Radiofrequency-Based Treatments for Facial Rejuvenation: A Systematic Review of Efficacy, Safety, and Patient-Centered Outcomes
Bibliographic record
Abstract
Background: Radiofrequency (RF) devices are widely used for noninvasive facial rejuvenation, but evidence on patient-centered outcomes remains heterogeneous and variably reported. Objectives: To synthesize evidence on the aesthetic, safety, tolerability, and psychological outcomes of RF treatments for facial rejuvenation. Methods: A systematic review was conducted in accordance with PRISMA and JBI guidelines. Databases (PubMed, Embase, CENTRAL, and LILACS) were searched for studies published between 2015 and 2025. Risk of bias was assessed using a JBI tool. A thematic synthesis was performed for aesthetic outcomes, patient satisfaction, and safety. The confidence of findings was evaluated using the GRADE-CERQual approach. Results: Fifteen studies were included, comprising a total of 1230 participants. RF treatments consistently improved aesthetic outcomes. Skin texture improved in 71% to 100% of patients (4 studies), and skin firmness improved in 52.9% to 100% (2 studies). High patient satisfaction was demonstrated, with rates ranging from 82% to 100% (13 studies). The safety profile was favorable; adverse events were mild and transient (erythema: 17.6%-100%; edema: 5.3%-26.5%), and no serious complications were reported. Mean pain scores were low (1.94/10 VAS). GRADE-CERQual assessment showed moderate confidence in these findings. A key limitation was the universal underreporting of downtime. Conclusions: Evidence indicates RF treatments for facial rejuvenation yield meaningful aesthetic improvements, high patient satisfaction, and an excellent safety profile. However, these conclusions are tempered by methodological limitations in the primary literature. Future research should employ rigorous designs, standardized outcome measures, and report on downtime to strengthen the evidence base.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".