Evidence map›Paper›PMID 42771179›Full record

ArticleArchives of orthopaedic and trauma surgery2026

Identification of biomechanical alterations associated with nonunion after tibial shaft fractures using musculoskeletal simulation based on motion capture and instrumented insole data.

Tabea Wahl, Bergita Ganse, Elke Warmerdam, Frank Hildebrand, Ulf Krister Hofmann, Maximilian Praster

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Article in Archives of orthopaedic and trauma 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.

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5 · Who and what money

Authors and funding

6 authors.

Tabea WahlDepartment of Orthopaedics, Trauma and Reconstructive Surgery, Universitätsklinikum Aachen, Aachen, Germany. twahl@ukaachen.de.
Bergita GanseWerner Siemens-Endowed Chair for Innovative Implant Development (Fracture Healing), Departments and Institutes of Surgery, Saarland University, Saarbrücken, Germany.ORCID https://orcid.org/0000-0002-9512-2910
Elke WarmerdamWerner Siemens-Endowed Chair for Innovative Implant Development (Fracture Healing), Departments and Institutes of Surgery, Saarland University, Saarbrücken, Germany.
Frank HildebrandDepartment of Orthopaedics, Trauma and Reconstructive Surgery, Universitätsklinikum Aachen, Aachen, Germany.
Ulf Krister HofmannDepartment of Orthopaedics, Trauma and Reconstructive Surgery, Universitätsklinikum Aachen, Aachen, Germany.
Maximilian PrasterDepartment of Orthopaedics, Trauma and Reconstructive Surgery, Universitätsklinikum Aachen, Aachen, Germany.ORCID https://orcid.org/0000-0002-6346-0253

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMusculoskeletal simulations based on gait analysis data provide access to parameters such as joint reaction forces, muscle forces, and push-off moments, which cannot directly be measured in clinical practice. Applying these methods may help evaluate weight-bearing patterns and identify mechanical risk factors associated with the development of nonunion. This study aimed to investigate differences in the longitudinal development of forces in the musculoskeletal system between cases with and without union in tibial shaft fractures. MATERIALS AND

methodsLongitudinal 3D marker-based motion capture and instrumented insole data of thirteen patients (8 union; 5 nonunion) with tibial shaft fractures were used to generate individualized musculoskeletal models using the AnyBody™ software.

resultsIn a linear mixed-effects model, the fractured limb showed impaired biomechanical parameters compared with the contralateral limb, including knee joint reaction forces (KJRFs), muscle forces, and push-off moments (all p < 0.001). During follow-up, parameters of the fractured leg increased over time, including KJRFs (p = 0.011), muscle forces (p ≤ 0.030), and ground reaction force (p = 0.008). The union group exhibited greater muscle forces, particularly in the soleus (p = 0.014) and gastrocnemius muscles (p = 0.049). The nonunion group exhibited significantly greater asymmetry between healthy and fractured leg than the union group in ground reaction force (β = 0.368, p = 0.011), KJRFs (β = 0.364, p = 0.028), and push-off moment (β = 0.457, p = 0.028). In additional time point-specific analyses no significant differences were found at 6 and 12 weeks.

conclusionBiomechanical loading patterns differed between patients with union and nonunion throughout fracture healing, with greater between-limb asymmetries in push-off moment, joint reaction forces, and plantar flexor muscle forces in the nonunion group. Larger studies are required to validate these findings using the proposed workflow.

Indexed as

Fractures, UnunitedTibial FracturesAdultBiomechanical PhenomenaFemaleFoot OrthosesGait AnalysisHumansMaleMiddle AgedMotion CaptureWeight-BearingFracture healingGait asymmetryLower limb biomechanicsWeight bearing

Identifiers

PMID42771179
PMCPMC13597656

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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.