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Record W3038350972 · doi:10.1177/2292550320933675

Facial Soft Tissue Augmentation With Bellafill: A Review of 4 Years of Clinical Experience in 212 Patients

2020· review· en· W3038350972 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

VenuePlastic Surgery · 2020
Typereview
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineChinSoft tissueNasolabial foldOstectomyDentistryDeformityScarsFiller (materials)Patient satisfactionSurgeryOrthodonticsAnatomy

Abstract

fetched live from OpenAlex

INTRODUCTION: Bellafill (Suneva Medical Inc) is a semipermanent injectable soft tissue filler composed of smooth and uniform polymethylmetacrylate (PMMA) microspheres suspended in a bovine collagen gel. It is a third generation PMMA filler, with more uniform shapes and sizes of the PMMA microspheres, which has been purported to decrease the incidence of granuloma formation. METHODS: We performed a retrospective review of our clinical experience from 2014 to 2017 with Bellafill as a soft tissue injectable filler in the following clinical scenarios: deep nasolabial folds, depressed facial acne scars, malar volume loss, temporal wasting, tear trough deformity, chin augmentation, angle of jaw augmentation, and lip augmentation. The primary outcome is the rate of adverse events, and the secondary outcome is subjective patient satisfaction. RESULTS: From 2014 to 2017, 842 syringes of Bellafill were administered to 212 patients, for a total of 417 procedures. Of the 417 procedures, 96 (23.0%) were for acne scars, 82 (19.7%) malar volume restorations, 65 (15.6%) nasolabial fold augmentations, 45 (10.8%) chin augmentations, 42 (10.1%) tear trough volume restorations, 28 (6.7%) temple volume restorations, 25 (6.0%) rhinoplasty touch-ups for small areas of nasal depression, 22 (5.3%) lip augmentations, and 12 (2.9%) jaw angle augmentations were performed. A range of 1 to 12 syringes were injected into each patient, over 1 to 3 sessions; 6 cases of adverse events occurred (1.4%). There were 4 cases of solitary nodules in the injection site, 1 case of lower eyelid oedema which persisted for 3 months and 1 case of lower lip oedema which resolved within hours. Patient satisfaction rates ranged from 83.3% for angle of jaw augmentation to 99.0% for improvement of acne scars. CONCLUSION: Bellafill is a safe and effective option for a semipermanent soft tissue filler, with high patient satisfaction and a good safety profile.

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)0.001
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
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 head0.120
GPT teacher head0.429
Teacher spread0.309 · 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