ArticleAesthetic plastic surgery2024
The 3-Level Approach to Facelift Planning: A Simple Paradigm for Surgical Rejuvenation of the Face.
Article in Aesthetic plastic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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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.
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Authors and funding
2 authors.
Funding
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Abstract
Our role as aesthetic surgeons demands individualized surgical planning that maximizes patient input and understanding. The value of such shared decision-making (SDM) in aesthetic surgery is becoming increasingly appreciated. This is particularly true for potential patients seeking surgical rejuvenation of the face, where the volume of "educational" information available on the internet, and through various social medial channels, may be overwhelming and even misleading. Presented is a "3-Level approach to facelift planning" named for the facial subregions targeted. This novel paradigm maximizes SDM with its simplicity and reproducibility, serves as an invaluable educational tool for patients, novice and seasoned surgeons alike, and facilitates communication between senior surgeons through its descriptive standardization. LEVEL OF EVIDENCE V: 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 .
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Registered trials
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.