A Comparison of the Minimum Inhibitory Concentration of Antibiotics in Staphylococcus Species Isolated From Orthopedic and Respiratory Medicine Infections.

INTRODUCTION: Antibiotic susceptibility is very important for the successful treatment of orthopedic infections, particularly for implant-related infections. While the minimum inhibitory concentrations (MICs) of Staphylococcus species were well investigated for the isolates from the respiratory tract, investigations for orthopedic pathogens are very limited. We investigated the antibiotic MIC values of Staphylococcus species isolated from orthopedic infections and compared them with those of respiratory medicine isolates used as a control. METHODS: The MICs of vancomycin (VCM), arbekacin (ABK), teicoplanin (TEIC), linezolid (LZD), and rifampicin (RFP) of a total of consecutive 259 (89 orthopedic and 170 respiratory) Staphylococcus speciesisolated in our laboratory from January 2013 to July 2016 were retrospectively reviewed. Differences between the MICs of each antibiotic in orthopedic and respiratory samples were determined. RESULTS: The number of methicillin-sensitive Staphylococcus aureus (MSSA) with a VCM MIC of <0.5 µg/mL among respiratory isolates was significantly higher than that among orthopedic isolates, while those with a MIC of 2 µg/mL were significantly lower (P = 0.0078). The proportion of methicillin-resistant coagulase-negative staphylococci (MRCNS) isolates with a VCM MIC of 2 µg/mL was significantly higher in orthopedic samples than that of methicillin-resistant Staphylococcus aureus (MRSA) (P < 0.001) in respiratory isolates. The proportion of MRCNS orthopedic isolates with an RFP MIC of >2 µg/mL was significantly higher (P = 0.0058) than that of other orthopedic staphylococci. CONCLUSIONS: The VCM MICs of Staphylococcus species from orthopedic infections were higher than those of respiratory samples, particularly MRCNS from implant-related samples.

Monitoring of blood biochemical markers for periprosthetic joint infection using ensemble machine learning and UMAP embedding.

INTRODUCTION: Periprosthetic joint infection (PJI) is a serious complication after total joint arthroplasty. It is important to accurately identify PJI and monitor postoperative blood biochemical marker changes for the appropriate treatment strategy. In this study, we aimed to monitor the postoperative blood biochemical characteristics of PJI by contrasting with non-PJI joint replacement cases to understand how the characteristics change postoperatively. MATERIALS AND METHODS: A total of 144 cases (52 of PJI and 92 of non-PJI) were reviewed retrospectively and split into development and validation cohorts. After exclusion of 11 cases, a total of 133 (PJI: 50, non-PJI: 83) cases were enrolled finally. An RF classifier was developed to discriminate between PJI and non-PJI cases based on 18 preoperative blood biochemical tests. We evaluated the similarity/dissimilarity between cases based on the RF model and embedded the cases in a two-dimensional space by Uniform Manifold Approximation and Projection (UMAP). The RF model developed based on preoperative data was also applied to the same 18 blood biochemical tests at 3, 6, and 12 months after surgery to analyze postoperative pathological changes in PJI and non-PJI. A Markov chain model was applied to calculate the transition probabilities between the two clusters after surgery. RESULTS: PJI and non-PJI were discriminated with the RF classifier with the area under the receiver operating characteristic curve of 0.778. C-reactive protein, total protein, and blood urea nitrogen were identified as the important factors that discriminates between PJI and non-PJI patients. Two clusters corresponding to the high- and low-risk populations of PJI were identified in the UMAP embedding. The high-risk cluster, which included a high proportion of PJI patients, was characterized by higher CRP and lower hemoglobin. The frequency of postoperative recurrence to the high-risk cluster was higher in PJI than in non-PJI. CONCLUSIONS: Although there was overlap between PJI and non-PJI, we were able to identify subgroups of PJI in the UMAP embedding. The machine-learning-based analytical approach is promising in consecutive monitoring of diseases such as PJI with a low incidence and long-term course.

Clinical characteristics and risk factors for culture-negative periprosthetic joint infections.

BACKGROUND: Culture-negative periprosthetic joint infections (PJIs) can complicate diagnosis and management of PJI. This study aimed to identify risk factors for culture-negative PJI and differences in clinical characteristics between culture-positive and culture-negative PJI group. METHODS: This retrospective, cross-sectional study evaluated PJI cases obtained between January 2013 and October 2019 at our institution. These PJI cases were divided into culture-positive and culture-negative groups and then compared. The demographics, laboratory findings, and details of patient's clinical characteristics were investigated. Univariate and multivariate logistic regression analysis were performed to investigate risk factors for culture-negative PJI. RESULTS: A total of 109 PJI cases were included in the analysis: 82 (75%) culture-positive and 27 (25%) culture-negative. The mean serum white blood cell (WBC) count, C-reactive protein level, and erythrocyte sedimentation rate in the culture-negative group were significantly lower than those in the culture-positive group (p < 0.05). There were no significant differences between the two groups regarding history of prior antibacterial administration or treatment success rates. Multivariate analysis identified a low serum WBC count as a risk factor for culture-negative PJI (odds ratio = 0.78; 95% confidence interval [CI] = 0.63-0.97; p = 0.027). CONCLUSIONS: A low serum WBC count is a risk factor for culture-negative PJI, but prior antimicrobial therapy is not. The results suggest that PJI cases with lower levels of systemic inflammation are likely to be culture-negative; therefore, the possibility of a culture-negative result should be considered in suspected cases of PJI with low inflammatory markers, regardless of prior antibiotic exposure.

Differences in Diagnostic Properties Between Standard and Enrichment Culture Techniques Used in Periprosthetic Joint Infections.

BACKGROUND: Culture-negative infections can complicate the diagnosis and management of orthopedic infections, particularly periprosthetic joint infections (PJIs). This study aimed to identify differences in rate of detection of infection and organisms between cultured using standard and enriched methods. METHODS: This retrospective, cross-sectional study evaluated PJI samples obtained between January 2013 and December 2017 at Yokohama City University Hospital. Samples were assessed using standard and enrichment culture techniques. White blood cell counts, C-reactive protein levels, type of microorganism (coagulase-positive or coagulase-negative), and methicillin-resistant Staphylococcus were investigated. RESULTS: A total of 151 PJI samples were included in the analysis; of these, 68 (45.0%) were positive after standard culture while 83 (55.0%) were positive only after enrichment culture. The mean white blood cell counts and C-reactive protein levels were significantly lower in the enrichment culture group than in the standard culture group (P < .01). The rate of methicillin-resistant Staphylococcus and coagulase-negative Staphylococci was significantly higher in the enrichment culture group than in the standard culture group (P < .01). CONCLUSION: The enrichment culture method has a higher rate of detection of infection than standard culture techniques and should, therefore, be considered when diagnosing orthopedic infections, particularly PJI.