A Proposed Method for Upper Eyelid and Infrabrow Tightening Using a Transcutaneous Temperature Controlled Radiofrequency Device With Opaque Plastic Eye Shields.
Bibliographic record
Abstract
BACKGROUND: Laxity of the eyelid and periorbital area, a common manifestation of aging, is usually addressed via blepharoplasty and/ or fat transfer. Given the trend toward safer, less invasive treatments preferred by those patients reticent to undergo more invasive procedures, viable alternatives have been sought. Transcutaneous temperature controlled radiofrequency (TTCRF) integrates non- invasive super cial RF treatment with automatic temperature feedback control of energy deposition, as a stimulator of overall collagen remodeling; however, the globe of the eye is particularly sensitive to RF energy. The purpose of the study was to propose a method by which TTCRF and other non-ablative modalities could be used to treat eyelid and infrabrow laxity, with autoclavable opaque black haptic scleral contact lenses protecting the globe of the eye. METHODS: Subjects (n=40, 36 women and 4 men, age range, 33-72) with mild to moderate laxity of the eyelid and infrabrow were treated with TTCRF using black plastic eye shields (Oculoplastik, Montreal, Quebec, Canada) to protect the globe of the eye from heat and RF energy. With the shields in place subjects were treated with the 10 mm small monopolar emitter of the ThermiSmooth device (Thermi, Irving, Tex.), using small circular looping motions to safely elevate the temperature of target tissue to the therapeutically rel- evant range for approximately 6 minutes; tissue temperature was measured in real time using the device's forward-looking infrared imaging. RESULTS: No major adverse events were recorded. Treatment was safe and tolerable for all subjects. CONCLUSION: The use of autoclavable opaque black plastic eye shields provides a safe method of treating the upper eye lid and infrabrow using TTCRF. J Drugs Dermatol. 2016;15(11):1302-1305..
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 0.001 |
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".