Evidence map›Paper›PMID 41158195›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Joint modeling and marker set selection significantly influence functional biomechanics in end-stage knee osteoarthritis: evidence from the sit-to-stand task.

Giovanni Spallone, Letizia Mancini, Arianna Carnevale, Stefano Campi, Emiliano Schena, Pieter D'Hooghe, Michael T Hirschmann, Rocco Papalia, Umile Giuseppe Longo

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06634654 (An Artificial Intelligence-based Approach in Total Knee Arthroplasty), which is not on this map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

NCT06634654 narecruitingnot on this map

An Artificial Intelligence-based Approach in Total Knee Arthroplasty: From Inflammatory Responses to Personalized Medicine

TypeinterventionalSponsorFondazione Policlinico Universitario Campus Bio-MedicoRan2024 to 2029Enrolled197ConditionsKnee OsteoarthritisArmsTotal Knee Arthroplasty, Multifaceted diagnostic assessments, Follow-ups, Genetic screening
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

9 authors.

Giovanni SpalloneFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Letizia ManciniFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Arianna CarnevaleFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Stefano CampiFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Emiliano SchenaFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Pieter D'HoogheDepartment of Orthopaedic Surgery and Sports medicine, Aspetar Hospital, Doha, Qatar.
Michael T HirschmannUniversity Clinic for Orthopedic Surgery and Traumatology, Kantonsspital Baselland, Bruderholz, Switzerland.
Rocco PapaliaFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Umile Giuseppe LongoFondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The sit-to-stand (STS) movement represents a mechanically demanding task, particularly informative in patients with knee osteoarthritis. While three-dimensional optoelectronic motion capture is the gold standard for analyzing joint biomechanics, the influence of protocol selection remains poorly characterized in the context of STS. This study investigated protocol-induced variability in knee kinematics and kinetics by evaluating two widely used marker sets: the anatomical-based IOR and the cluster-based CAST, each combined with either inverse kinematics or a six degrees-of-freedom joint model. Materials and Methods: Twenty-four patients (mean age of 67 ± 5 years and BMI of 28.9 ± 3.8 kg/m Results: Results revealed substantial variability across protocols, with the highest discrepancies observed in the sagittal plane: peak MAV reached 23.99° for knee flexion angle and 0.24 Nm/kg for knee flexion moment. Frontal and transverse parameters also showed clinically meaningful differences, particularly for knee adduction and internal rotation angles, with MAD values exceeding established thresholds. Differences were amplified when both markers set, and modeling strategy varied. In this context, cluster-based configurations showed reduced variability. SPM analyses revealed temporally localized differences, particularly at the initiation and final stabilization phases of the movement. Conclusion: These findings emphasize the critical role of protocol selection in motion analysis and its direct impact on the interpretation of knee biomechanics during functional tasks, highlighting the importance of adopting consistent and robust methodological frameworks to ensure clinical reliability and cross-study comparability. Clinical Trial Registration: https://clinicaltrials.gov/, identifier NCT06634654.

Indexed as

calibration anatomical systems techniqueIstituto Ortopedico Rizzolijoint modelingknee biomechanicsknee osteoarthritissit-to-stand

Identifiers

PMID41158195
PMCPMC12554728

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Registered trials

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.