ArticleDigital health
Advances in intelligent assistance operative adjuncts for unicompartmental knee arthroplasty: A bibliometric analysis of research trends and developments.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Global research landscape and trends in robot-assisted unicompartmental knee arthroplasty: a bibliometric analysis.Journal of robotic surgery · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
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
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What OpenQuestion holds
Registered trials
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.