Evidence map›Paper›PMID 40678600›Full record

ArticlePlastic and reconstructive surgery. Global open2025

Robotic-assisted Supermicrosurgery in Plastic Surgery: A Systematic Literature Review.

Hannah Brown, Ryleigh A Brown, Leticia Lenkiu, Aseela SamSam, Joseph Lopez, Rajendra Sawh-Martinez

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
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

6 authors.

Hannah BrownFrom the Department of Plastic & Reconstructive Surgery, University of Central Florida, School of Medicine, Orlando, FL.
Ryleigh A BrownMilken Institute of Public Health, George Washington University, Washington, DC.
Leticia LenkiuFrom the Department of Plastic & Reconstructive Surgery, University of Central Florida, School of Medicine, Orlando, FL.
Aseela SamSamDivision of Emergency Medicine, AdventHealth for Children, Orlando, FL.
Joseph LopezPediatric Head and Neck Surgery, AdventHealth for Children, Orlando, FL.
Rajendra Sawh-MartinezFrom the Department of Plastic & Reconstructive Surgery, University of Central Florida, School of Medicine, Orlando, FL.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robotic microsurgery is rapidly changing the surgical landscape by mitigating conventional hand-surgical limitations such as physiological tremor while promoting increased precision in confined spaces through the provision of high-depth microoptics and motion-scaling. The innovation of specialized "super" microsurgical robotic platforms such as Medical Microinstruments' Symani and Microsure's MUSA-2 has further bolstered microsurgical toolkits by enabling high-precision microvascular anastomoses in vessels with a diameter of 0.8 mm of less. Methods: Our team conducted a systematic literature review of the global uses of robotic-assisted supermicrosurgery in plastic and reconstructive surgery. Using Preferred Reporting Items for Systematic Review and Meta-Analyses 2020 flow guidelines, our search yielded 107 articles, of which 16 were eligible based on our inclusion criteria. Results: Our results showed that lymphaticovenous anastomoses represent 37% of reported plastic and reconstructive surgery supermicrosurgery robot clinical uses, whereas free flaps and nerve repairs comprised just 14% and 2%, respectively. These procedures were found to correspond with significant but short learning curves. Across studies, mean operating times were found to be up to 1.5 times greater than manual techniques and showed a downward trend in time spent. Our analysis revealed that robotic-assisted techniques decreased rates of microtrauma, with anastomotic patency rates of 99.38%. Conclusions: Although robotic technology represents a significant financial investment and includes training needs, current literature supports evidence of potential long-term net savings due to reliably high patency rates; decreased in-hospital recovery times; the promise of new, expanded surgical options and capabilities; and enhanced career longevity for surgeons.

Identifiers

PMID40678600
PMCPMC12269818

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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.