AB1017 RADIOFREQUENCY ECHOGRAPHIC MULTI-SPECTROMETRY (REMS) AND DUAL-ENERGY X-RAYS ABSORPTIOMETRY FOR THE EVALUATION OF BONE MINERAL DENSITY IN A PERITONEAL DIALYSIS SETTING

Background

Radiofrequency echographic multi-spectrometry (REMS) is a novel ultrasound-based technique that has shown good reliability in the assessment of bone mineral density (BMD).

Objectives

The aim of this study was to compare the performance of the REMS BMD assessment with dual-energy X-rays absorptiometry (DXA) in a cohort of patients affected by end-stage renal disease undergoing peritoneal dialysis (PD).

Methods

Consecutive patients referring to the PD clinic of our hospital were enrolled. Lumbar spine and proximal femur REMS scans were performed, and lumbar spine (anteroposterior and laterolateral) and proximal femur DXA scans were performed as well. Clinical data were extracted from medical records. The risk assessment outputs of two fracture risk algorithms (FRAX and DeFRA), calculated upon the worst BMD obtained from either technique were compared as well. Analysis of variance (ANOVA) with post hoc analysis (Bonferroni) and a two-sided Student’s t-test were used to estimate the absolute differences between groups.

Written informed consent was obtained from all participants included (protocol 1483 CESC).

Results

41 total patients were enrolled (Table 1). No significant differences were documented between the BMD T-scores measured through DXA or REMS at the proximal femur. At the lumbar spine, the DXA laterolateral T-score was not significantly different from that of REMS, while the DXA anteroposterior T-score was significantly higher than both the anteroposterior DXA and the REMS measurements (Figure 1, panel A and B). When either DXA or REMS was adopted, no significant difference in the fracture risk estimate was found for both algorithms (Figure 1, panel C and D).

Table 1.

anthropometrics, clinical and biochemical characteristics of the enrolled sample. CKD, chronic kidney disease; PTH, parathyroid hormone; ALP, alkaline phosphatase; IQR, interquartile range; VFA, vertebral fracture assessment.

Sample size (M)41 (29)Age (y)Median [IQR]62 [52-73]Height (cm)Median [IQR]170 [165-176]Body weight (Kg)Median [IQR]74 [61-83]Body mass index (Kg/m2)Median [IQR]25 [22-27.8]Disease duration – CKD (months)Median [IQR]132 [48-140]Dialysis duration (months)Median [IQR]10 [3-24]S-calcium (mg/dL)Median [IQR]9.1 [8.6-9.4]S-phosphorous (mg/dL)Median [IQR]5.4 [4.6-6.4]PTH (pg/mL)Median [IQR]31.4 [22.8-46.8]25OH Vitamin D (nmol/L)Median [IQR]53 [36-72]Patients with morphometric fractures (VFA)15%Patients with femoral fractures2.4%Total n° of morphometric fractures12Figure 1.

comparison of the mean T-scores (error bars represent 95%CI) measured with DXA and REMS at the lumbar spine (panel A), and at the femur (panel B). Comparison between the DeFRA DXA and REMS-derived outputs (panel C) and FRAX DXA and REMS-derived outputs (panel D) raw and after correction for TBS. DeFRA, FRAX-derived risk assessment tool; FRAX, Fracture Risk Assessment tool; AP, anteroposterior; LL, latero-lateral; TH, total hip; FN, femoral neck; TBS, trabecular bone score.

Conclusion

Our data showed a good agreement, in a real-life PD setting, between the DXA and REMS-derived BMDs and in the consequent fracture risk assessment obtained with the FRAX or DeFRA tools.

Disclosure of Interests

Angelo Fassio: None declared, Stefano Andreola: None declared, Davide Gatti Paid instructor for: Amgen, Celgene Eli-Lilly, MSD-Italia, Organon, UCB., Consultant of: Amgen, Celgene Eli-Lilly, MSD-Italia, Organon, UCB., Matteo Gatti: None declared, Giovanni Gambaro Speakers bureau: Vifor Pharma, Maurizio Rossini Speakers bureau: Abiogen, Amgen, Abbvie, BMS, Celgene, Eli-Lilly, Galapagos, Grunenthal, MSD, Novartis, Pfizer, Sanofi, Sandoz, Theramex, UCB., Ombretta Viapiana: None declared, Giulia Zanetti: None declared, Francesca Pistillo: None declared, Valeri Messina: None declared, Giovanni Adami: None declared

AB1018 RELATIONSHIP BETWEEN AORTIC CALCIFICATIONS AND DXA AND RADIOFREQUENCY ECHOGRAPHIC MULTI-SPECTROMETRY (REMS) ACQUISITIONS

Background

Data on the relationship between peritoneal dialysis (PD), BMD and aortic calcifications (AOC) are lacking.

Objectives

to study the relationship between the degree of AOC and DXA and Radiofrequency Echographic Multi-Spectrometry (REMS) acquisitions.

Methods

Consecutive patients referring to the PD our clinic were enrolled. Lumbar spine (LS) and proximal femur REMS scans were performed, and LS (anteroposterior and laterolateral) and proximal femur DXA scans were performed as well. The degree of AOC was assessed through the semiquantitative score described by Kauppila et al, and applied to the laterolateral LS DXA scans. To test for correlations between different variables, we used the Pearson’s correlation for continuous variables and Spearman’s rho for discrete variables. Multiple regression analysis was performed to adjust for age and body mass index (BMI) the correlation between BMD and the CKD duration. Written informed consent was obtained from all participants (protocol 1483CESC).

Results

41 total patients were enrolled (29 males, 19 females). Median disease duration of CKD [IQR]: 132 months [48-140]. 15% had vertebral fractures at the DXA Vertebral Fracture Assessment (VFA). The median calcification score [IQR] was 2 [0-6] (min-max 0-20).

We found a statistically significant positive correlation of moderate strength between the total calcification score and the difference between the DXA AP T-score and the DXA LL T-score at the LS (p<0.01, Spearman’s rho = 0.402), Figure 1.

Figure 1.

scatter plot reporting the relationship between the difference between the AP and LL T-scores and the aortic calcifications score.

After adjustment for confounders, we found a significant negative between the LS and femoral neck BMD measured through REMS and CKD duration (Table 1). The same correlation was not significant then BMD was assessed with DXA.

Table 1.

multiple linear regression analysis for REMS T-score at each site after adjustment for age and BMI. BMI, body mass index; β, standardised coefficient.

REMS lumbar spine T-scoreβpCKD duration (months)-0.2280.035Age (years)-0.511<0.01BMI (kg/m2)0.566<0.01REMS femoral neck T-scoreβpCKD duration (months)-0.2100.04Age (years)-0.612<0.01BMI (kg/m2)0.484<0.01REMS total hip T-scoreβpCKD duration (months)-0.1530.219Age (years)-0.523<0.01BMI (kg/m2)0.560<0.01

Conclusion

Our study confirmed that the overestimation of DXA BMD assessed with the anteroposterior scan is indeed influenced by AOC. Furthermore, our data suggest that REMS might be an interesting tool for the investigation of bone changes in CKD.

Disclosure of Interests

Angelo Fassio: None declared, Stefano Andreola: None declared, Davide Gatti Speakers bureau: Amgen, Celgene Eli-Lilly, MSD-Italia, Organon, UCB, Paid instructor for: Amgen, Celgene Eli-Lilly, MSD-Italia, Organon, UCB, Matteo Gatti: None declared, Giovanni Gambaro Speakers bureau: Vitor Pharma, Ombretta Viapiana: None declared, Valeri Messina: None declared, Giulia Zanetti: None declared, Francesca Pistillo: None declared, Maurizio Rossini Speakers bureau: Abiogen, Amgen, Abbvie, BMS, Celgene, Eli-Lilly, Galapagos, Grunenthal, MSD, Novartis, Pfizer, Sanofi, Sandoz, Theramex, UCB., Giovanni Adami: None declared

Prognostic Utility of the Gleason Grading System Revisions and Histopathological Factors Beyond Gleason Grade

Background

The International Society of Urological Pathology (ISUP) revised the Gleason system in 2005 and 2014. The impact of these changes on prostate cancer (PCa) prognostication remains unclear.

Objective

To evaluate if the ISUP 2014 Gleason score (GS) predicts PCa death better than the pre-2005 GS, and if additional histopathological information can further improve PCa death prediction.

Patients and Methods

We conducted a case–control study nested among men in the National Prostate Cancer Register of Sweden diagnosed with non-metastatic PCa 1998–2015. We included 369 men who died from PCa (cases) and 369 men who did not (controls). Two uro-pathologists centrally re-reviewed biopsy ISUP 2014 Gleason grading, poorly formed glands, cribriform pattern, comedonecrosis, perineural invasion, intraductal, ductal and mucinous carcinoma, percentage Gleason 4, inflammation, high-grade prostatic intraepithelial neoplasia (HGPIN) and post-atrophic hyperplasia. Pre-2005 GS was back-transformed using i) information on cribriform pattern and/or poorly formed glands and ii) the diagnostic GS from the registry. Models were developed using Firth logistic regression and compared in terms of discrimination (AUC).

Results

The ISUP 2014 GS (AUC = 0.808) performed better than the pre-2005 GS when back-transformed using only cribriform pattern (AUC = 0.785) or both cribriform and poorly formed glands (AUC = 0.792), but not when back-transformed using only poorly formed glands (AUC = 0.800). Similarly, the ISUP 2014 GS performed better than the diagnostic GS (AUC = 0.808 vs 0.781). Comedonecrosis (AUC = 0.811), HGPIN (AUC = 0.810) and number of cores with ≥50% cancer (AUC = 0.810) predicted PCa death independently of the ISUP 2014 GS.

Conclusion

The Gleason Grading revisions have improved PCa death prediction, likely due to classifying cribriform patterns, rather than poorly formed glands, as Gleason 4. Comedonecrosis, HGPIN and number of cores with ≥50% cancer further improve PCa death discrimination slightly.

openEHR Is FAIR-Enabling by Design

The FAIR Principles are a set of recommendations that aim to underpin knowledge discovery and integration by making the research outcomes Findable, Accessible, Interoperable and Reusable. These guidelines encourage the accurate recording and exchange of data, coupled with contextual information about their creation, expressed in domain-specific standards and machine-readable formats. This paper analyses the potential support to FAIRness of the openEHR specifications and reference implementation, by theoretically assessing their compliance with each of the 15 FAIR principles. Our study highlights how the openEHR approach, thanks to its computable semantics-oriented design, is inherently FAIR-enabling and is a promising implementation strategy for creating FAIR-compliant Clinical Data Repositories (CDRs).

Interchangeability of light and virtual microscopy for histopathological evaluation of prostate cancer

Virtual microscopy (VM) holds promise to reduce subjectivity as well as intra- and inter-observer variability for the histopathological evaluation of prostate cancer. We evaluated (i) the repeatability (intra-observer agreement) and reproducibility (inter-observer agreement) of the 2014 Gleason grading system and other selected features using standard light microscopy (LM) and an internally developed VM system, and (ii) the interchangeability of LM and VM. Two uro-pathologists reviewed 413 cores from 60 Swedish men diagnosed with non-metastatic prostate cancer 1998–2014. Reviewer 1 performed two reviews using both LM and VM. Reviewer 2 performed one review using both methods. The intra- and inter-observer agreement within and between LM and VM were assessed using Cohen’s kappa and Bland and Altman’s limits of agreement. We found good repeatability and reproducibility for both LM and VM, as well as interchangeability between LM and VM, for primary and secondary Gleason pattern, Gleason Grade Groups, poorly formed glands, cribriform pattern and comedonecrosis but not for the percentage of Gleason pattern 4. Our findings confirm the non-inferiority of VM compared to LM. The repeatability and reproducibility of percentage of Gleason pattern 4 was poor regardless of method used warranting further investigation and improvement before it is used in clinical practice.

The openEHR Genomics Project

Current high-throughput sequencing technologies allow us to acquire entire genomes in a very short time and at a relatively sustainable cost, thus resulting in an increasing diffusion of genetic test capabilities, in specialized clinical laboratories and research centers. In contrast, it is still limited the impact of genomic information on clinical decisions, as an effective interpretation is a challenging task. From the technological point of view, genomic data are big in size, have a complex granular nature and strongly depend on the computational steps of the generation and processing workflows. This article introduces our work to create the openEHR Genomic Project and the set of genomic information models we developed to catch such complex structure and to preserve data provenance efficiently in a machine-readable format. The models support clinical actionability of data, by improving their quality, fostering interoperability and laying the basis for re-usability.

Interoperable and scalable data analysis with microservices: applications in metabolomics

MOTIVATION

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator.

RESULTS

We developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.

AVAILABILITY AND IMPLEMENTATION

The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the Virtual Research Environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Estimation of Relative and Absolute Risks in a Competing-Risks Setting Using a Nested Case-Control Study Design: Example From the ProMort Study

In this paper, we describe the Prognostic Factors for Mortality in Prostate Cancer (ProMort) study and use it to demonstrate how the weighted likelihood method can be used in nested case-control studies to estimate both relative and absolute risks in the competing-risks setting. ProMort is a case-control study nested within the National Prostate Cancer Register (NPCR) of Sweden, comprising 1,710 men diagnosed with low- or intermediate-risk prostate cancer between 1998 and 2011 who died from prostate cancer (cases) and 1,710 matched controls. Cause-specific hazard ratios and cumulative incidence functions (CIFs) for prostate cancer death were estimated in ProMort using weighted flexible parametric models and compared with the corresponding estimates from the NPCR cohort. We further drew 1,500 random nested case-control subsamples of the NPCR cohort and quantified the bias in the hazard ratio and CIF estimates. Finally, we compared the ProMort estimates with those obtained by augmenting competing-risks cases and by augmenting both competing-risks cases and controls. The hazard ratios for prostate cancer death estimated in ProMort were comparable to those in the NPCR. The hazard ratios for dying from other causes were biased, which introduced bias in the CIFs estimated in the competing-risks setting. When augmenting both competing-risks cases and controls, the bias was reduced.

PhenoMeNal: processing and analysis of metabolomics data in the cloud

BACKGROUND

Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools. However, the rapid progress has resulted in a mosaic of independent, and sometimes incompatible, analysis methods that are difficult to connect into a useful and complete data analysis solution.

FINDINGS

PhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated, and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi, and Pachyderm.

CONCLUSIONS

PhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible, and shareable metabolomics data analysis platforms that are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adaptation of the infrastructure to other application areas and 'omics research domains.

wft4galaxy: a workflow testing tool for galaxy

Motivation

Workflow managers for scientific analysis provide a high-level programming platform facilitating standardization, automation, collaboration and access to sophisticated computing resources. The Galaxy workflow manager provides a prime example of this type of platform. As compositions of simpler tools, workflows effectively comprise specialized computer programs implementing often very complex analysis procedures. To date, no simple way to automatically test Galaxy workflows and ensure their correctness has appeared in the literature.

Results

With wft4galaxy we offer a tool to bring automated testing to Galaxy workflows, making it feasible to bring continuous integration to their development and ensuring that defects are detected promptly. wft4galaxy can be easily installed as a regular Python program or launched directly as a Docker container—the latter reducing installation effort to a minimum.

Availability and implementation

Available at https://github.com/phnmnl/wft4galaxy under the Academic Free License v3.0.

Brunner's Gland Hamartoma with Incipient Ductal Malignancy. Report of a Case

A duodenal tumor mainly composed of Brunner's glands was surgically resected in a 54-year-old man complaining of hematemesis and melena. Histologic examination of the specimen revealed a lobular pattern of either ducts or glandular acini, with Paneth cells; smooth muscle fibers, fat tissue and well formed vascular channels were seen in the stroma. These aspects are more suggestive of a hamartomatous rather than an adenomatous lesion. Moreover, the epithelium in some ducts showed early malignant transformation, which is a feature never observed in previous reports.

Splenic Mucinous Cystadenocarcinoma Arising in Heterotopic Pancreatic Tissue

A mucinous cystadenocarcinoma along with remnants of normal pancreatic tissue was discovered in the spleen of a 21-year-old woman. Extensive clinical, radiological, ultrasound and computed tomography investigation revealed that the patient's pancreas and ovaries were unremarkable. We presume an origin from heterotopic pancreatic tissue for this neoplasm and present a review of the literature in this regard.

Sarcomatous Variant of Wilms’ Tumor. A Light and Immunohistochemical Study of Four Cases

Four cases of infantile sarcomatous renal tumors are reported. Rhabdomyoblastic differentiation was investigated in these tumors by the immunoperoxidase method using antimyoglobin sera. Rhabdomyoblastic cells were found in 2 cases and in a metastasis of one case in which the primary tumor was composed by undifferentiated cells negative for myoglobin stain. The histogenesis of these neoplasias is discussed, and it is suggested that they are a sarcomatous variant of Wilms’ tumor.

Benign Lipoblastoma: First Case Report of a Mesenteric Origin

A case of benign lipoblastoma of the mesentery, surgically resected in a 4-year-old boy, is reported, with data on its gross and histologic features. Both diffuse lipoblastomatosis and single benign lipoblastoma have been observed in different anatomical sites, mostly involving the subcutaneous tissue, and only sporadic cases of mediastinal or retroperitoneal lipo-blastomas have been reported. The present case therefore appears to be the first description of a lipoblastoma arising from mesentery. The main tumoral lesions with which lipoblastoma can be confused are briefly discussed.

Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health

The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.

The future of metabolomics in ELIXIR

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

Ultrametricity of optimal transport substates for multiple interacting paths over a square lattice network

We model a set of point-to-point transports on a network as a system of polydisperse interacting self-avoiding walks (SAWs) over a finite square lattice. The ends of each SAW may be located both at random, uniformly distributed, positions or with one end fixed at a lattice corner. The total energy of the system is computed as the sum over all SAWs, which may represent either the time needed to complete the transport over the network, or the resources needed to build the networking infrastructure. We focus especially on the second aspect by assigning a concave cost function to each site to encourage path overlap. A simulated annealing optimization, based on a modified Berg-Foerster-Aragao de Carvalho-Caracciolo-Froehlich (BFACF) algorithm developed for polymers, is used to probe the complex conformational substate structure at zero temperature. We characterize the average cost gains (and path-length variations) for increasing polymer density with respect to a Dijkstra routing and find a nonmonotonic behavior as recently found for random networks. We observe the emergence of ergodicity breaking and of nontrivial overlap distributions among replicas when switching from a convex to a concave cost function (e.g., x^{γ}, where x represents the node overlap). Finally, we show that the space of ground states for γ<1 is compatible with an ultrametric structure, as seen in many complex systems such as some spin glasses.

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data

This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR's formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called "Constant Load" and "Constant Number of Records", with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes.

Making sense of big data in health research: Towards an EU action plan

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Hand soap contamination by Pseudomonas aeruginosa in a tertiary care hospital: no evidence of impact on patients

BACKGROUND

During an environmental investigation of Pseudomonas aeruginosa in intensive care units, the liquid hand soap was found to be highly contaminated (up to 8 × 10(5)cfu/g) with this pathogen. It had been used over the previous five months and was probably contaminated during manufacturing.

AIM

To evaluate the burden of this contamination on patients by conducting an epidemiological investigation using molecular typing combined with whole genome sequencing (WGS).

METHODS

P. aeruginosa isolates from clinical specimens were analysed by double locus sequence typing (DLST) and compared with isolates recovered from the soap. Medical charts of patients infected with a genotype identical to those found in the soap were reviewed. WGS was performed on soap and patient isolates sharing the same genotype.

FINDINGS

P. aeruginosa isolates (N = 776) were available in 358/382 patients (93.7%). Only three patients (0.8%) were infected with a genotype found in the soap. Epidemiological investigations showed that the first patient was not exposed to the soap, the second could have been exposed, and the third was indeed exposed. WGS showed a high number of core single nucleotide polymorphism differences between patients and soap isolates. No close genetic association was observed between soap and patient isolates, ruling out the hypothesis of transmission.

CONCLUSION

Despite a highly contaminated soap, the combined investigation with DLST and WGS ruled out any impact on patients. Hand hygiene performed with alcohol-based solution for >15 years was probably the main reason. However, such contamination represents a putative reservoir of pathogens that should be avoided in the hospital setting.

Health care workers' influenza vaccination: motivations and mandatory mask policy

BACKGROUND

Vaccination of health care workers (HCW) against seasonal influenza (SI) is recommended but vaccination rate rarely reach >30%. Vaccination coverage against 2009 pandemic influenza (PI) was 52% in our hospital, whilst a new policy requiring unvaccinated HCW to wear a mask during patient care duties was enforced.

AIMS

To investigate the determinants of this higher vaccination acceptance for PI and to look for an association with the new mask-wearing policy.

METHODS

A retrospective cohort study, involving HCW of three critical departments of a 1023-bed, tertiary-care university hospital in Switzerland. Self-reported 2009-10 SI and 2009 PI vaccination statuses, reasons and demographic data were collected through a literature-based questionnaire. Descriptive statistics, uni- and multivariate analyses were then performed.

RESULTS

There were 472 respondents with a response rate of 54%. Self-reported vaccination acceptance was 64% for PI and 53% for SI. PI vaccination acceptance was associated with being vaccinated against SI (OR 9.5; 95% CI 5.5-16.4), being a physician (OR 7.7; 95% CI 3.1-19.1) and feeling uncomfortable wearing a mask (OR 1.7; 95% CI 1.0-2.8). Main motives for refusing vaccination were: preference for wearing a surgical mask (80% for PI, not applicable for SI) and concerns about vaccine safety (64%, 50%) and efficacy (44%, 35%).

CONCLUSIONS

The new mask-wearing policy was a motivation for vaccination but also offered an alternative to non-compliant HCW. Concerns about vaccine safety and efficiency and self-interest of health care workers are still main determinants for influenza vaccination acceptance. Better incentives are needed to encourage vaccination amongst non-physician HCW.

VISPA: a computational pipeline for the identification and analysis of genomic vector integration sites

The analysis of the genomic distribution of viral vector genomic integration sites is a key step in hematopoietic stem cell-based gene therapy applications, allowing to assess both the safety and the efficacy of the treatment and to study the basic aspects of hematopoiesis and stem cell biology. Identifying vector integration sites requires ad-hoc bioinformatics tools with stringent requirements in terms of computational efficiency, flexibility, and usability. We developed VISPA (Vector Integration Site Parallel Analysis), a pipeline for automated integration site identification and annotation based on a distributed environment with a simple Galaxy web interface. VISPA was successfully used for the bioinformatics analysis of the follow-up of two lentiviral vector-based hematopoietic stem-cell gene therapy clinical trials. Our pipeline provides a reliable and efficient tool to assess the safety and efficacy of integrating vectors in clinical settings.

BioBlend.objects: metacomputing with Galaxy

Summary: BioBlend.objects is a new component of the BioBlend package, adding an object-oriented interface for the Galaxy REST-based application programming interface. It improves support for metacomputing on Galaxy entities by providing higher-level functionality and allowing users to more easily create programs to explore, query and create Galaxy datasets and workflows.

Availability and implementation: BioBlend.objects is available online at https://github.com/afgane/bioblend. The new object-oriented API is implemented by the galaxy/objects subpackage.

Contact:simone.leo@crs4.it

Mandatory infectious diseases consultation for MRSA bacteremia is associated with reduced mortality

OBJECTIVES

Although infectious disease (ID) consultation has been associated with lower mortality in Staphylococcus aureus bloodstream infections, it is still not mandatory in many centers. This study aimed at assessing the impact of ID consultation on diagnostic and therapeutic management of methicillin-resistant S. aureus (MRSA) bacteremia.

METHODS

Retrospective cohort study of all patients with MRSA bacteremia from 2001 to 2010. ID consultations were obtained on request between 2001 and 2006 and became mandatory since 2007.

RESULTS

156 episodes of MRSA bacteremia were included, mostly from central venous catheter (32%) and skin and soft tissue (19%) infections. ID consultation coverage was 58% between 2001 and 2006 and 91% between 2007 and 2010. ID consultation was associated with more echocardiography (59% vs. 26%, p < 0.01), vancomycin trough level measurements (99% vs. 77%, p < 0.01), follow-up blood cultures (71% vs. 50%, p = 0.05), deep-seated infections (43% vs. 16%, p < 0.01), more frequent infection source control (83% vs. 57%, p = 0.03), a longer duration of MRSA-active therapy (median and IQR: 17 days, 13-30, vs. 12, 3-14, p < 0.01) and a 20% reduction in 7-day, 30-day and in-hospital mortality.

CONCLUSIONS

ID consultation was associated with a better management of patients with MRSA bacteremia and a reduced mortality.

Orione, a web-based framework for NGS analysis in microbiology

Summary: End-to-end next-generation sequencing microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult owing to a lack of interoperability, reproducibility and transparency. To overcome these limitations we present Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for next-generation sequencing microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.

Availability and implementation: Orione is available online at http://orione.crs4.it.

Contact:gianmauro.cuccuru@crs4.it

Supplementary information:Supplementary data are available at Bioinformatics online.

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop

Summary: Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig’s scalability over many computing nodes and illustrate its use with example scripts.

Availability and Implementation: Available under the open source MIT license at http://sourceforge.net/projects/seqpig/

Contact:andre.schumacher@yahoo.com

Supplementary information:Supplementary data are available at Bioinformatics online.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry and PCR-based rapid diagnosis of Staphylococcus aureus bacteraemia

Effective empirical treatment is of paramount importance to improve the outcome of patients with Staphylococcus aureus bacteraemia. We aimed to evaluate a PCR-based rapid diagnosis of methicillin resistance (GeneXpert MRSA) after early detection of S. aureus bacteraemia using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Patients with a first episode of S. aureus bacteraemia identified using MALDI-TOF MS were randomized in a prospective interventional open study between October 2010 and August 2012. In the control group, antibiotic susceptibility testing was performed after MALDI-TOF MS identification on blood culture pellets. In the intervention group, a GeneXpert MRSA was performed after S. aureus identification. The primary outcome was the performance of GeneXpert MRSA directly on blood cultures. We then assessed the impact of early diagnosis of methicillin resistance on the empirical treatment. In all, 197 episodes of S. aureus bacteraemia were included in the study, of which 106 were included in the intervention group. Median time from MALDI-TOF MS identification to GeneXpert MRSA result was 97 min (range 25-250). Detection of methicillin resistance using GeneXpert MRSA had a sensitivity of 99% and a specificity of 100%. There was less unnecessary coverage of MRSA in the intervention group (17.1% versus 29.2%, p 0.09). GeneXpert MRSA was highly reliable in diagnosing methicillin resistance when performed directly on positive blood cultures. This could help to avoid unnecessary prescriptions of anti-MRSA agents and promote the introduction of earlier adequate coverage in unsuspected cases.

Lentiviral hematopoietic stem cell gene therapy benefits metachromatic leukodystrophy

Metachromatic leukodystrophy (MLD) is an inherited lysosomal storage disease caused by arylsulfatase A (ARSA) deficiency. Patients with MLD exhibit progressive motor and cognitive impairment and die within a few years of symptom onset. We used a lentiviral vector to transfer a functional ARSA gene into hematopoietic stem cells (HSCs) from three presymptomatic patients who showed genetic, biochemical, and neurophysiological evidence of late infantile MLD. After reinfusion of the gene-corrected HSCs, the patients showed extensive and stable ARSA gene replacement, which led to high enzyme expression throughout hematopoietic lineages and in cerebrospinal fluid. Analyses of vector integrations revealed no evidence of aberrant clonal behavior. The disease did not manifest or progress in the three patients 7 to 21 months beyond the predicted age of symptom onset. These findings indicate that extensive genetic engineering of human hematopoiesis can be achieved with lentiviral vectors and that this approach may offer therapeutic benefit for MLD patients.