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Record W4234978300 · doi:10.1177/2513826x211028926

Polyurethane-Coated Implants for Prevention of Double-Bubble Effect in Breast Augmentation

2021· article· en· W4234978300 on OpenAlexvenueno aff
Vitali Bagirov

Bibliographic record

VenuePlastic Surgery Case Studies · 2021
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsBreast augmentationMedicineComplicationSurgeryBubbleImplantPolyurethaneMammaplastyBreast surgeryBreast cancerInternal medicineMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Breast augmentation is the most frequently performed cosmetic surgery in the United States, with approximately 279,000 patients every year. The so-called double-bubble effect (DBE) is a common complication in breast augmentation. This complication is characterized by folds running along the lower pole of the breast, forming distinct bubble-like protrusions above and below the fold. Factors that increase the risk of DBE include bulbous breasts and a large native breast volume. There is evidence that polyurethane-coated (PU) implants may help to reduce the risk of DBE. We describe here the case of a 47-year old patient for whom DBE has recurred in each of 4 tandem breast surgeries. PU implants ultimately appeared to prevent the DBE, leading to an aesthetically satisfying treatment result for the patient. This case adds weigh to the growing body of evidence that supports the use of polyurethane implants to prevent DBE.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.047
GPT teacher head0.332
Teacher spread0.285 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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