Diagnosing Fracture-Related Infections: Where Are We Now?

被引:0
作者
Stevenson, Madeleine C. [1 ]
Slater, Julia C. [2 ]
Sagi, H. Claude [3 ]
Bedoya, Federico Palacio [1 ]
Powers-Fletcher, Margaret, V [1 ,4 ]
机构
[1] Univ Cincinnati, Coll Med, Dept Internal Med, Cincinnati, OH 45221 USA
[2] Univ Cincinnati, Coll Med, Dept Surg, Cincinnati, OH USA
[3] Univ Cincinnati, Coll Med, Dept Orthopaed Surg, Cincinnati, OH USA
[4] Univ Cincinnati, Coll Med, Dept Pathol & Lab Med, Cincinnati, OH 45221 USA
关键词
fracture-related infection; osteitis; osteomyelitis; culture-negative infection; PROSTHETIC JOINT INFECTION; SONICATION; FIXATION; DITHIOTHREITOL; MANAGEMENT; SAMPLES; PCR; NONUNION; IMPROVE; SITES;
D O I
10.1128/jcm.02807-20
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Accurate diagnosis of fracture-related infection (FRI) is critical for preventing poor outcomes such as loss of function or amputation. Due to the multiple variables associated with FRI, however, accurate diagnosis is challenging and complicated by a lack of standardized diagnostic criteria. Limitations with the current gold standard for diagnosis, which is routine microbiology culture, further complicate the diagnostic and management process. Efforts to optimize the process rely on a foundation of data derived from prosthetic joint infections (PJI), but differences in PM and FRI make it clear that unique approaches for these distinct infections are required. A more concerted effort focusing on FRI has dominated more recent investigations and publications leading to a consensus definition by the American Orthopedics (AO) Foundation and the European Bone and Joint Infection Society (EBJIS). This has the potential to better standardize the diagnostic process, which will not only improve patient care but also facilitate more robust and reproducible research related to the diagnosis and management of FRI. The purpose of this mini-review is to explore the consensus definition, describe the foundation of data supporting current FRI diagnostic techniques, and identify pathways for optimization of clinical microbiology-based strategies and data.
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