Evidence map›Paper›PMID 39026056›Full record

ArticleAesthetic plastic surgery2024

New Aesthetic Unit (NAU) Method: A Comprehensive Method Based on Accurate Anatomical Assessment and Precise Multilayering Panfacial Treatment for Hyaluronic Acid Fillers.

Navid Alizadeh

Abstract readCase Reports
In one paragraph

Article in Aesthetic plastic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

1 author.

Navid AlizadehCare Geneva Aesthetics, Rue Rodolphe-Toepffer 12, 1206, Geneva, Switzerland. navid.alizadeh@caregeneva.com.ORCID 0009-0006-6786-0824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent progress in anatomy enables a more sophisticated approach to treat patients with facial aesthetic concerns (PFAC) with HA fillers. Furthermore, advances in rheology have offered a range of HA fillers with different biomechanical properties adapted to different indications.

methodsBased on recent anatomical and rheological progresses, the author has developed a new methodology that couples an accurate patient assessment tool and a panfacial precise treatment instrument. In the presented method, the face is divided into 6 units called New Aesthetic Units (NAU). NAUs are classified on the extent of volume deficiency and asymmetry, ranging from none to moderate to severe deficiencies. After discussion with the patient regarding the assessment findings, a customized treatment plan, including timelines and number of sessions, is recommended. The modalities of the treatment are exhaustively described for each NAU based on multilayering, best practice medicine, and expert consensus available in the literature.

resultsBefore-and after-case studies are presented to illustrate how the NAU method is used in routine practice for the treatment of two patients with HA fillers.

conclusionThe NAU method is not only a practical and accurate roadmap for the assessment and treatment of PFAC with HA fillers, but also facilitates communication between injectors and patients and data analysis. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

Cosmetic TechniquesDermal FillersFaceHyaluronic AcidSkin AgingEstheticsFemaleHumansTreatment OutcomeDermal FillersHyaluronic AcidAestheticsDermal fillersFacial agingHyaluronic acidRejuvenation

Identifiers

PMID39026056
PMCPMC11739202

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Registered trials

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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.