Evidence map›Paper›PMID 41018845›Full record

ArticleJournal of medical ultrasound

Clinical Algorithm for Ultrasound-guided Facial and Neck Rejuvenation.

Sekina Alimova, Yehya Tlaiss, Victor Truten, John Warrak

Abstract read
In one paragraph

Article in Journal of medical ultrasound. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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

4 authors.

Sekina AlimovaDepartment of Radiology, Federal State Budgetary Educational Institution of Higher Education, Russian University of Medicine, Ministry of Health of the Russian Federation, Moscow, Russia.
Yehya TlaissDepartment of Ophthalmology, University of Balamand, Beirut, Lebanon.
Victor TrutenDepartment of Radiology, Federal State Budgetary Educational Institution of Higher Education, Russian University of Medicine, Ministry of Health of the Russian Federation, Moscow, Russia.
John WarrakDepartment of Ophthalmology, University of Balamand, Beirut, Lebanon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global rise in demand for minimally invasive esthetic procedures has underscored the need for enhanced precision and safety. This study presents a novel clinical algorithm integrating real-time ultrasound (US) guidance into facial and neck rejuvenation treatments to improve procedural outcomes. Conducted over four years with 56 patients, the study utilized high-frequency B-mode imaging, Doppler functionality, and superb microvascular imaging (SMI) to map anatomical structures, optimize treatment planning, and guide interventions. The algorithm follows a systematic, step-by-step protocol encompassing patient selection, anatomical assessment, procedure execution, and postoperative evaluation. Results indicated a significant improvement in procedural precision, with reduced complication rates and higher patient satisfaction. Notably, 85% of patients rated their outcomes as "much improved" or "very much improved" on the Global Aesthetic Improvement Scale (GAIS). The US-guided approach enabled more accurate filler placement, minimized vascular complications, and improved outcomes compared to traditional techniques. These findings support the integration of US diagnostics in esthetic practice to enhance safety, optimize results, and contribute to the evolving standards of care in non-surgical facial rejuvenation.

Indexed as

Aesthetic medicinefacial rejuvenationneck rejuvenationultrasound-guided procedures

Identifiers

PMID41018845
PMCPMC12463357

What OpenQuestion holds

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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.