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Record W4246015688 · doi:10.1177/2513826x1600200301

Complications of Polyacrylamide Hydrogel Augmentation Mammoplasty: A Case Report and Review of the Literature

2016· article· en· W4246015688 on OpenAlexaffvenue
Jessica Winter, Sarah Shiga, Avinash Islur

Bibliographic record

VenuePlastic Surgery Case Studies · 2016
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineBreast augmentationSurgeryPresentation (obstetrics)Case presentationMammoplastyAugmentation MammoplastyBreast reconstructionPopulationDebridement (dental)Breast cancerImplantCancer

Abstract

fetched live from OpenAlex

The use of Polyacrylamide hydrogel (PAAG) as an injectable filler for breast augmentation has fallen out of popularity since its first use in the 1980s, but has produced an increasing patient population presenting with complications related to PAAG injections. PAAG use was popularized most notably in China, Russia and Iran. However, given immigration trends and medical tourism, PAAG-related complications have become increasingly more common in North America. These complications can be difficult to treat, often necessitating complex surgery that includes gel removal, debridement procedures and, often, breast reconstruction. Approaches to surgical treatment and subsequent breast reconstruction are not universally defined primarily because of the limited knowledge about this group of patients. The present article presents the option of autologous free flap reconstruction for a patient with extensive muscular involvement, and aims to summarize complications and risks associated with PAAG through a case presentation and literature review.

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)0.002
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.005
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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 routes2
Has abstractyes

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