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Record W2412575034 · doi:10.5693/djo.01.2015.10.001

Retinal detachments after Boston Keratoprosthesis: incidence, predisposing factors, and visual outcomes

2015· article· en· W2412575034 on OpenAlexaff
Maria Stephanie R. Jardeleza, Marc‐André Rhéaume, James Chodosh, Anne Marie Lane, Claes H. Dohlman

Bibliographic record

VenueDigital Journal of Ophthalmology · 2015
Typearticle
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIncidence (geometry)MedicineKeratoprosthesisOphthalmologyRetinalOptometryVisual acuityOptics

Abstract

fetched live from OpenAlex

PURPOSE: To determine the rates, predisposing factors, and visual outcomes of retinal detachment (RD) after Boston Keratoprosthesis (KPro) implantation. METHODS: In this noncomparative, interventional case series, the medical records of 170 patients (205 eyes) who underwent Boston type 1 and type 2 KPro implantation at the Massachusetts Eye and Ear Infirmary between April 1993 and June 2009 were retrospectively reviewed. Incidence and annual rates of RD were calculated, and the roles of possible predictive factors for RD after KPro were investigated. Main outcome measures were rates of and risk factors for RD, visual acuity after RD, and surgical outcomes after repair. RESULTS: Sterile vitritis and autoimmune systemic disease significantly predisposed patients to RD after KPro placement. Of patients who developed RD after implantation, 50% progressed to visual acuity of no light perception despite surgical repair. CONCLUSIONS: Inflammation plays a major role in RD development after KPro implantation. Patients with predisposing factors should be advised of the high rates of RD and comanaged with a vitreoretinal specialist.

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 score0.039
Threshold uncertainty score0.477

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)0.0000.000

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 head0.030
GPT teacher head0.316
Teacher spread0.286 · 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

Citations30
Published2015
Admission routes1
Has abstractyes

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