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Record W2530282783 · doi:10.1159/000449124

High Rate of Early Posterior Capsule Opacification following Femtosecond Laser-Assisted Cataract Surgery

2016· article· en· W2530282783 on OpenAlexaff
Benjamin Rostami, Jack J. Tian, Nicholas Jackson, Rustum Karanjia, Kenneth Lu

Bibliographic record

VenueCase Reports in Ophthalmology · 2016
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsUniversity of Ottawa
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineFemtosecondCapsuleCataract surgeryPosterior capsule opacificationSurgeryOphthalmologyLaserPhacoemulsificationOpticsVisual acuity

Abstract

fetched live from OpenAlex

PURPOSE: To compare the rates of rapid posterior capsule opacification (PCO) formation in the first 3 months following femtosecond laser-assisted cataract surgery (FLACS) to manual anterior capsulorhexis. METHODS: Retrospective review of 29 cases of FLACS, comparing the rates of PCO in the first 3 months following surgery to 50 consecutive cases of manual anterior capsulorhexis. RESULTS: Seven of the 29 FLACS cases developed PCO requiring capsulotomy at 3 months, while none of the control cases required a capsulotomy over the same time period (p < 0.05). CONCLUSION: There is an increased incidence of early-onset PCO following the use of femtosecond laser in cataract surgery that is otherwise unfounded in manual capsulorhexis. This suggests that the use of a femtosecond laser could increase the risk of this novel postoperative complication.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.294
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations24
Published2016
Admission routes1
Has abstractyes

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