Evidence map›Paper›PMID 40791290›Full record

ReviewFrontiers in surgery2025

Application of augmented reality and surgical robotic navigation in total hip and knee replacement.

Xiuli Zhang, Yong Liu, Wen Luo, Yansu Guo

Abstract readReview
In one paragraph

Review in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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

3 citing papers in PubMed.

  1. Review
  2. [Research progress on tracker fixation strategies and related complications in robot-assisted total knee arthroplasty].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2026
    Review
  3. Review
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

4 authors.

Xiuli ZhangThe 1st Ward of Joint Surgery, Joint Surgery Department, Tianjin Hospital, Tianjin, China.
Yong LiuOrthropedic Department, Tianjin Hexi Hospital, Tianjin, China.
Wen LuoCollege of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin, China.
Yansu GuoBeijing Geriatric Healthcare and Disease Prevention Center, Xuanwu Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With advancements in computer vision, artificial intelligence, and other cutting-edge science and technologies, the focus of modern surgical technology has increasingly shifted towards intelligent, digital, minimally invasive, and precision approaches. Augmented reality (AR) technology and surgical robotics have emerged as significant research areas in total hip and knee replacement. Navigation systems, which are pivotal in both AR and robotic surgery, play a crucial role in guiding surgical operations using shared techniques. Recent developments in navigation systems for hip and knee replacement have focused on more natural, intelligent, and efficient methodologies. The use of AR and surgical robots for navigation has significantly enhanced the safety and accuracy of these procedures. Importantly, these technologies eliminate the need to implant positioning screws or other reference objects into the bone structure, thereby markedly reducing the risk of severe complications, such as lower limb pain and fractures. This study reviews the current applications, main challenges, and solutions associated with AR and surgical robot navigation systems for total hip and knee replacements.

Indexed as

augmented realityoperative navigationsurgical robottotal hip replacementtotal knee replacement

Identifiers

PMID40791290
PMCPMC12336157

What OpenQuestion holds

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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.