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Record W2900883020 · doi:10.2147/ccid.s180904

A 10-point plan for avoiding hyaluronic acid dermal filler-related complications during facial aesthetic procedures and algorithms for management

2018· article· en· W2900883020 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Cosmetic and Investigational Dermatology · 2018
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsCanadian Institute of Mining, Metallurgy and Petroleum
FundersUniversiteit Stellenbosch
KeywordsContext (archaeology)MedicineProduct (mathematics)DocumentationFiller (materials)Plan (archaeology)Operations managementRisk analysis (engineering)SurgeryAlgorithmComputer scienceEngineering

Abstract

fetched live from OpenAlex

The recent rapid growth in dermal filler use, in conjunction with inadequate product and injector control, has heralded a concerning increase in filler complications. The 10-point plan has been developed to minimize complications through careful preconsideration of causative factors, categorized as patient, product, and procedure related. Patient-related factors include history, which involves a preprocedural consultation with careful elucidation of skin conditions, systemic disease, medications, and previous cosmetic procedures. Other exclusion criteria include autoimmune diseases and multiple allergies. The temporal proximity of dental or routine medical procedures is discouraged. Insightful patient assessment, with the consideration of ethnicity, gender, and generational needs, is of paramount importance. Specified informed consent is vital due to the concerning increase in vascular complications, which carry the risk for skin compromise and loss of vision. Informed consent should be signed for both adverse events and their treatment. Product-related factors include reversibility, which is a powerful advantage when using hyaluronic acid (HA) products. Complications from nonreversible or minimally degradable products, especially when layered over vital structures, are more difficult to control. Product characteristics such as HA concentration and proprietary cross-linking should be understood in the context of ideal depth, placement, and expected duration. Product layering over late or minimally degradable fillers is discouraged, while layering of HA of over the same brand, or even across brands, seems to be feasible. Procedural factors such as photographic documentation, procedural planning, aseptic technique, and anatomical and technical knowledge are of pivotal importance. A final section is dedicated to algorithms and protocols for the management and treatment of complications such as hypersensitivity, vascular events, infection, and late-onset nodules. The 10-point plan is a systematic, effective strategy aimed at reducing the risk of dermal filler complications.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.074
GPT teacher head0.362
Teacher spread0.288 · 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