Evidence map›Paper›PMID 41953492›Full record

ArticleFrontiers in surgery2026

Kinematically aligned total knee arthroplasty via subvastus approach using the Mako® 2.0 total knee system: a surgical technique.

Teddy Cheong, Jonathan Yeo, Charles Kon Kam King, Ing How Moo

Abstract read
In one paragraph

Article in Frontiers in surgery, 2026. 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

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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

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.

Teddy CheongOrthopaedic Surgery, Changi General Hospital, Singapore, Singapore.
Jonathan YeoOrthopaedic Surgery, Changi General Hospital, Singapore, Singapore.
Charles Kon Kam KingOrthopaedic Surgery, Changi General Hospital, Singapore, Singapore.
Ing How MooOrthopaedic Surgery, Changi General Hospital, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Total knee arthroplasty (TKA) is among the most commonly utilised and cost-effective surgical musculoskeletal procedures, with up to 700,000 TKAs performed annually in the United States alone. Traditionally, the standard approach in TKA has been for mechanical alignment (MA) which provides equal medial and lateral gaps in extension and flexion. However, there remains a high rate of patient dissatisfaction with their TKA. Kinematic alignment (KA) aims to restore pre-arthritic alignment by placing the femoral and tibial components in alignment with the three kinematic axes of the knee while avoiding soft tissue releases. KA TKAs have produced favourable clinical outcomes and implant survivorship that are comparable and even superior to mechanical alignment TKAs in some studies. As technology advances, robotic-assisted systems such as the Mako® 2.0 Total Knee system are increasing in popularity due to its benefit of surgical precision and accuracy. To perform a KA TKA effectively, accurate bone resections, particularly the femur aspect, are required to ensure that the pre-arthritic alignment and joint line are restored. The Mako® 2.0 Total Knee system provides accurate and precise assistance in performing a KA TKA through the combination of meticulous computer tomography-based pre-operative planning and AccuStop™ haptic technology. Currently, there is a lack in existing literature that describes the technique of performing a KA TKA while using Mako® Total Knee 2.0 system. In this article, we describe specific procedures for pre-operative planning, intra-operative steps, and soft tissue evaluation using the Mako® 2.0 Total Knee system to perform a KA TKA. The aim is to describe a practical and efficient workflow that integrates kinematic alignment principles with the precision, reproducibility, and intraoperative feedback provided by robotic assistance.

Indexed as

arthroplastykinematic alignmentkneeMako®robotic

Identifiers

PMID41953492
PMCPMC13055504

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LicenceCC BY
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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.