Evidence map›Paper›PMID 40688002›Full record

ArticleJournal of orthopaedics2025

Discrepancy between predicted and actual soft tissue balance in robot-assisted total knee arthroplasty.

Hiroshi Inui, Haruhiko Nakamura, Ryota Takei, Masaki Uchida, Kei Satou, Tetsu Yamashita, Risa Matsumoto

Abstract read
In one paragraph

Article in Journal of orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

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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 synthesis or guideline pooled it.

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4 · The record

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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

7 authors.

Hiroshi InuiSaitama Medical Center, Saitama Medical University, Japan.
Haruhiko NakamuraSaitama Medical Center, Saitama Medical University, Japan.
Ryota TakeiSaitama Medical Center, Saitama Medical University, Japan.
Masaki UchidaSaitama Medical Center, Saitama Medical University, Japan.
Kei SatouSaitama Medical Center, Saitama Medical University, Japan.
Tetsu YamashitaSaitama Medical Center, Saitama Medical University, Japan.
Risa MatsumotoSaitama Medical Center, Saitama Medical University, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Achieving optimal soft tissue balance in total knee arthroplasty (TKA) is vital for successful clinical outcomes. Robotic-assisted TKA predicts postoperative soft tissue balance based on preoperative varus-valgus stress. Nevertheless, these predictions may not always be accurate due to changes in soft tissue balance after osteotomy and variability in manual stress application. Therefore, this study was conducted to investigate the differences between predicted and final soft tissue balance and determine the factors affecting these differences. Methods: In 112 robotic-assisted TKA cases, the predicted joint gaps at extension (10°) and flexion (90°) were evaluated intraoperatively before osteotomy, and the final joint gaps were evaluated after final implantation under manual varus-valgus stress. Differences between the predicted and final gaps (DPFG) e calculated, and correlations between DPFG and preoperative parameters were analyzed. Results: The final joint gaps were significantly larger than the predicted gaps in both extension and flexion (P < 0.001). A greater preoperative hip-knee-ankle angle and increased flexion angle were associated with smaller DPFG in the medial compartment. Conversely, severe preoperative flexion contracture correlated with larger DPFG in extension in the lateral compartment. Conclusion: Soft tissue balance predictions in robotic-assisted TKA are not always accurate, with the final joint gaps tending to be larger than predicted. Preoperative limb alignment and knee range of motion influence these differences, emphasizing the need for surgeons to interpret robotic predictions cautiously. Adjustments during surgery may be required to optimize soft tissue balance.

Identifiers

PMID40688002
PMCPMC12270604

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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.