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The Use of Osteoconductive Bone Graft Substitutes in Orthopaedic Trauma

Hak, David J.·2007·Journal of the American Academy of Orthopaedic Surgeons

Abstract

Several bone graft substitutes are now available for use in augmenting bone healing following trauma. Many of these products are osteoconductive and are indicated for filling bone defects in conjunction with standard methods of internal and external fixation. Osteoconduction refers to a process in which the three-dimensional structure of a substance is conducive for the ongrowth and/or ingrowth of newly formed bone. Currently used bone graft substitutes that primarily offer osteoconductive properties include coralline hydroxyapatite, collagen-based matrices, calcium phosphate, calcium sulfate, and tricalcium phosphate. These products vary considerably in chemical composition, structural strength, and resorption or remodeling rates. Understanding these differences is important in selecting a bone graft substitute with the properties desired for a specific clinical situation. The limited number of clinical studies and lack of direct-comparison studies between these products require the surgeon to fully understand the properties of each product when choosing a bone graft substitute.

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Metadata

Authors
Hak, D. J.
Venue
Journal of the American Academy of Orthopaedic Surgeons
Published
2007-09
Volume
15
Issue
9
Pages
525-536
ISSN
1067-151X (ISSN-L)
OpenAlex
W2187063217
Cited by
244
References
0
FWCI
7.09
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Use of Osteoconductive Bone Graft Substitutes in Orthopaedic Trauma. https://app.cochat.ai/papers/10.5435/00124635-200709000-00003
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Hak, D. J. (2007). The Use of Osteoconductive Bone Graft Substitutes in Orthopaedic Trauma. Journal of the American Academy of Orthopaedic Surgeons. https://doi.org/10.5435/00124635-200709000-00003

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.