Evidence map›Paper›PMID 41667898›Full record

ArticleJournal of robotic surgery2026

Global research trends in robot-assisted partial nephrectomy: a visualized bibliometric analysis.

Longtu Ma, Zewen Li, Zhao Xu, Rui Lu, Jingwen Liu, Xiaoyu Huang, Zhilong Dong

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Longtu Ma *Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China.
Zewen Li *Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China.
Zhao Xu *The Affiliated Taian City Central Hospital of Qingdao University, Taian, China.
Rui LuThe Affiliated Taian City Central Hospital of Qingdao University, Taian, China.
Jingwen LiuThe Affiliated Taian City Central Hospital of Qingdao University, Taian, China.
Xiaoyu HuangThe Affiliated Taian City Central Hospital of Qingdao University, Taian, China. huangxiaoyu95@163.com.
Zhilong DongDepartment of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China. dzl19780829@163.com.

Funding

Cuiying Science and Technology Innovation Program CY2024-LC-A01Fundamental Research Funds for Central Universities lzujbky-2023-ct06Gansu Province Joint Research Fund 23JRRA1509Gansu Province Key Talent Program 2023RCXM42Gansu Province Major Science and Technology Special Project 24ZDFA007National Natural Science Foundation of China 82160148
6 · The paper itself

Abstract

This study aimed to characterise the global research landscape of robot-assisted partial nephrectomy (RAPN) using bibliometric methods, by outlining temporal trends in publication output, key contributors and research themes, and identifying remaining evidence gaps. Publications on RAPN from 2001 to 2025 were retrieved from the Web of Science Core Collection, restricted to English-language articles and reviews. After screening titles and abstracts, 2,367 records were included (1,994 original articles and 373 reviews). Microsoft Excel was used to organise bibliographic information and generate time-trend plots. CiteSpace 6.3 and VOSviewer 1.6.17 were applied to construct collaboration and co-citation networks for countries/regions, institutions, authors, journals, keywords and references, and to perform clustering, timeline and burst-detection analyses. Annual RAPN publications were few in the early 2000s but increased steadily, entering a high-output phase in recent years and indicating that RAPN has become an important option in nephron-sparing surgery. Research activity was concentrated in a limited number of countries: the United States was the leading contributor, followed by Italy and China, with additional input from other European and Asian countries. A small group of high-volume tertiary and academic centres formed the institutional core of the field. Most articles were published in specialist urology journals, while leading general urology titles were the most frequently co-cited sources. Keywords were mainly related to partial nephrectomy, nephron-sparing surgery, surgical approach, outcomes and complications. Co-occurrence, clustering and timeline analyses showed that research focus has shifted from early feasibility and comparisons with open or laparoscopic surgery towards tumour complexity scoring, renal ischaemia and function preservation, oncologic outcomes, and the integration of three-dimensional reconstruction and image-guided or augmented reality–assisted RAPN. Global RAPN research has expanded rapidly over the past two decades and is largely driven by high-volume centres in North America and Europe, with growing participation from Asia. Existing evidence supports RAPN as a key component of nephron-sparing surgery, particularly for complex renal tumours, but robust prospective and multicentre data on long-term renal function, quality of life, cost-effectiveness and outcomes in less-resourced settings remain insufficient. Future studies should strengthen international collaboration, standardise functional and oncologic outcome reporting, and focus on risk-stratified comparisons and real-world cohorts to better define the indications and clinical value of RAPN.

Indexed as

BibliometricsKidney NeoplasmsNephrectomyRobotic Surgical ProceduresHumansBibliometricsCiteSpaceRenal cell carcinomaRobot-assisted partial nephrectomyVOSviewer

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.