Evidence map›Paper›PMID 42058460›Full record

ArticleArthroplasty today2026

Robotic Assistance for Low-Volume Total Knee Arthroplasty Surgeons Is Associated With Comparable Perioperative Outcomes Related to Those of High-Volume Surgeons Using Conventional Techniques.

Albert H Lee, Om B Jahagirdar, John P Slevin, Lee E Rubin, Jonathan N Grauer

Abstract read
In one paragraph

Article in Arthroplasty today, 2026. 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

5 authors.

Albert H LeeDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA.
Om B JahagirdarDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA.
John P SlevinFrank H. Netter MD School of Medicine, Quinnipiac University, North Haven, CT, USA.
Lee E RubinDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA.
Jonathan N GrauerDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Studies have reported mixed utility of robotics in total knee arthroplasty (TKA). Separately, higher surgical volume has correlated with improved outcomes. The potential interplay of these variables has not been assessed. Methods: Patients undergoing conventional and robotic TKAs performed by low-volume and high-volume surgeons were identified from PearlDiver M170Ortho. Three matched comparisons were performed: conventional low-volume TKA (LV-TKA) vs robotic LV-TKA (R-LV-TKA), conventional high-volume TKA (C-HV-TKA) vs robotic high-volume TKA (R-HV-TKA), and C-HV-TKA vs R-LV-TKA. Aggregated 90-day adverse events (AEs), 5-year implant-related events, and revision rates were assessed. Results: Among low-volume surgeons, there were 8923 conventional LV-TKAs and 2235 R-LV-TKAs. R-LV-TKAs had lower odds of 90-day any (odds ratio [OR] 0.63), severe (OR 0.71), and minor (OR 0.66) AEs, driven by deep vein thrombosis (OR 0.47) and transfusion (OR 0.43) rates (all Conclusions: Robotic assistance was associated with lower odds of aggregated perioperative complications for low-volume and high-volume surgeons and with improved 5-year outcomes in high-volume robotic surgeons. Notably, robotic usage by low-volume surgeons was associated with outcomes comparable to nonrobotic high-volume surgeons, suggesting outcome gaps because of volume may be partially closed through robotics.

Indexed as

OutcomesPearlDiverRoboticsSurgeon case volumeTotal knee arthroplasty

Identifiers

PMID42058460
PMCPMC13122694

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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.