Prediction of Hip Fracture Can Be Significantly Improved by a Single Biomedical Indicator
| Autor: | Angelo Cappello, Debora Testi, Saverio Gnudi, Marco Viceconti |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Bone density
Finite Element Analysis Population Biomedical Engineering Poison control Models Biological Sensitivity and Specificity Femoral Neck Fractures Reference Values Risk Factors medicine Humans education Aged Retrospective Studies Femoral neck Orthodontics Bone mineral education.field_of_study Hip fracture business.industry Reproducibility of Results Bayes Theorem medicine.disease medicine.anatomical_structure Fracture (geology) Female Stress Mechanical business Biomedical engineering |
| Zdroj: | Annals of Biomedical Engineering. 30:801-807 |
| ISSN: | 0090-6964 |
| DOI: | 10.1114/1.1495866 |
| Popis: | Femoral neck fractures are a relevant clinical and social problem. The aim of this study was to improve the prediction of patients at-risk of femoral neck fracture with respect to the current densitometric-based methods. In particular, finite element models were used to assess the prediction accuracy obtained by combining together data from the bone density distribution, the proximal femur anatomy, and the fall-related loading conditions. Two-dimensional finite element models were developed based on dual energy x-ray absorptiometry data. A population of 93 elder Caucasian women (half of them reporting a femoral neck fracture) were retrospectively classified both using the standard clinical protocol and Bayes' linear classifiers. This study showed that the bone mineral density in the femoral neck region dominated the fracture event (65% accuracy). Adding the subject's height and the neck-shaft angle to the bone density increased the accuracy to 77%. The classification accuracy was further improved to 82% by including the peak principal tensile strain obtained from the finite element analyses. This research demonstrated that adding one single biomechanical indicator to the standard clinical measurements improves the identification of patients at-risk of femoral neck fracture. © 2002 Biomedical Engineering Society. PAC2002: 8759Ls, 8719Rr |
| Databáze: | OpenAIRE |
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