Evidence map›Paper›PMID 40895918›Full record

ReviewCureus2025

Knee Arthroplasty Types: An Educational Framework for Multidisciplinary Healthcare Teams.

Uday Mahajan, Meraj Akhtar, Baijaeek Sain, Arnab Sain

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Uday MahajanTrauma and Orthopaedics, Queen Elizabeth Hospital Birmingham, Birmingham, GBR.
Meraj AkhtarTrauma and Orthopaedics, Lincoln County Hospital, Lincoln, GBR.
Baijaeek SainTrauma and Orthopaedics, Royal Berkshire NHS Foundation Trust, Reading, GBR.
Arnab SainTrauma and Orthopaedics, Worthing Hospital, Worthing, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knee arthroplasty is a widely performed surgical procedure that significantly improves the quality of life for patients with advanced knee joint diseases. However, many multidisciplinary healthcare professionals lack a clear understanding of the types and subtypes of knee arthroplasty, which is essential for effective perioperative care and rehabilitation planning. This narrative review categorises knee arthroplasty into three main types: total knee arthroplasty, partial knee arthroplasty, and revision knee arthroplasty. Total knee arthroplasty remains the most common procedure, with subtypes based on implant constraint, fixation method, bearing surface, alignment philosophy, surgical approach, and technological aids. Partial knee arthroplasty includes unicompartmental and patellofemoral replacements, offering faster recovery and more natural knee kinematics in appropriately selected patients, although with higher revision rates. Revision knee arthroplasty addresses failed implants using one-stage or two-stage procedures with specialised components such as constrained condylar and hinged implants, stem extensions, augments, and megaprostheses, but carries higher surgical complexity and complication risks. This educational framework aims to enhance multidisciplinary understanding of knee arthroplasty procedures, supporting better communication, patient education, and rehabilitation planning. Future research should validate its impact in educational settings and explore ongoing innovations in implant designs and surgical technologies to optimise patient outcomes.

Indexed as

knee arthroplastymultidisciplinary educationpartial knee replacementrevision total joint arthroplastytotal knee replacement (tkr)

Identifiers

PMID40895918
PMCPMC12398274

What OpenQuestion holds

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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.