Evidence map›Paper›PMID 39133416›Full record

ArticleArchives of dermatological research2024

Outstanding user reported satisfaction for light emitting diodes under-eye rejuvenation.

Jennifer Y Wang, Margaret Kabakova, Paras Patel, David Bitterman, Kayla Zafar, Raichel Philip, Jessica Mineroff Gollogly, Sharen Rivas, Alana Kurtti, Nyousha Yousefi and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of dermatological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jennifer Y WangDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Margaret KabakovaDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Paras PatelDermatology Service, Veterans Affairs New York Harbor Healthcare System - Brooklyn Campus, Brooklyn, NY, USA.
David BittermanDermatology Service, Veterans Affairs New York Harbor Healthcare System - Brooklyn Campus, Brooklyn, NY, USA.
Kayla ZafarDermatology Service, Veterans Affairs New York Harbor Healthcare System - Brooklyn Campus, Brooklyn, NY, USA.
Raichel PhilipDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Jessica Mineroff GolloglyDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Sharen RivasIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Alana KurttiDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Nyousha YousefiDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Omobola OnikoyiDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Natasha MasubDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA.
Jared JagdeoDepartment of Dermatology, SUNY Downstate Medical Center, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, USA. jrjagdeo@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The under-eye region is an area of significant cosmetic concern. Photobiomodulation (PBM) has emerged as an effective, safe, inexpensive, and convenient treatment for skin rejuvenation. Herein, we aim to evaluate the safety and efficacy of a LED under-eye device for under-eye rejuvenation, as measured by objective and patient reported outcomes. Eleven participants self-administered treatment using a commercially available LED device emitting red (633 nm) and near infrared (830 nm) light for six weeks. Standardized photographs and questionnaires were administered at baseline and six weeks. Photographic digital analysis indicated an improvement in under-eye wrinkles at six weeks compared to baseline, with a reduction in wrinkle score from 20.05 to 19.72. However, this finding was not statistically significant. Participants self-reported consistent improvements in under-eye wrinkles, texture, dark circles, bags, pigmentation, and erythema. All participants reported a high degree of comfortability, ease of use, and satisfaction with the eye device. The participants noted no moderate or severe adverse events and few reports of transient expected outcomes such as mild erythema. The participants' self-reported improvements and high user satisfaction, and the device's favorable safety profile, highlights the benefits of at-home LED devices for under-eye rejuvenation. Future randomized controlled trials with larger sample sizes could further establish the safety and efficacy of at-home LED under-eye treatments.

Indexed as

Cosmetic TechniquesPatient SatisfactionRejuvenationSkin AgingAdultAgedFemaleHumansLow-Level Light TherapyMaleMiddle AgedSurveys and QuestionnairesTreatment OutcomeAestheticsLow level laser therapyPhotobiomodulationUnder-eye rejuvenationWrinkles

Identifiers

PMID39133416

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.