Evidence map›Paper›PMID 41438996›Full record

ArticleArthroplasty today2025

Robotic-Assisted Total Knee Arthroplasty With Metal Block Augmentation for Severe Varus Knee With Tibial Defect.

Yasushi Oshima, Tokifumi Majima

Abstract read
In one paragraph

Article in Arthroplasty today, 2025. 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. Article
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

2 authors.

Yasushi OshimaDepartment of Orthopaedic Surgery, Nippon Medical School, Tokyo, Japan.
Tokifumi MajimaDepartment of Orthopaedic Surgery, Nippon Medical School, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Total knee arthroplasty (TKA) for severe varus knee deformity with an uncontained medial tibial bone defect remains challenging for orthopaedic surgeons because additional bone resection to remove the bone defect area, application of metal augmentation, and adjustment of soft tissue balancing are technically difficult. Robotic technology has been demonstrated to achieve accurate bone resection and optimal soft tissue balancing in TKA. This study aimed to present a case series of the application of robotic-assisted TKA with metal augmentation for severe varus knee. Methods: Fifteen patients with 22 affected knees and postoperative follow-up of longer than 12 months were included in this study. Primary TKA with metal block augmentation was performed using robotic technology, and the implant positions, soft tissue balancing, and clinical outcomes were evaluated. Results: The visual analog scale score and knee injury and osteoarthritis outcome score were significantly improved. In addition, the lower extremity alignment and implant positions in the coronal and sagittal planes were radiographically accurate. Moreover, the medial knee stability was maintained, and lateral looseness diminished postoperatively. Conclusions: To resect the bone defect area perfectly the same as the depth of metal augmentations was technically difficult in conventional TKA. However, besides the primary bone resections, residual bone defect evaluation, soft tissue balancing adjustment, and additional bone resection to remove the bone defect area were performed easily and accurately using robotic technology. Therefore, robotic technology provides potential benefits for TKA with metal block augmentation in severe varus knees with medial tibial bone defects. Level of evidence: Level IV case series study.

Indexed as

Knee osteoarthritisMetal block augmentationRobotic technologyTibial bone defectTotal knee arthroplasty

Identifiers

PMID41438996
PMCPMC12720117

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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.