Evidence map›Paper›PMID 34762249›Full record

ArticleJournal of robotic surgery2022

Study on augmented reality for robotic surgery bedside assistants.

Camille Linick Stewart, Abigail Fong, Govinda Payyavula, Simon DiMaio, Kelly Lafaro, Kirsten Tallmon, Sherry Wren, Jonathan Sorger, Yuman Fong

Abstract read
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In one paragraph

Article in Journal of robotic surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Robot-assisted liver resection: the real benefit so far.Langenbeck's archives of surgery · 2022
    Review
  5. 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

9 authors.

Camille Linick StewartDepartment of Surgery, City of Hope National Medical Center, Duarte, CA, USA.ORCID http://orcid.org/0000-0002-9745-5823
Abigail FongDepartment of Surgery, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Govinda PayyavulaIntuitive Surgical, Sunnyvale, CA, USA.
Simon DiMaioIntuitive Surgical, Sunnyvale, CA, USA.
Kelly LafaroDepartment of Surgery, Johns Hopkins University, Baltimore, MD, USA.
Kirsten TallmonDepartment of Surgery, City of Hope National Medical Center, Duarte, CA, USA.
Sherry WrenDepartment of Surgery, Stanford University School of Medicine, Palo Alto, CA, USA.
Jonathan SorgerIntuitive Surgical, Sunnyvale, CA, USA.
Yuman FongDepartment of Surgery, City of Hope National Medical Center, Duarte, CA, USA. yfong@coh.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic surgery bedside assistants play an important role in robotic procedures by performing intra-corporeal tasks while accommodating the physical presence of the robot. We hypothesized that an augmented reality headset enabling 3D intra-corporeal vision while facing the surgical field could decrease time and improve accuracy of robotic bedside tasks. Bedside assistants (one physician assistant, one medical student, three surgical trainees, and two attending surgeons) performed validated tasks within a mock abdominal cavity with a surgical robot docked. Tasks were performed with a bedside monitor providing 2D or 3D vision, or an optical see-through head-mounted augmented reality device with 2D or 3D vision. The effect of augmented reality device resolution on performance was also evaluated. For the simplest task of touching a straw, performance was generally high, regardless of mode of visualization. With more complex tasks, including stapling and pulling a ring along a path, 3D augmented reality decreased time and number of errors per task. 3D augmented reality allowed the physician assistant to perform at the level of an attending surgeon using 3D augmented reality (p = 0.08). All participants had improved times for the ring path task with better resolution (lower resolution 23 ± 11 s vs higher resolution 14 ± 4 s, p = 0.002). 3D augmented reality vision with high resolution decreased time and improved accuracy of more complex tasks, enabling a less experienced robotic surgical bedside assistant to function similar to attending surgeons. These data warrant further study with additional complex tasks and bedside assistants at various levels of training.

Indexed as

Augmented RealityLaparoscopyRoboticsRobotic Surgical ProceduresClinical CompetenceHumansAugmented realityLaparoscopyMinimally invasive surgeryRobotic surgeryVideo-assisted surgeryVideo display

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.