Comparison of Intense Pulsed Light with 1,927-nm Fractionated Thulium Fiber Laser for the Rejuvenation of the Chest
Bibliographic record
Abstract
BACKGROUND: Rejuvenation of the aging chest is important to prevent noticeable disparities between the treated skin of the face and that of the untreated chest. OBJECTIVE: To compare a high-density thulium fiber laser (TFL)-based protocol for the rejuvenation of the aging chest with intense pulsed light (IPL). METHODS AND MATERIALS: We conducted a retrospective chart review comparing patients treated with IPL and those treated with TFL in combination with a quality-switched alexandrite laser and long pulsed dye laser. Blinded photographic assessment of overall improvement, rhytides, skin texture, dyspigmentation, and telangiectasia was performed. Patient satisfaction was assessed in a standardized follow-up survey. Cost and practicality were compared. RESULTS: At a mean follow-up of 45.8 days for IPL and 78.3 days for TFL, the two protocols had comparable clinical efficacy in achieving rejuvenation of the chest. Differences existed in terms of cost and practicality. CONCLUSION: TFL can be used at high density and in simultaneous combination with other targeted laser modalities to achieve rejuvenation of the aging chest. IPL achieves similar clinical efficacy. The choice between treatment modalities depends on physician and patient preferences.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".