Evidence map›Paper›PMID 39386097›Full record

ArticlePlastic and reconstructive surgery. Global open2024

Technical Strategies and Learning Curve in Robotic-assisted Peripheral Nerve Surgery.

Martin Aman, Felix Struebing, Jonathan Weigel, Amir K Bigdeli, Emre Gazyakan, Ulrich Kneser, Leila Harhaus, Arne H Boecker

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

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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

8 authors.

Martin AmanFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Felix StruebingFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Jonathan WeigelFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Amir K BigdeliFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Emre GazyakanFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Ulrich KneserFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Leila HarhausFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.
Arne H BoeckerFrom the Department of Hand, Plastic and Reconstructive Surgery, Burn Center, B.G. Trauma Center Ludwigshafen, Ludwigshafen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robotic-assisted peripheral nerve surgery (RASPN) has emerged as a promising advancement in microsurgery, offering enhanced precision and tremor reduction for nerve coaptations. This study investigated the largest published patient collective in RASPN and provided specific technical aspects, operative setups, and a learning curve. Methods: Data collection involved creating a prospective database that recorded surgical details such as surgery type, duration, nerve coaptation time, and number of stitches. The experienced surgeon first underwent a 12-hour training program utilizing the Symani robot system in combination with optical magnification tools before using the system clinically. Results: The study included 19 patients who underwent robot-assisted peripheral nerve reconstruction. The cohort included six men (31.6%) and 13 women (68.4%), with an average age of 53.8 ± 18.4 years. The procedures included nerve transfers, targeted muscle reinnervation, neurotized free flaps, and autologous nerve grafts. Learning curve analysis revealed no significant reduction in time per stitch over the initial nine coaptations (4.9 ± 0.5 min) compared with the last 10 coaptations (5.5 ± 1.5 min). Conclusions: The learning curve for RASPN was compared with early experiences with other surgical robots, emphasizing the importance of surgical proficiency and assistant training. Obstacles such as instrument grip strength and blood clot formation were highlighted, and suggestions for future advancements were proposed. RASPN presents an exciting opportunity to enhance precision; however, ongoing research and optimization are necessary to fully harness its benefits.

Identifiers

PMID39386097
PMCPMC11463204

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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.