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Record W2402565715 · doi:10.1097/ico.0b013e318038d2ff

Five-Millimeter-Incision Deep Lamellar Endothelial Keratoplasty

2007· article· en· W2402565715 on OpenAlexaff
Natasha Yepes, Fanny Segev, Michael Hyams, Penny McAllum, Allan R. Slomovic, David S. Rootman

Bibliographic record

VenueCornea · 2007
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsVisual acuityMedicineAstigmatismOphthalmologySurgeryOptics

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate visual acuity, topography, and endothelial cell density 1 year after deep lamellar endothelial keratoplasty (DLEK) for endothelial dysfunction. METHODS: This is a prospective, comparative, interventional case series. Thirty-five eyes of 35 patients who had undergone DLEK with a 5-mm incision and had a minimum of 1-year follow-up were included. Main outcome measures were best spectacle-corrected visual acuity (BSCVA), uncorrected visual acuity (UCVA), astigmatism, topographic regularity and symmetry, and endothelial cell density. RESULTS: : One year postoperatively, BSCVA was 0.33 +/- 0.12 (mean, 20/60; range, 20/40-20/400) compared with 0.15 +/- 0.15 preoperatively (mean, 20/200; range, 20/70-20/800). Six patients did not reach an acceptable visual acuity and were not included in the mean BSCVA, 2 had a primary failure, and the others had preexisting glaucoma or macular disease. Spherical equivalent was -0.04 +/- 1.2 D, refractive astigmatism was 1.76 +/- 1.69 D, surface regularity index was 0.97 +/- 0.54, and surface asymmetry index was 1.25 +/- 0.78 1 year after surgery. Mean endothelial cell count from the donor was 2904 +/- 559 (range, 4694-2111) and 1 year after surgery was 1595 +/- 662 (range, 702-3040), equating to 45% cell loss (range, 15%-77%). CONCLUSIONS: DLEK is a newer method to replace the endothelium in patients with Fuchs dystrophy. Results showed minimal astigmatism, good topographic parameters, and acceptable visual acuity. Endothelial cell loss at 1 year was significant.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.258
Teacher spread0.245 · 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 designOther design
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

Citations12
Published2007
Admission routes1
Has abstractyes

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