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Record W2417813387 · doi:10.1097/dss.0000000000000541

Volumizing Hyaluronic Acid Filler for Midface Volume Deficit

2015· article· en· W2417813387 on OpenAlexaff
Leslie Baumann, Rhoda S. Narins, Kenneth Beer, Arthur Swift, Kimberly J. Butterwick, Julius W. Few, Adrienne Drinkwater, Diane K. Murphy

Bibliographic record

VenueDermatologic Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsCanadian Institute of Mining, Metallurgy and Petroleum
Fundersnot available
KeywordsMedicinePatient satisfactionHyaluronic acidSurgeryPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Juvéderm Voluma XC (VYC-20L; hyaluronic acid gel) is approved in the United States for correction of age-related midface volume deficit (MVD). OBJECTIVE: Assess safety and effectiveness of VYC-20L after repeat treatment. METHODS: Subjects with MVD underwent optional repeat treatment 12 to 24 months after initial treatment if correction was lost or at 24 months regardless of loss of correction (n = 167). Investigators rated outcomes on the Mid-Face Volume Deficit Scale (MFVDS) and the Global Aesthetic Improvement Scale (GAIS). Subject-rated outcomes were the GAIS, overall satisfaction with facial appearance, achievement of treatment goal, and Self-Perception of Age questionnaire. Subjects recorded treatment-site responses in 30-day diaries. RESULTS: Mean injection volume for repeat treatment (3.13 mL) was approximately half the mean total injection volume for initial/touch-up treatment (6.8 mL). After repeat treatment, effectiveness was demonstrated on all investigator-rated and subject-rated measures, consistent with results observed after initial treatment. The percentage of subjects improving by ≥1 point on the MFVDS was 82.8% and 91.1% at 6 and 12 months after repeat treatment, respectively. The incidence, severity, and duration of common treatment-site responses were lower after repeat versus initial treatment. CONCLUSION: Repeat treatment with VYC-20L was well tolerated and resulted in high levels of effectiveness and subject satisfaction.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.179
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.106
GPT teacher head0.312
Teacher spread0.206 · 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 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

Citations19
Published2015
Admission routes1
Has abstractyes

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