Dataset Information

Functional Imaging in Diagnostic of Orthopedic Implant-Associated Infections.

ABSTRACT: Surgeries' sterile conditions and perioperative antibiotic therapies decrease implant associated infections rates significantly. However, up to 10% of orthopedic devices still fail due to infections. An implant infection generates a high socio-economic burden. An early diagnosis of an infection would significantly improve patients' outcomes. There are numerous clinical tests to diagnose infections. The "Gold Standard" is a microbiological culture, which requires an invasive sampling and lasts up to several weeks. None of the existing tests in clinics alone is sufficient for a conclusive diagnosis of an infection. Meanwhile, there are functional imaging modalities, which hold the promise of a non-invasive, quick, and specific infection diagnostic. This review focuses on orthopedic implant-associated infections, their pathogenicity, diagnosis and functional imaging.

SUBMITTER: Potapova I

PROVIDER: S-EPMC4665528 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Functional Imaging in Diagnostic of Orthopedic Implant-Associated Infections.

Potapova Inga I

Diagnostics (Basel, Switzerland) 20131021 4

Surgeries' sterile conditions and perioperative antibiotic therapies decrease implant associated infections rates significantly. However, up to 10% of orthopedic devices still fail due to infections. An implant infection generates a high socio-economic burden. An early diagnosis of an infection would significantly improve patients' outcomes. There are numerous clinical tests to diagnose infections. The "Gold Standard" is a microbiological culture, which requires an invasive sampling and lasts up ...[more]

PMID: 26824928

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Project description:The diagnosis of orthopedic implant-associated infections (OIAIs) caused by the slow-growing anaerobic bacterium Cutibacterium acnes is challenging. The mild clinical presentations of this low-virulent bacterium along with its ubiquitous presence on human skin and human-dominated environments often make it difficult to differentiate true infection from contamination. Previous studies have applied C. acnes phylotyping as a potential avenue to distinguish contamination from infection; several studies reported a prevalence of phylotypes IB [corresponding to type H in the single-locus sequence typing (SLST) scheme] and II (SLST type K) in OIAIs, while a few others found phylotype IA1 (more specifically SLST type A) to be abundant. However, phylotype determination has mainly been done in a culture-dependent manner on randomly selected C. acnes isolates. Here, we used a culture-independent amplicon-based next-generation sequencing (aNGS) approach to determine the presence and relative abundances of C. acnes phylotypes in clinical OIAI specimens. As amplicon, the SLST target was used, a genomic fragment that is present in all C. acnes strains known to date. The aNGS approach was applied to 30 sonication fluid (SF) samples obtained from implants removed during revision surgeries, including 17 C. acnes culture-positive and 13 culture-negative SF specimens. In 53% of the culture-positive samples, SLST types were identified: relative abundances were highest for K-type C. acnes, followed by H- and D-type C. acnes. Other types, including A- and C-type C. acnes that are more prevalent on human skin, had low relative abundances. The aNGS results were compared with, and confirmed by a culture-dependent approach, which included the isolation, whole genome sequencing (WGS) and phylotyping of 36 strains of C. acnes obtained from these SF samples. Besides serving as a powerful adjunct to identify C. acnes phylotypes, the aNGS approach could also distinguish mono- from heterotypic infections, i.e., infections caused by more than one phylotype of C. acnes: in eight out of nine culture-positive SF samples multiple C. acnes types were detected. We propose that the aNGS approach, along with the patient's clinical information, tissue and SF cultures and WGS, could help differentiate C. acnes contamination from true infection.

Dataset Information

Functional Imaging in Diagnostic of Orthopedic Implant-Associated Infections.

Publications

Functional Imaging in Diagnostic of Orthopedic Implant-Associated Infections.

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