retinopathy and Macular degeneration with 44 patients (15.7%) and 16 patients (5.7%) respectively. Inter family marriage could be one of the main causes of low vision. Public awareness should be embarked on for enlightenment on ocular diseases result in consanguineous marriage. Also, it is an important issue to start establishing low vision clinics in order to improve the situation.

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)0.005
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 score0.020
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.085
GPT teacher head0.486
Teacher spread0.401 · 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

Citations27
Published2015
Admission routes1
Has abstractyes

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