Evidence map›Paper›PMID 40970121›Full record

ArticleOrthopaedic journal of sports medicine2025

Biokinetic Profiles in Patellofemoral Pain Patients During a Step-Down Task: An Unsupervised Machine Learning Approach.

Leonardo Metsavaht, Gustavo Leporace, Felipe F Gonzalez, Eliane C Guadagnin, Enzo Mameri, Jonathan A Gustafson, Adam Yanke, Jorge Chahla, Marcus Luzo

Abstract read
In one paragraph

Article in Orthopaedic journal of sports medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Leonardo MetsavahtDepartamento de Diagnóstico por Imagem, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, State of São Paulo, Brazil.ORCID https://orcid.org/0000-0001-9263-1309
Gustavo LeporaceDepartment of Biomechanics, Instituto Brasil de Tecnologias da Saúde, Ipanema, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0002-7265-4658
Felipe F GonzalezDepartment of Biomechanics, Instituto Brasil de Tecnologias da Saúde, Ipanema, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0001-7142-6031
Eliane C GuadagninDepartment of Biomechanics, Instituto Brasil de Tecnologias da Saúde, Ipanema, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0003-3250-4134
Enzo MameriDepartamento de Diagnóstico por Imagem, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, State of São Paulo, Brazil.ORCID https://orcid.org/0000-0001-9642-4868
Jonathan A GustafsonDepartment of Orthopedic Surgery, Rush University Medical Center, Chicago, Illinois, USA.
Adam YankeDepartment of Sports Medicine, Midwest Orthopaedics at Rush, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0002-9601-4217
Jorge ChahlaDepartment of Sports Medicine, Midwest Orthopaedics at Rush, Chicago, Illinois, USA.
Marcus LuzoDepartamento de Diagnóstico por Imagem, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, State of São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is a lack of consensus regarding the optimal identification of motion-based subgroups (biokinetic profiles) of patients with patellofemoral pain (PFP) to guide effective management strategies. Purpose: To investigate different biokinetic profiles among patients with PFP during a step-down task and compare their clinical and physical characteristics. Study Design: Descriptive laboratory study. Methods: A total of 49 patients with PFP had their 3-dimensional kinematics assessed during a step-down task using an optoelectronic system. The variables analyzed were trunk and lower limb joint angles. Self-organizing maps and K-means clustering techniques were used to identify distinct biokinetic profiles. Clinical characteristics compared among profiles were hip/knee isometric strength and passive range of motion, descriptive characteristics, and patient-reported outcome measures. Results: Four biokinetic profiles were identified for the step-down task in patients with PFP. Profile 1 (Balanced Alignment Profile) exhibited a trunk-hip-knee aligned movement pattern, with increased knee flexion ( Conclusion: This study identified 4 clinically relevant biokinetic profiles of patients with PFP based on their kinematics during a step-down task. The principal clinical value of this study is the development of a functional classification for patients with PFP. Each profile exhibits characteristics that may provide valuable insights for clinicians to implement targeted interventions and improve patient care. Acknowledging the variability in movement profiles and their implications in PFP underscores the importance of moving beyond one-size-fits-all treatment strategies. Clinical Relevance: This study uncovers previously unknown movement-based biokinetic profiles in patellofemoral pain and identifies several modifiable clinical characteristics associated with each profile, which could be addressed through targeted interventions.

Indexed as

kinematicskneemusclepatellofemoral pain syndromestep-downstrength

Identifiers

PMID40970121
PMCPMC12441261

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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.