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Record W3095900011 · doi:10.14730/aaps.2020.02194

Sickle-shaped transposition flap oriented along relaxed skin tension lines for lower eyelid reconstruction

2020· article· en· W3095900011 on OpenAlexaboutno aff
Tae Hyeon Lee, Hyun Joon Seo, Seong Oh Park

Bibliographic record

VenueArchives of Aesthetic Plastic Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEctropionEyelidSurgeryTransposition (logic)Patient satisfactionRetrospective cohort study

Abstract

fetched live from OpenAlex

The reconstruction of defects in the lower eyelid region is prone to complications such as ectropion and epiphora. This area is also aesthetically important; therefore, operations should be carried out with caution. We introduce a simple and easy surgical approach for the repair of small to moderate-sized lower eyelid defects. Methods A retrospective chart review was performed for all patients who underwent lower eyelid defect reconstruction using a sickle-shaped transposition flap in 2018 or 2019. Photographs were taken at each visit, and the Vancouver Scar Scale was used to evaluate residual marks every 3 months for 1 year. Patients reported their subjective satisfaction levels on a visual analogue scale that ranged from 0 to 10. Results A total of nine patients were included. No flap necrosis, ectropion, epiphora, or other complications were observed. Among the eight patients with skin cancer, no recurrence was noted during the follow-up period. The mean Vancouver Scar Scale scores were 5.500.99 at 3 months postoperatively, 4.610.85 at 6 months postoperatively, 3.050.80 at 9 months postoperatively, and 1.110.58 at 12 months postoperatively. The mean overall patient satisfaction rating was 9.110.78 (as rated on the visual analogue scale). Conclusions In the reconstruction of lower eyelid defects, the sickle-shaped transposition flap could be a simple, fast, and aesthetically favorable surgical option.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.020
GPT teacher head0.244
Teacher spread0.224 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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