1. In Silico clinical trial to predict the efficacy of hip protectors for preventing hip fractures.
- Author
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Oliviero S, La Mattina AA, Savelli G, and Viceconti M
- Subjects
- Humans, Female, Aged, Male, Protective Devices, Accidental Falls prevention & control, Finite Element Analysis, Patient Compliance, Models, Biological, Femur physiopathology, Osteoporosis prevention & control, Hip Fractures prevention & control, Hip Fractures epidemiology, Computer Simulation
- Abstract
Osteoporosis is characterized by loss of bone mineral density and increased fracture risk. Reduction of hip fracture incidence is of major clinical importance. Hip protectors aim to attenuate the impact force transmitted to the femur upon falling, however different conclusions on their efficacy have been reported; some authors suggest this may be due to differences in compliance. The aim of this study was to apply an In Silico trial methodology to predict the effectiveness of hip protectors and its dependence on compliance. A cohort of 1044 virtual patients (Finite Element models of proximal femur) were generated. A Markov chain process was implemented to predict fracture incidence with and without hip protectors, by simulating different levels of compliance. At each simulated follow-up year, a Poisson distribution was randomly sampled to determine the number of falls sustained by each patient. Impact direction and force were stochastically sampled from a range of possible scenarios. The effect of wearing a hip protector was simulated by applying attenuation coefficients to the impact force (12.9 %, 19 % and 33.8 %, as reported for available devices). A patient was considered fractured when impact force exceeded the femur strength. Without hip protector, virtual patients experienced 66 ± 5 fractures in 10 years. Wearing the three devices, fracture incidence was reduced to 43 ± 4, 35 ± 4 and 17 ± 2 respectively, at full compliance. As expected, effectiveness was dependent on compliance. This In Silico trial technology can be applied in the future to test multiple interventions, optimise intervention strategies, improve clinical trial design and drug development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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