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Record W1998526144 · doi:10.1097/ico.0b013e3181d4f91a

Impression Cytologic Analysis After Corneal Collagen Cross-Linking Using Riboflavin and Ultraviolet- A Light in the Treatment of Keratoconus

2010· article· en· W1998526144 on OpenAlexaff
Adimara da Candelária Renesto, Jeison de Nadai Barros, Mauro Campos

Bibliographic record

VenueCornea · 2010
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsKeratoconusConjunctivaRiboflavinCorneal collagen cross-linkingCorneaOphthalmologyGoblet cellMedicineCytologySignificant differencePathologyEpitheliumInternal medicineChemistry

Abstract

fetched live from OpenAlex

PURPOSE: To report impression cytologic (IC) results after corneal cross-linking (CXL) using riboflavin and ultraviolet-A light in the treatment of keratoconus and compare the data with those from a group of subjects with the same disease. METHODS: Forty eyes were distributed into 2 groups: patients in group 1 underwent CXL, whereas patients in group 2 received riboflavin 0.1% eyedrops for 1 month of topical use. IC specimens were obtained from all eyes before treatment and 1 and 3 months after treatment. RESULTS: Patients in group 1 showed a decrease in goblet cell density on the superior conjunctiva after CXL (P = 0.008) but no difference on the temporal conjunctiva or in the cornea. Patients in group 2 demonstrated improvement in cell-to-cell contact of epithelial cells and reduced keratinization on the temporal conjunctiva after treatment (P = 0.003 and P = 0.034, respectively) but no changes on the superior conjunctiva or in the cornea. Fisher exact test comparison of IC total scores after treatment revealed no difference between groups. CONCLUSIONS: Despite changes in goblet cell density after corneal CXL in the superior conjunctiva and an improvement in the morphology of epithelial cells after the use of riboflavin eyedrops, comparison of total IC scores showed no difference between groups.

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)0.000
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 score0.030
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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