Safety and Tolerability of the 1440‐ and 1927‐nm Non‐Ablative Fractional Diode Laser System for Skin Resurfacing: A Review of Current Literature
Bibliographic record
Abstract
BACKGROUND: Energy-based devices, such as lasers, provide effective treatments for skin resurfacing. Ablative fractional lasers have a higher risk of adverse events (AEs), like scarring and postinflammatory hyperpigmentation, particularly in patients with darker skin types, than non-ablative fractional lasers. The 1440- and 1927-nm non-ablative fractional diode laser (NFDL) system is indicated for use in dermatological procedures requiring the coagulation of soft tissue and for general skin resurfacing procedures. AIM: To help inform clinical decision-making about the dual 1440/1927-nm NFDL system, particularly for treating patients with diverse skin types who require safe and effective resurfacing treatments. METHODS: A PubMed search of literature was conducted to review safety and tolerability outcomes from clinical studies of 1440- and 1927-nm NFDL treatments. RESULTS: Expected skin reactions, including erythema, edema, and crusting, were mild to moderate and self-limited for concurrent and individual use of the 1440- and 1927-nm handpieces. Mild discomfort and heat sensation, which were also expected, indicated that treatment was well tolerated. Safety was also demonstrated in patients with skin of color, with no serious AEs. Levels of patient satisfaction were high. CONCLUSIONS: The dual 1440/1927-nm NFDL system is a safe and well-tolerated option for resurfacing of diverse skin types with minimal postprocedural downtime and reduced risk of AEs relative to ablative lasers.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".