Evidence map›Paper›PMID 40747731›Full record

ArticleSkin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)2025

Fractional and Non-Fractional Picosecond Nd:YAG Lasers Combined With Fractional Picosecond KTP Laser for the Treatment of Melasma in Female Chinese.

Changhan Chen, Youhui Ke

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In one paragraph

Article in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Changhan ChenDepartment of Cosmetology, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine, Affiliated Zhejiang Chinese Medical University, Wenzhou, Zhejiang, China.ORCID https://orcid.org/0009-0001-2780-8777
Youhui KeDepartment of Cosmetology, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine, Affiliated Zhejiang Chinese Medical University, Wenzhou, Zhejiang, China.

Funding

Wenzhou Key Laboratory of Laser Cosmetology 2022HZSY0042
6 · The paper itself

Abstract

BACKGROUND AND

objectivesMelasma is a chronic pigmented lesion on the face that is challenging to treat. Single laser treatments are usually ineffective. Recently, picosecond lasers are becoming an emerging option for the treatment of melasma. This study aimed to evaluate the efficacy and safety of fractional and non-fractional picosecond Nd:YAG lasers (PSNL) combined with fractional picosecond KTP laser (PSKL) on melasma in female Chinese.

methodsForty-eight Chinese patients with facial melasma were selected and divided into two groups. Every 4 weeks, each patient received one treatment, for a total of six treatments. Treatment was administered to 24 patients using fractional and non-fractional PSNL in the Nd:YAG group and fractional PSKL combined with fractional and non-fractional PSNL in the Nd:YAG+KTP group. Pain scores and adverse reactions were noted following each treatment, and the modified Melasma Area Severity Index (mMASI) and patient satisfaction were assessed 1 month following every two treatments.

resultsThe mMASI scores of both groups showed a considerable decline from the baseline. Following six treatments, the Nd:YAG+KTP group's mean mMASI score was 2.29 ± 0.82, while the Nd:YAG group was 2.87 ± 0.68. This difference was statistically significant (p < 0.05). At every stage of the procedure, the Nd:YAG+KTP group experienced higher patient satisfaction than the Nd:YAG group. In comparison to the Nd:YAG group, which had a pain score of 2.75 (2.54, 3.00), the Nd:YAG+KTP group had a higher pain score of 3.00 (3.00, 3.17). During the study, no severe side effects were seen in the treated areas, including blisters, hypopigmentation, or post-inflammatory hyperpigmentation (PIH).

conclusionThe efficacy of fractional and non-fractional PSNL combined with fractional PSKL in the treatment of melasma is significantly better than that of using single wavelength fractional and non-fractional PSNL, with higher patient satisfaction and less adverse reactions.

Indexed as

Lasers, Solid-StateLow-Level Light TherapyMelanosisAdultChinaEast Asian PeopleFemaleHumansMiddle AgedPatient SatisfactionTreatment OutcomeYoung Adultfractionalmelasmanon‐fractionalpicosecond KTP laserpicosecond Nd:YAG laser

Identifiers

PMID40747731
PMCPMC12314648

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.