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Record W2316608377 · doi:10.1093/asj/sjv262

Misconceptions of Capsular Contracture, Operative Times, and Complications in the Transaxillary Breast Augmentation Literature

2016· letter· en· W2316608377 on OpenAlexaff
Benjamin M. Gelfant

Bibliographic record

VenueAesthetic Surgery Journal · 2016
Typeletter
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsGeoscience BC
Fundersnot available
KeywordsMedicineCapsular contractureBreast augmentationSurgeryContractureMammaplastyCosmetic TechniquesGeneral surgeryBreast reconstructionBreast cancerInternal medicine

Abstract

fetched live from OpenAlex

Another article appears, this time with “level 3” evidence, again professing endoscopic-assisted transaxillary breast augmentation isn't a good procedure. 1 In this study it is purported to have increased operating time, on average, by nearly an hour per procedure. The authors appear to have limited experience with the procedure (17 cases between June 2011 and March 2013, or less than one per month). As a surgeon with more than 18 years of experience with this operation, I would ask, “What were they doing?” Similarly, a study we have seen and heard quoted with some frequency (level 4 evidence) concludes “The risk of CC [capsular contracture] is significantly higher with transaxillary incisions than with periareolar or inframammary incisions.” 2 The transaxillary approach again gets a “black eye” from authors who have what appears to be little experience (47 breasts over six years). In our personal experience, without any hint of rushing, the operation routinely takes between 35 and 40 minutes, from skin to skin (and not occasionally, less). With smooth-shelled, gel-filled implants, this is facilitated with an insertion funnel. (We have no experience with placement of textured devices via the transaxillary approach.) The operation is gentle, nearly bloodless, and complications are rare; in over 2500 cases since 1997 there have been seven hematomas and only one peri-prosthetic infection requiring explantation (16 years ago). Contracture rates are also very low, in the range of 1% long term. The power of statistics today is such that a higher level of evidence will accord a paper longevity, citations, and eventually canonization. The adage “Lies, damned lies, and statistics” 3 can be negated in this environment by evidence-based medicine. But clinical experience will hopefully allow us to see the flaws and for reason to prevail. The author holds shares in Ideal Implant, Inc. (Dallas, TX) and Johnson and Johnson, Inc. (New Brunswick, NJ). The author received no financial support for the research, authorship, and publication of this article.

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)0.015
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.985
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.090
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0020.005
Scholarly communication0.0040.005
Open science0.0020.001
Research integrity0.0050.005
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 head0.015
GPT teacher head0.262
Teacher spread0.246 · 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.

Study designSystematic review
DomainReporting
GenreCommentary

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

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