Identifying Minimum Single Dose of Recombinant Human Hyaluronidase for In Vitro Dissolution of Twenty-Two Hyaluronic Acid Fillers
Bibliographic record
Abstract
PURPOSE: As the use of hyaluronic acid fillers continues to increase for clinical and aesthetic purposes, associated complications continue to rise as well. Excess hyaluronidase is often used to dissolve filler, which has its own set of adverse effects. This study analyzes 22 commercially available fillers to delineate the lowest single dose of recombinant human hyaluronidase (RHH) required to fully dissolve each filler within 6 hours across 3 trials. METHODS: Aliquots in 0.2 ml amounts of each of 22 hyaluronic acid fillers were placed in wells. A single dose of RHH, titrated to a minimum volume of 0.45 cc, was administered to the center of the aliquot, to a maximum of 140 units. RHH amounts were as follows: 0, 2.5, 5, 10, 20, 40, 60, 80, 100, 120, or 140 units RHH. Bird's eye and lateral photographs were taken to monitor dissolution progress at several time points over the 6-hour period to monitor aliquot height and appearance changes. Filler aliquots were left undisturbed for 6 hours, after which dissolution was confirmed by stirring the aliquot on video recording. This process was repeated 3 times per filler to determine the minimum dose of RHH required to consistently dissolve each aliquot. RESULTS: For each of the 22 fillers, the minimum dose of RHH required for dissolution was identified with consistent results across 3 trials, demonstrating reliability. Juvéderm Volbella, Juvéderm Vollure, Juvéderm Skinvive, Restylane-L, Restylane Lyft, and Restylane Silk were identified as the least resistant fillers, requiring ≤20 units to dissolve. Resilient hyaluronic acid (RHA) 2, RHA 3, RHA 4, Belotero Volume, Juvéderm Ultra XC, Juvéderm Volux, Restylane Kysse, and Revanesse Versa were classified as most resistant, requiring ≥120 units to dissolve. CONCLUSIONS: This study identifies the minimum single dose of RHH from 2.5 units/0.2 ml to 140 units/0.2 ml for dissolution of 22 different hyaluronic acid fillers over 6 hours. These results paired with previous studies help elucidate the dissolution profiles of each filler in the context of their rheological properties, further informing physicians on how to optimally dissolve different hyaluronic acid fillers in a clinical setting.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".