Consensus Recommendations for Combined Aesthetic Interventions in the Face Using Botulinum Toxin, Fillers, and Energy-Based Devices
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: The aging process is a complex interplay of intrinsic and extrinsic factors across multiple layers of the face. Accordingly, combining aesthetic interventions targeting different manifestations of aging often leads to better results than single modalities alone. However, no guidelines for a pan-facial approach using multiple interventions have been published to date. OBJECTIVE: To develop consensus recommendations for the optimal combination and ideal sequence of botulinum toxin (BoNT), hyaluronic acid, calcium hydroxylapatite, and microfocused ultrasound with visualization (MFU-V) in persons of all Fitzpatrick skin types. METHODS AND MATERIALS: Fifteen specialists convened under the guidance of a certified moderator. Consensus was defined as approval from 75% to 94% of all participants, whereas agreement of ≥95% denoted a strong consensus. RESULTS: Optimal aesthetic treatment of the face begins with a thorough patient assessment and an individualized treatment plan. Spacing consecutive treatments 1 to 2 weeks apart allows for resolution of side effects and/or to assess results. For same-day treatments, BoNT and fillers may be performed together in either sequence, whereas MFU-V is recommended before injectable agents. CONCLUSION: Expert consensus supports a combination approach using multiple modalities in specific sequence for the safe and effective treatment of the aging face.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it