MétaCan
Menu
Back to cohort
Record W2388293516 · doi:10.1097/icb.0000000000000333

A SECOND CASE OF BILATERAL RHEGMATOGENOUS RETINAL DETACHMENTS REPAIRED WITH SIMULTANEOUS BILATERAL PNEUMATIC RETINOPEXY

2016· article· en· W2388293516 on OpenAlexaff
Uriel Rubin, C. de Jager, Moayed Zakour, J. Gonder

Bibliographic record

VenueRetinal Cases & Brief Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsHotel Dieu HospitalQueen's University
Fundersnot available
KeywordsMedicineRetinal TearRetinal detachmentRetinalTearsOphthalmologySurgeryPresentation (obstetrics)

Abstract

fetched live from OpenAlex

BACKGROUND/PURPOSE: To present a case of a patient with simultaneous bilateral retinal detachments treated successfully with bilateral pneumatic retinopexy. STUDY DESIGN: Case report. RESULTS: This is a case of an otherwise healthy 49-year-old woman with no remarkable ocular history that presented with simultaneous phakic superior bilateral rhegmatogenous retinal detachments. Treatment on the day of presentation included laser retinopexy of the inferior lattice degeneration in the left eye and bilateral intravitreal injection of 0.4 cc of 100% C3F8 gas preceded by topical anesthesia. After 48 hours, both retinas were completely reattached, and bilateral laser retinopexy was performed to the superior tears. DISCUSSION: After a review of the literature, the authors could find only two reported cases of simultaneous bilateral retinal detachments treated successfully with pneumatic retinopexy. This is not only a cost-effective procedure but also allows treatment when there is no immediate operating room availability or a when a quick referral for surgery is not possible.

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)0.000
metaresearch head score (Gemma)0.003
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueRetinal Cases & Brief ReportsSame topicRetinal and Macular SurgeryFrench-language works237,207