Current Concepts in the Use of Small-Particle Hyaluronic Acid
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.
Bibliographic record
Abstract
BACKGROUND: Soft-tissue augmentation with hyaluronic acid (HA) fillers has become one of the most popular cosmetic procedures performed. HA fillers represent safe and commonly used fillers. Several different HA fillers are available. The differences lie in the manufacturing process, allowing for tailored uses. A small-particle HA with lidocaine (SP-HAL; Restylane Silk; Galderma, Uppsala, Sweden) was approved by the US Food and Drug Administration in June 2014 but has been available for many years in Canada as Restylane Fine Lines and in Europe as Restylane Vital. METHODS: Relevant articles were reviewed relating to the composition, effectiveness, and safety of SP-HAL. We also discuss the author's extensive clinical experience in the use of this product in Canada. RESULTS: SP-HAL has demonstrated proven benefits for lip fullness, augmentation, and treatment of perioral rhytides. Although off-label in the United States, SP-HAL is also well suited for the treatment of superficial fine lines, including periorbital, forehead, marionette, and smile lines. In addition, it has also been used in the tear trough region. A novel application for SP-HAL includes use as a skinbooster with intradermal micropuncture. In this technique, small aliquots of product are injected so as to gradually rejuvenate the skin in areas such as the face and hands. Side effects of SP-HAL were generally transient and mild. The most common side effects were swelling, tenderness, bruising, pain, and redness. CONCLUSION: SP-HAL is an effective and safe HA filler with varied clinical uses.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it