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Record W4310721662 · doi:10.1016/j.ajoc.2022.101764

Argentinian flag sign during refractive laser-assisted cataract surgery – A case report

2022· article· en· W4310721662 on OpenAlexaff
Mariam Issa, Lili Tong, Sohel Somani

Bibliographic record

VenueAmerican Journal of Ophthalmology Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsWilliam Osler Health SystemUniversity of Toronto
Fundersnot available
KeywordsCataract surgeryPhacoemulsificationMedicineComplicationOphthalmologySurgerySign (mathematics)CapsulorhexisVisual acuity

Abstract

fetched live from OpenAlex

Purpose: The Argentinian flag sign, or radial capsular tear extensions, is a rare complication when performing capsulorhexis during cataract surgery. Identifying and managing this complication early is important to prevent the tear from propagating around the periphery leading to posterior capsular rupture or vitreous loss. Observations: The Argentinian flag sign was previously reported in a case of femtosecond laser-assisted cataract surgery (FLACS). However, our report presents the first case after FLACS using the Catalys™ Precision Laser System, a platform which has been associated with a larger percentage of complete capsulotomies when compared to other platforms. Radial extensions of the capsular tear were observed in a 27-year-old male patient with an intumescent cataract in left eye. The complication was managed by manually redirecting and completing the radial extension flaps, along with delicate phacoemulsification and manual cutting of capsular edge in areas with significant capsular-IOL overlap. Conclusions and importance: Our case report highlights that despite the Catalys™ Precision Laser System success rates, radial tears may occur, especially in highly pressurized intumescent cataract. Therefore, surgeons must be prepared to optimize the surgical techniques to prevent the occurrence of this complication, as well as identify and manage it when it presents.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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