Medical device-associated infections account for a large proportion of hospital-acquired infections. A variety of opportunistic pathogens can cause implant infections, depending on the type of the implant and on the anatomical site of implantation. The success of these versatile pathogens depends on rapid adhesion to virtually all biomaterial surfaces and survival in the hostile host environment. Biofilm formation on implant surfaces shelters the bacteria and encourages persistence of infection. Furthermore, implant-infecting bacteria can elude innate and adaptive host defences as well as biocides and antibiotic chemotherapies. In this Review, we explore the fundamental pathogenic mechanisms underlying implant infections, highlighting orthopaedic implants and Staphylococcus aureus as a prime example, and discuss innovative targets for preventive and therapeutic strategies.

Implant infections: adhesion, biofilm formation and immune evasion

Prosthetic joint infection (PJI) is a tremendous burden for individual patients as well as the global health care industry. While a small minority of joint arthroplasties will become infected, appropriate recognition and management are critical to preserve or restore adequate function and prevent excess morbidity. In this review, we describe the reported risk factors for and clinical manifestations of PJI. We discuss the pathogenesis of PJI and the numerous microorganisms that can cause this devastating infection. The recently proposed consensus definitions of PJI and approaches to accurate diagnosis are reviewed in detail. An overview of the treatment and prevention of this challenging condition is provided.

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Prosthetic Joint Infection

Prosthetic Joint Infections

Although prosthetic joint infection (PJI) is a rare event after arthroplasty, it represents a significant complication that is associated with high morbidity, need for complex treatment, and substantial healthcare costs. An accurate and rapid diagnosis of PJI is crucial for treatment success. Current diagnostic methods in PJI are insufficient with 10-30% false-negative cultures. Consequently, there is a need for research and development into new methods aimed at improving diagnostic accuracy and speed of detection. In this article, we review available conventional diagnostic methods for the diagnosis of PJI (laboratory markers, histopathology, synovial fluid and periprosthetic tissue cultures), new diagnostic methods (sonication of implants, specific and multiplex PCR, mass spectrometry) and innovative techniques under development (new laboratory markers, microcalorimetry, electrical method, reverse transcription [RT]-PCR, fluorescence in situ hybridization [FISH], biofilm microscopy, microarray identification, and serological tests). The results of highly sensitive diagnostic techniques with unknown specificity should be interpreted with caution. The organism identified by a new method may represent a real pathogen that was unrecognized by conventional diagnostic methods or contamination during specimen sampling, transportation, or processing. For accurate interpretation, additional studies are needed, which would evaluate the long-term outcome (usually >2 years) with or without antimicrobial treatment. It is expected that new rapid, accurate, and fully automatic diagnostic tests will be developed soon.

Epidemiology and new developments in the diagnosis of prosthetic joint infection

MALDI-TOF Mass Spectrometry for Microorganism Identification

Hospital-acquired infections associated with implanted medical devices are most commonly caused by staphylococci. Current methods of species identification are slow, costly, and sometimes unreliable. We evaluated the ability of a Bruker Daltonics Microflex MALDI-TOF/MS in conjunction with MALDI Biotyper software to identify 158 characterized staphylococcal isolates from prosthetic joint infections, including 36 Staphylococcus aureus, 100 Staphylococcus epidermidis, 10 Staphylococcus capitis, 8 Staphylococcus lugdunensis, 2 Staphylococcus warneri, and 2 Staphylococcus haemolyticus isolates using the extraction method recommended by Bruker Daltonics. The suggested species identification by the MALDI Biotyper software was correct for all isolates, indicating reliable differentiation between S. aureus and coagulase-negative staphylococci. Applying the recommended criteria of the MALDI Biotyper software all 158 isolates gave scores ≥2.0, implying secure genus and probable species identification for all isolates. 34/36 S. aureus, 36/100 S. epidermidis, 5/10 S. capitis, 6/8 S. lugdunensis, 2/2 S. haemolyticus, 0/2 S. warneri displayed scores ≥2.3 implying highly probable species identification. For S. epidermidis 25/100 additional isolates had a score close to 2.3. It appears that additional clinically relevant staphylococcal isolates in the data base might aid in identification at scores implying highly probable species identification. The ability of the MALDI Biotyper software to recognize clonally-related strains within a species group (i.e. sub-typing) was investigated, and showed great potential. In conclusion, the MALDI-TOF/MS MALDI Biotyper system provides a promising rapid and reliable method of identifying clinical isolates from prosthetic joint infections to the species level, and has potential for sub-typing.

Rapid Identification of Staphylococci from Prosthetic Joint Infections Using MALDI-TOF Mass-Spectrometry

Fifty-six α-hemolytic streptococcal isolates were identified using MALDI Biotyper MS (Bruker Daltonics), API 20 Strep (bioMerieux), and BD Phoenix (Becton, Dickinson). The gold standard for identification was 16S rRNA gene sequence analysis with 16S-23S rRNA intergenic spacer sequencing. The following percentages of isolates were correctly identified to the species level: MALDI Biotyper, 46%; BD Phoenix, 35%; and API 20 Strep, 26%.

Identification of clinical isolates of α-hemolytic streptococci by 16S rRNA gene sequencing, matrix-assisted laser desorption ionization-time of flight mass spectrometry using MALDI Biotyper, and conventional phenotypic methods: a comparison

Identification of microbial pathogens still relies primarily on culture and phenotypic methods, which is labour-intensive and time-consuming. In this study, identification of bacteria with valid standard identification using BD Phoenix, API panels and other recommended procedures is compared to identification with matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF) mass spectrometry using the MALDI Biotyper (Bruker Daltonics) in the setting of a routine NHS diagnostic microbiology laboratory. In total, 928 bacterial isolates obtained from blood (n=463), wounds and pus (n=208), respiratory tract (n=100), faeces (n=86) and urines (n=71) were analysed. There were 721 (77.7%) isolates with a MALDI Biotyper score > or =2.0, indicating secure genus and probable species identification; and 149 (16.1%) isolates with a score > or =1.7 and or =2.0 and > or =1.7 comprised 31 and 33 genera and 65 and 67 species, respectively. Overall, 99.4% and 99.1% of organism identifications were in agreement between the MALDI Biotyper and conventional identification at the genus level, and 89.3% and 87.8% at species level when analysing organisms with MALDI Biotyper scores > or =2.0 and > or =1.7, respectively. With many but not all organisms, identification at the genus level is sufficient; however, MALDI Biotyper separation of 208 staphylococci into Staphylococcus aureus and coagulase-negative staphylococci was always correct when scores were > or =1.7. First results were obtained after 5-10 min and analysis of a full 96-well target plate was completed in approximately 90 min. Substantial savings of between pounds 1.79 and pounds 2.56 per isolate, depending on the cost model of acquisition of the MALDI Biotyper system and number of isolates tested, would be realised when all 928 isolates were identified using the MALDI Biotyper and disk-susceptibility testing when compared to the cost for 618 Phoenix ID panels and 158 API panels and disk-susceptibility tests only (i.e., not taking into account costs incurred for identification of the remaining 152 mixed isolates). Microbial identification by MALDI Biotyper offers a rare opportunity for significant cost-neutral or even cost-saving quality improvements in medical diagnostics.

Comparison of bacterial identification by MALDI-TOF mass spectrometry and conventional diagnostic microbiology methods: agreement, speed and cost implications

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Rapid Identification of Staphylococci from Prosthetic Joint Infections Using MALDI-TOF Mass-Spectrometry

Identification of clinical isolates of α-hemolytic streptococci by 16S rRNA gene sequencing, matrix-assisted laser desorption ionization-time of flight mass spectrometry using MALDI Biotyper, and conventional phenotypic methods: a comparison

Comparison of bacterial identification by MALDI-TOF mass spectrometry and conventional diagnostic microbiology methods: agreement, speed and cost implications