Evidence map›Paper›PMID 38627503›Full record

ArticleScientific reports2024

Optimized reusable modular 3D-printed models of choledochal cyst to simulate laparoscopic and robotic bilioenteric anastomosis.

Jing Gu, Jie Cao, Wenli Cao, Yusuo Chen, Fangqiang Wei

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

5 authors.

Jing GuDepartment of General Surgery, Cancer Center, Division of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang Province, China.
Jie CaoNingbo Chuangdao 3D Medical Technology Co., Ltd., Ningbo, 315336, Zhejiang Province, China.
Wenli CaoDepartment of General Surgery, Cancer Center, Division of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang Province, China.
Yusuo ChenDepartment of General Surgery, Cancer Center, Division of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang Province, China.
Fangqiang WeiDepartment of General Surgery, Cancer Center, Division of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang Province, China. wdfwfq@126.com.

Funding

the fund of Public Welfare Technology Research Program/Social Development of Zhejiang Provincial Natural Science Foundation of China No. LGF21H030011the fund of the Joint Project of Department of Science and Technology of State Administration of Traditional Chinese Medicine and Zhejiang Administration of Traditional Chinese Medicine No.GZY-ZJ-KJ-23059The Outstanding Young Personnel Research Fund of Zhejiang Provincial People's Hospital to Wei FQ No. ZRY2020B012
6 · The paper itself

Abstract

Laparoscopic and robotic surgery is a challenge to the surgeon's hand-eye coordination ability, which requires constant practice. Traditional mentor training is gradually shifting to simulation training based on various models. Laparoscopic and robotic bilioenteric anastomosis is an important and difficult operation in hepatobiliary surgery. We constructed and optimized the reusable modular 3D-printed models of choledochal cyst. The aim of this study was to verify the ability of this optimized model to distinguish between surgeons with different levels of proficiency and the benefits of repeated practice. A total of 12 surgeons with different levels participated in the study. Operation completion time and OSATS score were recorded. The model was validated by Likert scale. Surgeons were shown the steps and contents before performing laparoscopic or robotic bilioenteric anastomosis using the model. Surgeons with different levels of experience showed different levels when performing laparoscopic bilioenteric anastomosis on this model. Repeated training can significantly shorten the time of laparoscopic bilioenteric anastomosis and improve the operation scores of surgeons with different levels of experience. At the same time, preliminary results have shown that the performance of surgeons on the domestic robotic platform was basically consistent with their laparoscopic skills. This model may distinguish surgeons with different levels of experience and may improve surgical skills through repeated practice. It is worth noting that in order to draw more reliable conclusions, more subjects should be collected and more experiments should be done in the future.

Indexed as

Choledochal CystLaparoscopyRobotic Surgical ProceduresAnastomosis, SurgicalClinical CompetenceHumansPrinting, Three-Dimensional3D-printed modelBilioenteric anastomosisLaparoscopicRoboticTraining

Identifiers

PMID38627503
PMCPMC11021543

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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.