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A Modern Approach to Biofilm-Related Orthopaedic Implant Infections

Overview of attention for book
Attention for Chapter 11: The Role of Biomarkers for the Diagnosis of Implant-Related Infections in Orthopaedics and Trauma
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Chapter title
The Role of Biomarkers for the Diagnosis of Implant-Related Infections in Orthopaedics and Trauma
Chapter number 11
Book title
A Modern Approach to Biofilm-Related Orthopaedic Implant Infections
Published in
Advances in experimental medicine and biology, January 2017
DOI 10.1007/5584_2017_11
Pubmed ID
Book ISBNs
978-3-31-952273-9, 978-3-31-952274-6
Authors

Abtin Alvand, Maryam Rezapoor, Javad Parvizi, Alvand, Abtin, Rezapoor, Maryam, Parvizi, Javad

Abstract

Diagnosis of implant-related (periprosthetic joint) infections poses a major challenge to infection disease physicians and orthopaedic surgeons. Conventional diagnostic tests continue to suffer from issues of accuracy and feasibility. Biomarkers are used throughout medicine for diagnostic and prognostic purposes, as they are able to objectively determine the presence of a disease or a biological state. There is increasing evidence to support the measurement of specific biomarkers in serum and/or synovial fluid of patients with suspected periprosthetic joint infections. Promising serum biomarkers include interleukin (IL)-4, IL-6, tumour necrosis factor (TNF)-α, procalcitonin, soluble intercellular adhesion molecule 1 (sICAM-1), and D-dimer. In addition to c-reactive protein and leucocyte esterase, promising biomarkers that can be measured in synovial fluid include antimicrobial proteins such as human β-defensin (HBD)-2 and human β-defensin (HBD)-3, and cathelicidin LL-37, as well as several interleukins such as IL-1β, IL-6, IL-8, IL-17, TNF- α, interferon-δ, and vascular endothelial growth factor.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 14%
Student > Doctoral Student 4 11%
Student > Postgraduate 4 11%
Other 3 8%
Student > Ph. D. Student 3 8%
Other 7 19%
Unknown 10 28%
Readers by discipline Count As %
Medicine and Dentistry 15 42%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Biochemistry, Genetics and Molecular Biology 2 6%
Immunology and Microbiology 2 6%
Chemical Engineering 1 3%
Other 3 8%
Unknown 11 31%