Development of antibiotic resistance in periprosthetic joint infection after total knee arthroplasty.

AIMS: The management of periprosthetic joint infection (PJI) after total knee arthroplasty (TKA) is challenging. The correct antibiotic management remains elusive due to differences in epidemiology and resistance between countries, and reports in the literature. Before the efficacy of surgical treatment is investigated, it is crucial to analyze the bacterial strains causing PJI, especially for patients in whom no organisms are grown. METHODS: A review of all revision TKAs which were undertaken between 2006 and 2018 in a tertiary referral centre was performed, including all those meeting the consensus criteria for PJI, in which organisms were identified. Using a cluster analysis, three chronological time periods were created. We then evaluated the antibiotic resistance of the identified bacteria between these three clusters and the effectiveness of our antibiotic regime. RESULTS: We identified 129 PJIs with 161 culture identified bacteria in 97 patients. Coagulase-negative staphylococci (CNS) were identified in 46.6% cultures, followed by Staphylococcus aureus in 19.8%. The overall resistance to antibiotics did not increase significantly during the study period (p = 0.454). However, CNS resistance to teicoplanin (p < 0.001), fosfomycin (p = 0.016), and tetracycline (p = 0.014) increased significantly. Vancomycin had an 84.4% overall sensitivity and 100% CNS sensitivity and was the most effective agent. CONCLUSION: Although we were unable to show an overall increase in antibiotic resistance in organisms that cause PJI after TKA during the study period, this was not true for CNS. It is concerning that resistance of CNS to new antibiotics, but not vancomycin, has increased in a little more than a decade. Our findings suggest that referral centres should continuously monitor their bacteriological analyses, as these have significant implications for prophylactic treatment in both primary arthroplasty and revision arthroplasty for PJI. Cite this article: Bone Joint J 2021;103-B(6 Supple A):171-176.

Blood loss after revision knee arthroplasty is 1.38- to 2.17-fold higher than after primary knee arthroplasty: A retrospective analysis of 898 cases.

BACKGROUND: There are a number of factors that influence blood loss during and after primary total knee arthroplasty (TKA) and revision TKA (rTKA). The purpose of this study was to provide a factorial assessment that would aid surgeons in managing expected blood loss in rTKA, when compared to TKA. The first question asked was the blood loss and transfusions between TKA and rTKA and the second question was risk factors for blood loss after rTKA. HYPOTHESIS: Blood loss in any rTKA is higher than in TKA by a factor of 2. PATIENTS AND METHODS: A retrospective single-centre consecutive series of rTKA between 2006 and 2018 was performed. Based on the rTKA types identified in joint registries, 4 rTKA cohorts were created: aseptic minor rTKA, aseptic major rTKA, 1st stage, and 2nd stage septic rTKA. A consecutive TKA cohort from the same study period was used to create a propensity score matched cohort with the aseptic major rTKA cohort. RESULT: A total of 622 rTKA were identified. Aseptic major rTKA had double the median blood loss than TKA. The lowest blood loss was observed in the TKA group followed by aseptic minor rTKA, and the highest in 2nd stage septic rTKA. The median total blood loss was higher in all rTKA by a factor ranging between 1.38 and 2.17. Higher age, female gender, lower preoperative hemoglobin, chronic heart disease and history of myocardial infarction were risk factors for increased blood loss. The type of rTKA performed was not predictive of blood loss in the linear regression analysis. DISCUSSION: Blood loss after rTKA is 1.38 to 2.17-fold higher than after TKA. The blood loss observed in 2nd stage septic rTKA and aseptic major rTKA was the highest. Older female patients, with a low preoperative hemoglobin, were identified to be at the highest risk of blood loss after rTKA. Strategies for further blood loss reductions need to be utilised to the fullest extent for these procedures. LEVEL OF EVIDENCE: III; retrospective prognostic study.

A Case Study Competition Among Methods for Analyzing Large Spatial Data.

The Gaussian process is an indispensable tool for spatial data analysts. The onset of the "big data" era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alternatives to the full Gaussian process that are more amenable to handling big spatial data have been proposed. These modern methods often exploit low-rank structures and/or multi-core and multi-threaded computing environments to facilitate computation. This study provides, first, an introductory overview of several methods for analyzing large spatial data. Second, this study describes the results of a predictive competition among the described methods as implemented by different groups with strong expertise in the methodology. Specifically, each research group was provided with two training datasets (one simulated and one observed) along with a set of prediction locations. Each group then wrote their own implementation of their method to produce predictions at the given location and each was subsequently run on a common computing environment. The methods were then compared in terms of various predictive diagnostics. Supplementary materials regarding implementation details of the methods and code are available for this article online. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary materials for this article are available at 10.1007/s13253-018-00348-w.

Evaluating alternative explanations for an association of extinction risk and evolutionary uniqueness in multiple insular lineages.

Studies in insular environments have often documented a positive association of extinction risk and evolutionary uniqueness (i.e., how distant a species is from its closest living relative). However, the cause of this association is unclear. One explanation is that species threatened with extinction are evolutionarily unique because they are old, implying that extinction risk increases with time since speciation (age-dependent extinction). An alternative explanation is that such threatened species are last survivors of clades that have undergone an elevated extinction rate, and that their uniqueness results from the extinction of their close relatives. Distinguishing between these explanations is difficult but important, since they imply different biological processes determining extinction patterns. Here, we designed a simulation approach to distinguish between these alternatives using living species, and applied it to 12 insular radiations that show a positive association between extinction risk and evolutionary uniqueness. We also tested the sensitivity of results to underlying assumptions and variable extinction rates. Despite differences among the radiations considered, age-dependent extinction was supported as best explaining the majority of the empirical cases. Biological processes driving characteristic changes in abundance with species duration (age-dependency) may merit further investigation.

Mistranslation drives the evolution of robustness in TEM-1 ß-lactamase.

How biological systems such as proteins achieve robustness to ubiquitous perturbations is a fundamental biological question. Such perturbations include errors that introduce phenotypic mutations into nascent proteins during the translation of mRNA. These errors are remarkably frequent. They are also costly, because they reduce protein stability and help create toxic misfolded proteins. Adaptive evolution might reduce these costs of protein mistranslation by two principal mechanisms. The first increases the accuracy of translation via synonymous "high fidelity" codons at especially sensitive sites. The second increases the robustness of proteins to phenotypic errors via amino acids that increase protein stability. To study how these mechanisms are exploited by populations evolving in the laboratory, we evolved the antibiotic resistance gene TEM-1 in Escherichia coli hosts with either normal or high rates of mistranslation. We analyzed TEM-1 populations that evolved under relaxed and stringent selection for antibiotic resistance by single molecule real-time sequencing. Under relaxed selection, mistranslating populations reduce mistranslation costs by reducing TEM-1 expression. Under stringent selection, they efficiently purge destabilizing amino acid changes. More importantly, they accumulate stabilizing amino acid changes rather than synonymous changes that increase translational accuracy. In the large populations we study, and on short evolutionary timescales, the path of least resistance in TEM-1 evolution consists of reducing the consequences of translation errors rather than the errors themselves.

Hybridization alters spontaneous mutation rates in a parent-of-origin-dependent fashion in Arabidopsis.

Over 70 years ago, increased spontaneous mutation rates were observed in Drosophila spp. hybrids, but the genetic basis of this phenomenon is not well understood. The model plant Arabidopsis (Arabidopsis thaliana) offers unique opportunities to study the types of mutations induced upon hybridization and the frequency of their occurrence. Understanding the mutational effects of hybridization is important, as many crop plants are grown as hybrids. Besides, hybridization is important for speciation and its effects on genome integrity could be critical, as chromosomal rearrangements can lead to reproductive isolation. We examined the rates of hybridization-induced point and frameshift mutations as well as homologous recombination events in intraspecific Arabidopsis hybrids using a set of transgenic mutation detector lines that carry mutated or truncated versions of a reporter gene. We found that hybridization alters the frequency of different kinds of mutations. In general, Columbia (Col)×Cape Verde Islands and Col×C24 hybrid progeny had decreased T→G and T→A transversion rates but an increased C→T transition rate. Significant changes in frameshift mutation rates were also observed in some hybrids. In Col×C24 hybrids, there is a trend for increased homologous recombination rates, except for the hybrids from one line, while in Col×Cape Verde Islands hybrids, this rate is decreased. The overall genetic distance of the parents had no influence on mutation rates in the progeny, as closely related accessions on occasion displayed higher mutation rates than accessions that are separated farther apart. However, reciprocal hybrids had significantly different mutation rates, suggesting parent-of-origin-dependent effects on the mutation frequency.

A practical guide to Bayesian group sequential designs.

Bayesian approaches to the monitoring of group sequential designs have two main advantages compared with classical group sequential designs: first, they facilitate implementation of interim success and futility criteria that are tailored to the subsequent decision making, and second, they allow inclusion of prior information on the treatment difference and on the control group. A general class of Bayesian group sequential designs is presented, where multiple criteria based on the posterior distribution can be defined to reflect clinically meaningful decision criteria on whether to stop or continue the trial at the interim analyses. To evaluate the frequentist operating characteristics of these designs, both simulation methods and numerical integration methods are proposed, as implemented in the corresponding R package gsbDesign. Normal approximations are used to allow fast calculation of these characteristics for various endpoints. The practical implementation of the approach is illustrated with several clinical trial examples from different phases of drug development, with various endpoints, and informative priors.

Tenofovir or zidovudine in second-line antiretroviral therapy after stavudine failure in southern Africa.

BACKGROUND: There is debate over using tenofovir or zidovudine alongside lamivudine in second-line antiretroviral therapy (ART) following stavudine failure. We analysed outcomes in cohorts from South Africa, Zambia and Zimbabwe METHODS: Patients aged ≥16 years who switched from a first-line regimen including stavudine to a ritonavir-boosted lopinavir-based second-line regimen with lamivudine or emtricitabine and zidovudine or tenofovir in seven ART programmes in southern Africa were included. We estimated the causal effect of receiving tenofovir or zidovudine on mortality and virological failure using Cox proportional hazards marginal structural models. Its parameters were estimated using inverse probability of treatment weights. Baseline characteristics were age, sex, calendar year and country. CD4(+) T-cell count, creatinine and haemoglobin levels were included as time-dependent confounders. RESULTS: A total of 1,256 patients on second-line ART, including 958 on tenofovir, were analysed. Patients on tenofovir were more likely to have switched to second-line ART in recent years, spent more time on first-line ART (33 versus 24 months) and had lower CD4(+) T-cell counts (172 versus 341 cells/µl) at initiation of second-line ART. The adjusted hazard ratio comparing tenofovir with zidovudine was 1.00 (95% CI 0.59, 1.68) for virological failure and 1.40 (0.57, 3.41) for death. CONCLUSIONS: We did not find any difference in treatment outcomes between patients on tenofovir or zidovudine; however, the precision of our estimates was limited. There is an urgent need for randomized trials to inform second-line ART strategies in resource-limited settings.

Multiorder correction algorithms to remove image distortions from mass spectrometry imaging data sets.

Time-of-flight secondary ion mass spectrometry imaging is a rapidly evolving technology. Its main application is the study of the distribution of small molecules on biological tissues. The sequential image acquisition process remains susceptible to measurement distortions that can render imaging data less analytically useful. Most of these artifacts show a repetitive nature from tile to tile. Here we statistically describe these distortions and derive two different algorithms to correct them. Both a generalized linear model approach and the linear discriminant analysis approach are able to increase image quality for negative and positive ion mode data sets. Additionally, performing simulation studies with repetitive and nonrepetitive tiling error we show that both algorithms are only removing repetitive distortions. It is further shown that the spectral component of the data set is not altered by the use of these correction methods. Both algorithms presented in this work greatly increase the image quality and improve the analytical usefulness of distorted images dramatically.