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Record W3044260228 · doi:10.1097/sap.0000000000002498

Comments on “Defining Plastic, Reconstructive, Aesthetic, and Cosmetic Surgeries: What Can Get Lost and Found in Translation”

2020· letter· en· W3044260228 on OpenAlexaff
Patrick Tansley, Darryl Hodgkinson, Tim Brown

Bibliographic record

VenueAnnals of Plastic Surgery · 2020
Typeletter
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsScience North
Fundersnot available
KeywordsMedicinePlastic surgeryReconstructive surgerySpecialtySurgeryCraftGeneral surgeryFamily medicineVisual arts

Abstract

fetched live from OpenAlex

To the Editor: We read with interest the Editorial by Wei, Gu, and Li regarding the definitions of plastic, reconstructive, aesthetic, and cosmetic surgeries.1 The Oxford English Dictionary has the following descriptors: *Cosmetic, adj. Of surgery: improving or modifying the appearance. Of prosthetic devices: recreating or imitating the normal appearance. *Aesthetic, adj. Designating surgery or dentistry intended to restore or improve a person's appearance; of or relating to such treatment. Although there is a semantic difference between the words “aesthetic” and “cosmetic,” for most practical purposes, there is none, except perhaps in public (consumer) perception.2 From the content of the editorial along with its publishing Journal, there is a presumption that a single surgical craft group (plastic surgery) is uniquely trained to deliver cosmetic surgical procedures. The United Kingdom General Medical Council (GMC) and its counterpart in Australia, the Australian Medical Council (AMC) have recognized that this is not the case. The GMC recently warned that the possession of qualifications in a given specialty field does not imply expertise in cosmetic surgery, whereas in 2018, the AMC reported that plastic surgeons trained by the Royal Australasian College of Surgeons had a “deficit” in their experience of aesthetic surgery and a “gap in this area of practice.”3 Across the western world, plastic surgical training is almost exclusively undertaken in public hospitals and is reconstructive in nature, such as hand surgery, trauma, burn, and cancer care. Typically, this publicly funded undertaking does not incorporate training in cosmetic surgery, which is almost exclusively undertaken and independently funded in the private sector. It is only through diligence of the individual plastic surgeon who seeks additional specific training that competence in aesthetic/cosmetic surgery can be achieved. Such specific training typically comprises dedicated academic education in conjunction with practical aesthetic surgical fellowships, over and above that offered by standard publicly funded training schemes. The existence, quality, uptake, and outcomes of such training seem variable at best.4–6 In addition, there is no agreed method of accreditation for medical practitioners performing cosmetic surgical procedures. The field is not yet recognized as a specialty, and currently, any medical practitioner may call himself or herself a “cosmetic surgeon.” As a result, there has been an expansion of clinics offering cosmetic surgical procedures performed by nonsurgical entrepreneurs. As a consequence, patients and regulators find it difficult to distinguish between surgeons competent in cosmetic surgery compared with those who do not have appropriate knowledge, training, and skills to undertake and deliver high-quality cosmetic surgical outcomes. The situation has been exploited and worsened by various surgical craft-groups producing misleading claims that “they alone” are properly trained in cosmetic surgery, despite the diametrically opposed findings of the GMC and AMC. Such claims are not credible in the absence of completion of specific, comprehensive dedicated education, and training in cosmetic surgery. Australia has its own Australasian College of Cosmetic Surgery, established in 1999 as a not-for-profit, multidisciplinary fellowship-based body, which has trained and qualified surgeons from multiple subspecialties, including general surgeons, plastic surgeons, maxillofacial surgeons, ear nose and throat surgeons, ophthalmologists, and other doctors who practice cosmetic medicine and surgery.7 After 2 years of specific cosmetic surgery training, trainees face written and oral examinations and if successful, graduate with fellowship specifically in cosmetic surgery and with the requirement to recertify in cosmetic surgery annually thereafter. Although the authors make the statement that “Nowadays, cosmetic surgery is acknowledged as a subbranch of plastic surgery,” Australian legislation stipulates that a medical speciality can only be recognized based on a “burden of disease.” Cosmetic surgical procedures are not undertaken on such basis. In light of the enormous global demand for them, the time has come to rethink contemporary recognition of cosmetic surgery as a specialty in its own right, based on a “burden of demand.” Such recognition would incorporate a multitude of natural professional safeguards to patients. An initiative has been proposed in Australia to establish a competency-based, national accreditation system for all medically qualified providers of cosmetic surgical procedures that would favor no particular craft group but provide better and safer outcomes. Its purpose is to remove confusion for consumers, allowing them to make informed and potentially safer choices. “Who performs what” should now be relegated to a position of secondary importance in relation to the partisan viewpoint of traditional surgical groups. For the sake of the patient, what really counts is competency in cosmetic surgery and in its execution. Acceptance of independent speciality recognition and competency-based accreditation are the key first steps to provide a better standard in cosmetic surgery. Patrick Tansley, MD, FACCS, FRCS (Plast)Darryl Hodgkinson, FACCS, FRCS (C)Tim Brown, MA, FACCS, FRACS, FRCS (Plast) North East Plastic Surgery Melbourne Victoria, Australia [email protected]

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.313
Teacher spread0.213 · 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 designNot applicable
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

Citations2
Published2020
Admission routes1
Has abstractyes

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