Evidence map›Paper›PMID 42803861›Full record

ReviewJournal of robotic surgery2026

Global research landscape and trends in robot-assisted unicompartmental knee arthroplasty: a bibliometric analysis.

Xueneng Yang, Ruijuan Li, Junfei Liu, Bo Li, Zhendong Yang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of robotic surgery, 2026. 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

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.

Xueneng YangThe First Affiliated Hospital of Xinjiang Medical University, Xinjiang Medical University, Urumqi, Xinjiang, China.
Ruijuan LiKunming Hanchen Medical Aesthetic Hospital, Yunnan, China.
Junfei LiuDepartment of Geriatric Orthopedics, Affiliated Hospital of Yunnan University, Kunming, Yunnan, China.
Bo LiDepartment of Traumatology, Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Zhendong YangSecond Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China. 20242050@kmmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robot-assisted unicompartmental knee arthroplasty (RA-UKA) has received increasing attention, but its overall research landscape and evolving priorities remain incompletely characterized. This study systematically analyzed the global literature on RA-UKA to identify research trends, major contributors, knowledge structures, and emerging topics. Publications indexed in the Web of Science Core Collection through August 20, 2026 were retrieved and analyzed using Bibliometrix/Biblioshiny and VOSviewer. A total of 238 publications from 73 journals involving 952 authors were included. Publication output increased markedly after 2018. The United States contributed the largest number of publications, while several European countries showed strong international collaboration. Knee Surgery, Sports Traumatology, Arthroscopy, The Journal of Arthroplasty, and The Bone & Joint Journal were major publication and citation sources. Early influential studies focused primarily on robotic systems, surgical accuracy, and implant positioning. More recent research has increasingly addressed clinical outcomes, survivorship, revision, complications, patient-reported outcomes, patient satisfaction, and personalized knee arthroplasty. Overall, RA-UKA research has shifted from establishing technical accuracy toward determining whether these technical advantages translate into durable and clinically meaningful benefits. Further multicenter and long-term comparative studies are needed to clarify its effectiveness across different patients, robotic platforms, and clinical settings.

Indexed as

Arthroplasty, Replacement, KneeBibliometricsRobotic Surgical ProceduresHumansBibliometric analysisKnowledge mappingResearch landscapeResearch trendsRobot-assisted unicompartmental knee arthroplasty

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.