Safety Data of Injectable Nonanimal Stabilized Hyaluronic Acid Gel for Soft Tissue Augmentation
Bibliographic record
Abstract
BACKGROUND: Nonanimal hyaluronic acid gel was recently developed for soft tissue augmentation and volume expansion and has been shown to offer several advantages in comparison to other augmentation materials. There are rare reports of adverse events believed to be secondary to trace amounts of proteins in the hyaluronic acid raw material. OBJECTIVE: To determine the safety profile of nonanimal stabilized hyaluronic acid gel (Restylane, Perlane, Restylane Fine Lines, Q-Med AB, Uppsala, Sweden) for soft tissue augmentation using a retrospective review of all adverse events data from Europe, Canada, Australia, South American, and Asia from 1999 and 2000. RESULTS: Data from an estimated 144,000 patients treated in 1999 indicated the major reaction to injectable hyaluronic acid was localized hypersensitivity reactions, occurring in approximately 1 of every 1400 patients treated. In 1999 there was an adverse event reported for 1 of every 650 patients (0.15%) treated. These were temporary events that included redness, swelling, localized granulomatous reactions, bacterial infection, as well as acneiform and cystic lesions. For 2000 there was an estimated 262,000 patients treated with hyaluronic acid gel. The total number of adverse events was 144, corresponding to one adverse event for every 1800 patients (0.06%) treated. The major adverse event was again hypersensitivity, occurring in 1 of every 5000 patients treated. CONCLUSION: According to the reported worldwide adverse events data, hypersensitivity to nonanimal hyaluronic acid gel is the major adverse event and is most likely secondary to impurities of bacterial fermentation. According to data from 2000, the incidence of hypersensitivity appears to be declining after the introduction of a more purified hyaluronic acid raw material.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".