Evidence map›Paper›PMID 42317387›Full record

ArticleDigital health

Advances in intelligent assistance operative adjuncts for unicompartmental knee arthroplasty: A bibliometric analysis of research trends and developments.

Ruilin Shi, Shuai An, Jingyi Wang, Daoqin Li, Tao He, Gaoyan La, Ziliang Wang, Yuchen Han, Mingli Feng, Zheng Li and 1 more

Abstract read
In one paragraph

Article in Digital health. 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. 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

11 authors.

Ruilin ShiDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Shuai AnDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0003-4234-2634
Jingyi WangDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Daoqin LiDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Tao HeDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Gaoyan LaDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Ziliang WangDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Yuchen HanDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Mingli FengDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Zheng LiDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.
Jingbo ChengDepartment of Orthopedics, Xuanwu Hospital Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aims to systematically characterize the worldwide research profile of intelligent assistance operative adjuncts for unicompartmental knee arthroplasty, with particular attention to robotic-assisted systems, computer-assisted navigation, and patient-specific instruments (PSI). By clarifying the developmental trajectory of this field, the study seeks to inform future technological innovation and support evidence-based clinical translation. Methods: Studies concerning intelligent assistance operative adjuncts for UKA were identified through the Web of Science Core Collection. The final dataset comprised 296 articles, from which information on authorship, publication characteristics, contributing countries and institutions, source journals, and citation records was extracted. Statistical evaluation combined with visual mapping was used to examine trends in publication output and citation activity, major research themes, influential author clusters, institutional collaboration patterns, and journal distribution. Results: Between 2003 and 2025, the annual number of publications showed a continuous upward trajectory. The United States and the United Kingdom contributed the largest share of publications, while the Hospital for Special Surgery ranked first among institutions and Andrew D. Pearle was identified as the leading author by publication output. Among journals, The Journal of Arthroplasty received the highest citation frequency. Frequently occurring keywords included alignment, accuracy, outcome, and survivorship. Conclusion: During the past two decades, robotics have evolved from "technical validation" to "evidence-based optimization," becoming the dominant paradigm among intelligent assistance operative adjuncts. By contrast, navigation systems still exert substantial academic influence, whereas interest in PSI has declined. As alignment accuracy and survivorship are further validated, research has expanded toward long-term functional outcomes, patient satisfaction and cost-effectiveness, providing a basis for evaluation frameworks that integrate patient-reported outcome measures. Large-scale, robotic UKA are expected to further consolidate its role in evidence-based medicine and accelerate the integration of personalized, precision-based, and value-driven care for unicompartmental knee disease, ultimately benefiting a broader patient population.

Indexed as

computer-assisted surgeryknee osteoarthritisnavigationpartial knee arthroplastypatient-specificrobot-assisted

Identifiers

PMID42317387
PMCPMC13272994

What OpenQuestion holds

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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.