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Record W2921836821 · doi:10.5539/gjhs.v11n4p85

Congenital Cataract Surgery: Our Four Years’ Experience in Prince Hamza Hospital (Amman-Jordan)

2019· article· en· W2921836821 on OpenAlexvenueno aff
Raed Shatnawi, Mohammad Abu‐Ain, Motasem Al-Latayfeh, Basel Turki Baarah

Bibliographic record

VenueGlobal Journal of Health Science · 2019
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntraocular lensPseudophakiaOphthalmologyIntraocular lensesCataract surgeryVisual acuityIncidence (geometry)Visual rehabilitationRetrospective cohort studyOptometrySurgery

Abstract

fetched live from OpenAlex

PURPOSE: The study has examined the problems encountered during management of cataract surgery during clinical practice within a developing country. METHODS: A retrospective study was conducted by recruiting patients with the diagnosis of congenital cataract operated between 2011 and 2014. Intraocular lens was implanted, when the corneal diameter was 10 mm or more, which approximately corresponded to the capsular bag diameter, regardless of the patients’ age. RESULTS: The results showed that 13 were aphakic and none of them developed visual axis opacification. Eleven out of the 49 pseudophakic patients needed 2 or more surgeries to clear visual axis opacification; whereas, 25 out of 49 pseudophakic patients received hydrophobic intraocular lens. However, 3 of them (12%) developed visual axis opacification. The remaining 24 patients received hydrophilic intraocular lens, where 8 of them (33%) developed visual axis opacification. There was increased incidence of visual axis opacification as a result of pseudophakia that required a second surgery, which delayed their visual rehabilitation. CONCLUSION: Hydrophobic intraocular lenses are better used because of their lower risk to induce visual axis opacification.

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 score0.015
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.334
Teacher spread0.304 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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