ArticleJournal of robotic surgery2024
Does robotic-assisted unicompartmental knee arthroplasty restore native joint line more accurately than with conventional instruments?
Article in Journal of robotic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Robotic-Assisted unicompartmental knee arthroplasty restores native joint line height and reduces alignment outliers.International orthopaedics · 2025Pooled it
- Accuracy of ROSAJournal of clinical medicine · 2026Article
- Image-based robotics enhance precision and efficiency in lateral UKA: A comparative study of 135 UKAs.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
- Short-term outcomes of robotic versus conventional unicompartmental knee arthroplasty: evidence from a national database.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2025Article
- Image-Based Robotic Unicompartmental Knee Arthroplasty Results in Fewer Radiologic Outliers with No Impact on Revision Rates Compared to Imageless Systems: A Systematic Review.Journal of clinical medicine · 2025Review
- High accuracy of component positioning and restoration of lower limb alignment using robotic medial unicompartmental knee arthroplasty.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study's primary aim is the restoration of native joint line in patients having robotic-assisted unicondylar knee arthroplasty and conventional unicondylar knee arthroplasty. Literature in the past has demonstrated that reducing the joint line can result in greater failure rates. This is a prospective cohort investigation of patients who had medial UKA between March 2017 and March 2022.All patient's pre-operative and post-operative radiological joint line assessments were examined by two observers by Weber's methods. Robotic-assisted UKA performed with hand-held image-free robots was compared to conventional UKA groups. The distal position of the femoral component was higher in Group B utilizing conventional tools than in Group A employing robotic-assisted UKA. This positional difference was statistically significant. The mean difference among the pre-operative and post-operative joint lines in Group A was 1.6 ± 0.49 (range 0.8 mm-2.4 mm), while it was 2.47 ± 0.51 (range 1.6 mm-3.9 mm) (p 0.005) in Group B. In Group A, a greater percentage of the subjects (64%) attained a femoral component position within two millimeters from the joint line, whereas just 18% in Group B did. When compared with the conventional UKA technique, the meticulous attention to detail and planning for ligament rebalancing when using the robotic-assisted UKA technique not solely enhance surgical precision for implant placing but additionally provides excellent native joint line restoration and balancing. For validation of its longevity and survivability, the cohort must be tracked for a longer period of time.
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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.