Evidence map›Paper›PMID 36042122›Full record

ArticleJournal of experimental orthopaedics2022

Introduction of ROSA robotic-arm system for total knee arthroplasty is associated with a minimal learning curve for operative time.

Scott M Bolam, Mei Lin Tay, Faseeh Zaidi, Raghavendra P Sidaginamale, Michael Hanlon, Jacob T Munro, A Paul Monk

Open access · goldAbstract read
In one paragraph

Article in Journal of experimental orthopaedics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 3 pooled it
8.7field-weighted citation impact, top 1% of its field
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

31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. High in-vivo accuracy of a novel robotic-arm-assisted system for total knee arthroplasty.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025
    Article
  18. Article
  19. Article
  20. Observational
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

7 authors at 3 institutions in 2 countries.

Scott M BolamDepartment of Orthopaedic Surgery, Auckland City Hospital, Auckland, New Zealand. s.bolam@auckland.ac.nz.ORCID http://orcid.org/0000-0002-0197-307X
Mei Lin TayDepartment of Surgery, Faculty of Medical and Health Sciences, University of Auckland, Building 502 20185 Park Road, Grafton, 1023, Auckland, New Zealand.
Faseeh ZaidiDepartment of Surgery, Faculty of Medical and Health Sciences, University of Auckland, Building 502 20185 Park Road, Grafton, 1023, Auckland, New Zealand.
Raghavendra P SidaginamaleDepartment of Orthopaedics, University Hospital of North Tees, Stockton on Tees, United Kingdom.
Michael HanlonDepartment of Orthopaedic Surgery, Auckland City Hospital, Auckland, New Zealand.
Jacob T MunroDepartment of Orthopaedic Surgery, Auckland City Hospital, Auckland, New Zealand.
A Paul MonkDepartment of Orthopaedic Surgery, Auckland City Hospital, Auckland, New Zealand.
University of Auckland · NZAuckland City Hospital · NZUniversity Hospital of North Tees · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe introduction of robotics for total knee arthroplasty (TKA) into the operating theatre is often associated with a learning curve and is potentially associated with additional complications. The purpose of this study was to determine the learning curve of robotic-assisted (RA) TKA within a multi-surgeon team.

methodsThis prospective cohort study included 83 consecutive conventional jig-based TKAs compared with 53 RA TKAs using the Robotic Surgical Assistant (ROSA) system (Zimmer Biomet, Warsaw, Indiana, USA) for knee osteoarthritis performed by three high-volume (> 100 TKA per year) orthopaedic surgeons. Baseline characteristics including age, BMI, sex and pre-operative Kellgren-Lawrence graded and Hip-Knee-Ankle Axis were well-matched between the conventional and RA TKA groups. Cumulative summation (CUSUM) analysis was used to assess learning curves for operative times for each surgeon. Peri-operative and delayed complications (infection, periprosthetic fracture, thromboembolism, and compromised wound healing) and revisions were reviewed.

resultsThe CUSUM analysis for operative time demonstrated an inflexion point after 5, 6 and 15 cases for each of the three surgeons, or 8.7 cases on average. There were no significant differences (p = 0.53) in operative times between the RA TKA learning (before inflexion point) and proficiency (after inflexion point) phases. Similarly, the operative times of the RA TKA group did not differ significantly (p = 0.92) from the conventional TKA group. There was no discernible learning curve for the accuracy of component planning using the RA TKA system. The average length of post-operative follow-up was 21.3 ± 9.0 months. There was one revision for instability in the conventional TKA group and none in the RA TKA group. There were no significant difference (p > 0.99) in post-operative complication rates between the conventional TKA and RA TKA groups.

conclusionsThe introduction of the RA TKA system was associated with a learning curve for operative time of 8.7 cases. Operative times between the RA TKA and conventional TKA group were similar. The short learning curve implies this RA TKA system can be adopted relatively quickly into a surgical team with minimal risks to patients.

Indexed as

Learning curveOperative timePersonalised robotic TKARobotically assisted systemROSA knee system

Identifiers

PMID36042122
PMCPMC9427173
OpenAlexW4293697355

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.