Evidence map›Paper›PMID 41230427›Full record

ArticleApplied bionics and biomechanics2025

Tailored Multibody Tibiofemoral Joint Model for Precision Care.

Shavkat Nadir Kuchimov, Mehmed Ozkan, Yener Temelli

Abstract read
In one paragraph

Article in Applied bionics and biomechanics, 2025. 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

3 authors.

Shavkat Nadir KuchimovInstitute of Biomedical Engineering, Bogazici University, Istanbul, Türkiye, boun.edu.tr.ORCID https://orcid.org/0000-0003-1481-8447
Mehmed OzkanInstitute of Biomedical Engineering, Bogazici University, Istanbul, Türkiye, boun.edu.tr.ORCID https://orcid.org/0000-0003-2492-8113
Yener TemelliDepartment of Orthopedics, American Outpatient Medical Center, American Hospital, Istanbul, Türkiye, amerikanhastanesi.org.ORCID https://orcid.org/0009-0005-5185-2152

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knee motion involves intricate coordination among various anatomical structures. Effective treatment of knee pathologies requires precise identification of deformities and accurate surgical interventions, which often involve rapid tissue modification based on established knowledge. However, motion disorders are typically detected long after surgery. To address this, a simulation environment is proposed to plan and analyze surgical impacts on knee motion. Comprehensive knee joint modeling is crucial for a successful simulation. Clinically accepted movement procedures based on passive knee motion make tibiofemoral articulation modeling sufficient. Proposed model tibiofemoral articulation, incorporating 15 ligaments, tibial and femoral bones, and cartilages. Ligaments' tensile, bones', and cartilages' contact forces (CFs) define internal force interactions. Anatomical structures, their shapes, positions, and attachment points are identified from MRI, ensuring patient-specific modeling. Simulation results are compared to cadaver data using passive knee motion. Two rotational and three translational dependent joint motions (JMs) are compared pairwise. The results are highly correlated with the clinical benchmark. Pearson's correlation show a strong association between experimental and simulated passive knee flexions (PKFs;

Indexed as

knee contact surfacesknee joint modelpatient specific ligament attachmentspatient specific ligament force modelingpatient specific modelsurgical planningtibiofemoral joint model

Identifiers

PMID41230427
PMCPMC12602475

What OpenQuestion holds

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LicenceCC BY
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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.