Monopolar radiofrequency treatment of human eyelids: A prospective, multicenter, efficacy trial
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: To evaluate the efficacy of a novel 0.25 cm(2) monopolar radiofrequency (RF) treatment tip for aesthetic rejuvenation of the eyelids. STUDY DESIGN/MATERIALS AND METHODS: This was a prospective, multicenter trial in which the eyelids of 72 patients were treated. Patients underwent a single treatment session and were then followed on a serial basis for 6 months. Cutaneous anesthesia was not required to perform the treatments. Assessments were made by the treating physician, the subjects, and by masked physician observers evaluating photographs taken at each data point. RESULTS: Upper eyelid tightening and reduction of hooding was noted in 88 and 86% of subjects, respectively. Lower eyelid tightening was noted in 71-74% of subjects. The majority of patients treated achieved at least up to 25% improvement while a smaller percentage achieved more dramatic results. There was no correlation between the amount of energy applied to the eyelids and the clinical outcome. There were no serious adverse sequelae. CONCLUSION: Human eyelids can be safely treated with monopolar RF energy delivered via a novel 0.25 cm(2) treatment tip. Using this technology non-invasive eyelid rejuvenation was achieved in the majority of subjects treated. The factors differentiating those patients who achieve the most impressive changes from others remain unclear. Further development and testing of this technology is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".