Evidence map›Paper›PMID 39286816›Full record

ArticleJPRAS open2024

Robot-Assisted Microsurgery-what does the learning curve look like?

Helena Frieberg, Jessica M Winter, Olof Engström, Daniel Önefäldt, Anna Nilsson, Maria Mani

Abstract read
In one paragraph

Article in JPRAS open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

  1. Pooled it
  2. Pooled it
  3. Review
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  8. Review
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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.

Helena FriebergSection of Plastic and Maxillofacial Surgery, Department of Surgical Sciences, Uppsala University, and Department of Plastic and Reconstructive Surgery, Uppsala University Hospital, Uppsala, Uppsala, Sweden.
Jessica M WinterSection of Plastic and Maxillofacial Surgery, Department of Surgical Sciences, Uppsala University, and Department of Plastic and Reconstructive Surgery, Uppsala University Hospital, Uppsala, Uppsala, Sweden.
Olof EngströmSection of Plastic and Maxillofacial Surgery, Department of Surgical Sciences, Uppsala University, and Department of Plastic and Reconstructive Surgery, Uppsala University Hospital, Uppsala, Uppsala, Sweden.
Daniel ÖnefäldtSection of Plastic and Maxillofacial Surgery, Department of Surgical Sciences, Uppsala University, and Department of Plastic and Reconstructive Surgery, Uppsala University Hospital, Uppsala, Uppsala, Sweden.
Anna NilssonSection of Plastic and Maxillofacial Surgery, Department of Surgical Sciences, Uppsala University, and Department of Plastic and Reconstructive Surgery, Uppsala University Hospital, Uppsala, Uppsala, Sweden.
Maria ManiSection of Plastic and Maxillofacial Surgery, Department of Surgical Sciences, Uppsala University, and Department of Plastic and Reconstructive Surgery, Uppsala University Hospital, Uppsala, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The introduction of robotic assistance in surgical practice has led to advancements such as the MUSA-2 robotic system that was designed for microsurgical procedures. Advantages of this system include tremor filtration and motion scaling. Initial studies showed promising results in skill acquisition for robot-assisted microsurgery. This study evaluated the learning curve for microsurgical anastomosis with and without robotic assistance among surgeons of varying experience levels. Methods: Fifteen surgeons were divided into 3 groups (novice, intermediate, and expert) based on their microsurgical experience. They performed 10 anastomoses by hand and 10 with robotic assistance on synthetic polyvinyl alcohol vessels (diameter of 2 mm) in a laboratory setting. Participants were timed and mistakes such as backwall and leakage were assessed and recorded. Demographic information was collected. Results: Statistical differences were found in manual anastomosis times between the intermediate and novice groups compared to the experts (p < 0.01). However, no statistical difference was found in the mean time between groups for the robot-assisted anastomoses. Conclusion: This study indicated similarities in the learning curves for robot-assisted anastomosis among surgeons with varied experience levels. Experts excelled technically in manual anastomoses, but robot-assistance enabled novice and intermediate surgeons to perform comparably to the experts. Robotic assistance may aid more novice learners in performing microsurgical anastomosis safely at earlier points in their education.

Indexed as

AnastomosisLearning curveMicrosurgeryRobot-assistance

Identifiers

PMID39286816
PMCPMC11403640

What OpenQuestion holds

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LicenceCC BY
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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.