Evidence map›Paper›PMID 41095464›Full record

ReviewMaterials (Basel, Switzerland)2025

Integration of Multi-Scale Predictive Tools of Bone Fragility: A Structural and Material Property Perspective.

Muhammad Ateeq, Laura Maria Vergani, Federica Buccino

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 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. Review
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.

Muhammad AteeqDepartment of Mechanical Engineering (DMEC), Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.
Laura Maria VerganiDepartment of Mechanical Engineering (DMEC), Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.ORCID 0000-0003-2353-7751
Federica BuccinoDepartment of Mechanical Engineering (DMEC), Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.ORCID 0000-0002-2224-6322

Funding

European Union 101120290Ministero dell'università e della ricerca 2022R4KA9X
6 · The paper itself

Abstract

Bone fragility represents a significant global health burden, characterized by the deterioration of bone strength, increased brittleness, and heightened fracture susceptibility. Osteoporosis substantially elevates the risk of fragility fractures, the principal clinical manifestation of the disease. Current diagnostic approaches, including biomedical imaging, bone strength assessment, and bone mineral density measurement, are closely linked to identifying bone fragility through various predictive models and tools. Although numerous studies have employed predictors to characterize fragility fractures, few have comprehensively examined the morpho-structural features of bone across multiple hierarchical scales, limiting the ability to fully elucidate the underlying mechanisms of bone fragility. This review summarizes recent advancements in predictive modeling and novel diagnostic tools, focusing on multiscale approaches for assessing bone fragility. We critically evaluate the translational potential of these tools for the early detection of fragility fractures and their clinical application in mitigating fracture risk. Moreover, this study discusses the integration of multiscale predictive methodologies, which promise to enhance early-stage bone fragility detection and potentially prevent severe fractures through timely intervention. Finally, the study reflects on current research limitations, addressing the challenges associated with multiscale predictive modeling of bone fragility, and proposes future directions to refine these tools to improve the accuracy and utility of fragility fracture prediction and prevention strategies.

Indexed as

fragility fracturesmultiscaleosteoporosispredictive tools

Identifiers

PMID41095464
PMCPMC12525592

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Registered trials

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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.