Evidence map›Paper›PMID 38746355›Full record

ArticleResearch square2024

Implementing a Robotic Hepatopancreatobiliary Program for New Faculty: Safety, Feasibility and Lessons Learned.

Britney Niemann, Christopher Kenney, J Wallis Marsh, Carl Schmidt, Brian A Boone

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Britney NiemannDivision of Surgical Oncology, Department of Surgery, West Virginia University.
Christopher KenneyDivision of Surgical Oncology, Department of Surgery, West Virginia University.
J Wallis MarshDivision of Surgical Oncology, Department of Surgery, West Virginia University.
Carl SchmidtDivision of Surgical Oncology, Department of Surgery, West Virginia University.
Brian A BooneDivision of Surgical Oncology, Department of Surgery, West Virginia University.

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Laura F. Gibson · 2012 to 2026
$81.0M
NIGMS NIH HHS U54 GM104942
6 · The paper itself

Abstract

Background: Robotic surgery is increasingly utilized in hepatopancreatobiliary (HPB) surgery, but the learning curve is a substantial obstacle hindering implementation. Comprehensive robotic training can help to surmount this obstacle; however, despite the expansion of robotic training into residency and fellowship programs, limited data is available about how this translates into successful incorporation in faculty practice. Methods: All operations performed during the first three years of practice of a complex general surgical oncology-trained surgical oncologist at a tertiary care academic institution were retrospectively reviewed. The surgeon underwent comprehensive robotic training during residency and fellowship. Results: 137 HPB operations were performed during the initial three years of practice. Over 80% were performed robotically each year across a spectrum of HPB procedures with a 6% conversion rate. Median operative time, the optimal metric for operative proficiency and evaluation for a learning curve, was similar throughout the study period for each major operation and below several reported optimized operative times. Major complications were similar across the experience and comparable to published series. Conclusion: Comprehensive robotic training in residency and fellowship as well as a dedicated, well-trained operative team allows for early attainment of optimized outcomes in a new HPB robotic practice.

Indexed as

careerhepatopancreatobiliaryprogram implementationrobotic surgery

Identifiers

PMID38746355
PMCPMC11092865

What OpenQuestion holds

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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.