Microneedle fractional radiofrequency in the treatment of periorbital dark circles
Bibliographic record
Abstract
BACKGROUND: Periorbital hyperpigmentation (POH) is a common disorder in the patients. Women are more upset with POH in compare to males. Several methods have been used to the POH, with different efficacy and adverse reactions. AIM: The aim of the present study is to evaluate the efficacy of microneedle fractional radiofrequency (MRF) in treating POH. METHODS: So, nine patients with POH and the age range of 25-57 years, were treated by microneedle fractional radiofrequency (MRF). The outcome was evaluated via biometric assessment. The colorimeter was used to assess the skin lightness. Mexameter was used for evaluated the amount of Melanin in the periorbital skin. Cutometer was used for skin elasticity assessment. The skin ultrasound imaging system was utilized to estimate the epidermis and dermis diameter and density. Furthermore, Visioface was applied to assessed the skin color and wrinkles. Also patient's satisfaction and physician's assessment were evaluated. RESULTS: The results displayed that the periorbital skin lightness 32.38% ± 5.67 and elasticity of the R2: 40.29% ± 8.18, R5: 39.03 ± 5.38 and R7: 42.03% ± 14.16 were significantly improved after treatment (p < 0.05). Also the melanin content of the skin was decreased (49.41% ± 9.12). The skin layers were denser in the dermis and also in the epidermis (skin density: 30.21% ± 10.16 and skin thickness: 41.12% ± 13.21) (p < 0.05). The results revealed the decrease in the percent change of the skin color (30.34% ± 9.30) and wrinkle (area: 25.84% ± 6.43 and volume: 30.66% ± 8.12) (p < 0.05). Similarly, the physician and patient's assessment were confirmed the obtained outcomes. CONCLUSION: In conclusion, the microneedle RF technique is practicable, effective and safe method for periorbital dark circles treatment.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".