Radiofrequency Microneedling: A Comprehensive and Critical Review
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: Many studies have evaluated radiofrequency microneedling (RFMN) in various dermatologic conditions. However, the efficacy and safety of RFMN, and how it compares with other energy-based devices in a clinician's armamentarium, remains unclear. OBJECTIVE: To review higher-quality evidence supporting RFMN and the dermatologic conditions which it can be used in. MATERIALS AND METHODS: A search was conducted in MEDLINE and EMBASE from inception to May 13, 2020, using the terms: "radiofrequency microneedling" OR "fractional radiofrequency" OR "radiofrequency needling" OR "radiofrequency percutaneous collagen induction." Only randomized, split body or blinded studies with original data on humans were included. Non-English or non-dermatology-related studies were excluded. RESULTS: Forty-two higher-quality studies were included after applying the inclusion and exclusion criteria. There were 14 studies for skin rejuvenation, 7 for acne scars, 6 for acne vulgaris, 5 each for striae and axillary hyperhidrosis, 2 for melasma, and 1 each for rosacea, cellulite, and androgenetic alopecia. CONCLUSION: Radiofrequency microneedling is an effective intervention that can be used repeatedly and safely in combination with other treatment modalities and in individuals with darker skin phototypes. Radiofrequency microneedling-induced dermal remodeling and neocollagenesis are slow and progressive but continue to improve even 6 months after treatment.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 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 | 0.001 | 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