Evidence map›Paper›PMID 41267924›Full record

ArticleMedComm2025

Unleashing the Potential: First-in-Human Evaluation of Automatic Robotic-Assisted Endovascular Aortic Repair for Standardized Therapies.

Bowen Liang, Chao Song, Shibo Xia, Wenying Guo, Longtu Zhu, Kundong Wang, Qingsheng Lu

Abstract read
In one paragraph

Article in MedComm, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Review
  3. 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

7 authors.

Bowen LiangDepartment of Vascular Surgery, Shanghai Changhai Hospital Naval Medical University Shanghai China.
Chao SongDepartment of Vascular Surgery, Shanghai Changhai Hospital Naval Medical University Shanghai China.
Shibo XiaDepartment of Vascular Surgery, Shanghai Changhai Hospital Naval Medical University Shanghai China.
Wenying GuoDepartment of Vascular Surgery, Shanghai Changhai Hospital Naval Medical University Shanghai China.
Longtu ZhuDepartment of Vascular Surgery, Shanghai Changhai Hospital Naval Medical University Shanghai China.
Kundong WangDepartment of Instrument Science and Engineering Shanghai Jiao Tong University Shanghai China.
Qingsheng LuDepartment of Vascular Surgery, Shanghai Changhai Hospital Naval Medical University Shanghai China.ORCID https://orcid.org/0000-0003-0262-7985

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endovascular surgical robots have advanced vascular surgery through the integration of automatic programs for complex interventions. However, current systems still lack full procedural automation capabilities. This single-center single-arm study explores the feasibility and safety of automatic robotic-assisted endovascular aortic repair (EVAR) using a novel surgical algorithm with in vitro and in vivo experiments. The EVAR process was deconstructed into surgical steps and programmed into an endovascular surgical robot, which executed the steps automatically based on parameters derived from image processing software. In vitro experiments using 3D-printed vascular models demonstrated millimeter-level precision, with reduced operation time, fluoroscopy time, and radiation exposure compared to manual robotic control. In vivo evaluations in four patients with abdominal aortic aneurysms achieved 100% technical and clinical success, with no major adverse events. Operation time averaged 110 ± 47 min, fluoroscopy time was 19 ± 6 min, and patient-side radiation exposure was 1251 ± 389 mGy. Surgeon-side radiation exposure was 4 ± 1 mGy. The results indicate that automatic robotic-assisted EVAR can be performed with acceptable accuracy and safety to provide standardized therapies, shorten operation time, and reduce radiation exposure of patients.

Indexed as

automaticendovascular aortic repairsurgical algorithmsurgical robot

Identifiers

PMID41267924
PMCPMC12627237

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.