Evidence map›Paper›PMID 37159822›Full record

ReviewJournal of orthopaedics2023

Robotic-assisted knee replacement surgery & infection: A historical foundation, systematic review and meta-analysis.

Siddarth Raj, Harroop Bola, Thomas York

Abstract readReview
In one paragraph

Review in Journal of orthopaedics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Risk of periprosthetic joint infection within 1 year following robotic-assisted versus conventional primary total knee arthroplasty: a propensity-score-matched cohort study.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2026
    Article
  5. Review
  6. Article
  7. Review
  8. 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

3 authors.

Siddarth RajUniversity Hospital Coventry and Warwickshire NHS Trust, Coventry, UK.
Harroop BolaImperial College School of Medicine, Imperial College London, London, UK.
Thomas YorkImperial College School of Medicine, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: An increasing proportion of Knee arthroplasty is performed using robotic-assisted surgical techniques. This study sought to use a meta-analytical approach to establish summary rates of surgical site infection in robotic-assisted procedures and compare the rate of deep infections to those seen in conventional knee arthroplasty. Methods: This study performed a literature search across four online databases to establish a summary rate of surgical site infection across two categories: deep infection and superficial and pin-site infections. This was processed with the aid of a bespoke data-extraction tool. Risk of Bias analysis was performed using the Cochrane RoB2 tool. Meta-analysis was then performed with tests for heterogeneity and a DerSimonian-Laird random effects model. Results: A total of 17 studies were identified as appropriate for inclusion in the meta-analysis. The summary rate of overall surgical site infections within one year of robotic knee arthroplasty was found to be 0.568% (SE = 0.183, 95% CI = 0.209-0.927). Deep infections fell to 0.154% (SE = 0.069, 95% CI = 0.018-0.290) and to 0.347% (SE = 0.109, 95% CI = 0.133-0.561) in superficial and pin-site infections. Conclusion: The surgical site infection rates were found to be low across robotic knee arthroplasty. Further research is required to prove its superiority compared to the conventional, non-robotic technique.

Indexed as

ArthroplastyComplicationinfectionKneeMeta-analysisRobotic-assisted

Identifiers

PMID37159822
PMCPMC10163613

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Registered trials

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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.