Evidence map›Paper›PMID 41910754›Full record

ArticleBiomechanics and modeling in mechanobiology2026

A simple personalised prediction model for hip fracture risk based on mechanistic parameters.

Christina Wapp, Yvan Gugler, Paula Cameron, Alice Dudle, Daniela Frauchiger, Maria Papageorgiou, Emmanuel Biver, Serge Ferrari, Kurt Lippuner, Philippe Zysset

Abstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 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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0citing papers in PubMed
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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

10 authors.

Christina WappARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland. christina.wapp@unibe.ch.ORCID http://orcid.org/0009-0006-2476-2941
Yvan GuglerARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0009-0007-1494-3009
Paula CameronARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0009-0008-1713-7106
Alice DudleARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0001-8929-1454
Daniela FrauchigerARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0003-2583-9702
Maria PapageorgiouDivision of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Emmanuel BiverDivision of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.ORCID http://orcid.org/0000-0001-6174-1951
Serge FerrariDivision of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.ORCID http://orcid.org/0000-0002-1372-4417
Kurt LippunerARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-7195-3779
Philippe ZyssetARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-4712-7047

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 183584
6 · The paper itself

Abstract

Fragility hip fractures in older adults are a major burden for the individual and the society, as they result in increased morbidity, mortality and substantial health care expenditure. Most fragility hip fractures are caused by falls, resulting in an impact on the postero-lateral aspect of the hip, inducing a force that exceeds the femoral bone strength. The risk of fracture depends on the rate of falling, the fall-induced impact force, and the femoral bone strength. This article presents the framework of a novel fragility hip fracture risk calculator based on a combined mechanistic and stochastic modelling approach. The model integrates the stochastic aspects of a fall and its dynamics together with a 1D mechanical model predicting the impact force in the hip to calculate a one-year absolute fracture risk. The required input parameters are based on QCT images, but can be substituted with more accessible anthropometric and densitometric data. To demonstrate how the parameters are extracted from clinical data and how the model is calibrated, data from the AFFIRM-CT cohort were used. A sensitivity analysis was conducted, confirming that the fall rate, the trochanteric soft tissue thickness and the bone strength are the dominating parameters influencing the risk of fragility hip fractures. Furthermore, output variables such as the predicted impact velocity and impact force aligned well with experimental data. Thus, the model is able to reflect observations from empirical data, indicating that it can capture the intrinsic aspects that define the risk of fragility hip fractures.

Indexed as

Hip FracturesModels, BiologicalAccidental FallsAgedBiomechanical PhenomenaFemaleHumansMalePrediction AlgorithmsRisk FactorsFallsFracture riskFragility fractureHip fractureImpact forcePrediction

Identifiers

PMID41910754
PMCPMC13675280

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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.