Comparison of two enzymatic immunoassays, high resolution mass spectrometry method and radioimmunoassay for the quantification of human plasma histamine

International audienceHistamine (HA) is one of the main immediate mediators involved in allergic reactions. HA plasma concentration is well correlated with the severity of vascular and respiratory signs of anaphylaxis. Consequently, plasma quantification of HA is useful to comfort the diagnosis of anaphylaxis. Currently, radioimmunoassay (RIA) is the gold standard method to quantify HA due to its high sensitivity, but it is time consuming, implicates specific formations and cautions for technicians, and produces hazardous radioactive wastes. The aim of this study was to compare two enzymatic immunoassays (EIA) and one in-house liquid chromatography high-resolution mass spectrometry method (LC-HRMS) with the gold standard method for HA quantification in plasma samples of patients suspected of anaphylaxis reactions. Ninety-two plasma samples were tested with the 4 methods (RIA, 2 EIA and LC-HRMS) for HA quantification. Fifty-eight samples displayed HA concentrations above the positive cut-off of 10 nM evaluated by RIA, including 18 highly positive samples (>100 nM). Our results showed that Immunotech® EIA and LC-HRMS concentrations were highly correlated with RIA values, in particular for samples with a HA concentration around the positive cut-off. In our hands, plasma concentrations obtained with the Demeditec Diagnostics® EIA correlated less with results obtained by RIA, and an underestimation of plasma HA levels led to a lack of sensitivity. In conclusion, this study demonstrates that Immunotech® EIA and LC-HRMS method could be used instead of RIA to assess plasma HA in human diagnostic use

Integrating clinical, gene expression, protein expression and preanalytical data for in silico cancer research.

International audienceWe present the phase I development of an integrative platform for the analysis of clinical, gene expression, protein expression and pre-analytical data. The platform is aimed at providing transparent access and analysis tools to researchers investigating new biomarkers and prognosis factors in the particular field of lymphoma diseases. In this article, we report on the data integration phase. The platform's principal advantage is its completeness as it integrates in a single environment clinical, genomic and proteomic data, allowing for their combined analysis. The architecture consists in a data warehouse including data on patients, clinical trials and array platforms and a DeMilitarized Zone for data exchange. A secure web-based platform allows any collaborative team to request the data warehouse and access basic statistics on integrated data. The presented system is currently in use

Comparison of Bayesian network and decision tree methods for predicting access to the renal transplant waiting list

International audienceThe study compares the effectiveness of Bayesian networks versus Decision Trees for predicting access to renal transplant waiting list in a French healthcare network. The data set consisted in 809 patients starting renal replacement therapy. The data were randomly divided into a training set (90%) and a validation set (10%). Bayesian network and CART decision tree were built on the training set. Their predictive performances were compared on the validation set. The age variable was found to be the most important factor in both models. Both models were highly sensitive and specific: sensitivity 90.0% (95%CI: 76.8-100), specificity 96.7% (95%CI: 92.2-100). Moreover, the models were complementary since the Bayesian network provided a global view of the variables' associations while the decision tree was more easily interpretable by physicians. These approaches provide insights on the current care process. This knowledge could be used for optimizing the healthcare process

Prise en compte de la stationnarité dans les algorithmes d'analyse spectrale et d'identification fondés sur la mesure des corrélations et spectres d'ordre supérieur

Les méthodes d'analyse spectrale et d'identification fondées sur le calcul des statistiques d'ordre supérieur ne peuvent pas s'appliquer sans précaution à l'analyse de données obtenues en échantillonant des signaux analogiques à temps continu. Dans cette communication nous présentons deux approches qui tiennent compte de cette difficulté, une première qui est une estimation de la phase dans le domaine spectral et une seconde qui est une modélisation MA dans le domaine temporel

Towards a decision support system for optimising clinical pathways of elderly patients in an emergency department

International audienceData stored in Healthcare Information Systems correspond potentially to a vast source of information for supporting decisions in management or public health issues. The presented study illustrates clinical data valuation, through the analysis of clinical pathways of elderly patients at the Emergency Department (ED) of Rennes hospital. METHOD: Relevant data were extracted from the Emergency Department database. Several analysis (e.g., cusum method) and representation tools (e.g., Graphviz) were used to study the patients' pathways, the dynamics of flows and the patients' characteristics. RESULTS: 4951 admissions were analysed and visualized. The representations provided a synthetic, global and comprehensive view of the department activities, to the satisfaction of the clinicians. Limitations of the ICD-10 coding of the diagnoses at the ED were pointed out as well as syntax and semantic interoperability issues. A solution is proposed for automating and scaling the Decision Support System

Managing an emergency department by analysing HIS medical data: a focus on elderly patient clinical pathways

International audienceINTRODUCTION: The objective of this paper is to present complementary views of the activity of the emergency department for a specific group of patients. Once validated, these views will be used as decision support tools for better managing the department and providing better care delivery for this population. The views are produced from the data stored in Healthcare Information Systems that correspond potentially to a vast source of information for supporting decisions on management or public health issues. METHOD: The study focuses on two groups of patients: the elderly population (over 75-years-old) and the under 75-year-old patients, at the Rennes hospital. The validation of the views is performed by comparing results for the two distinct groups. Relevant data were extracted from the Emergency Department database. Several analysis (like cusum chart) and representation tools (Graphviz) were used to study the patients' pathways, the dynamics of arrivals and the patients' characteristics. RESULTS: The representations provided a synthetic, global and comprehensive view of the department activities, to the satisfaction of the clinicians. The study showed that ICD-10 coding, assigned at the patient's departure from the emergency department hence from all available known clinical data, is not appropriate for the elderly population as these patients are mainly diagnosed by "symptoms" and several solutions are proposed. Finally, it is stressed out that a proper delivery of care to elderly patients should require some level of scheduling in the emergency department that is by essence characterized by its non scheduled activity

IL-2 requirement for human plasma cell generation: coupling differentiation and proliferation by enhancing MAPK-ERK signaling.

International audienceMature B cell differentiation involves a well-established transcription factor cascade. However, the temporal dynamics of cell signaling pathways regulating transcription factor network and coordinating cell proliferation and differentiation remain poorly defined. To gain insight into the molecular processes and extrinsic cues required for B cell differentiation, we set up a controlled primary culture system to differentiate human naive B cells into plasma cells (PCs). We identified T cell-produced IL-2 to be critically involved in ERK1/2-triggered PC differentiation. IL-2 drove activated B cell differentiation toward PC independently of its proliferation and survival functions. Indeed, IL-2 potentiated ERK activation and subsequent BACH2 and IRF8 downregulation, sustaining BLIMP1 expression, the master regulator for PC differentiation. Inhibition of the MAPK-ERK pathway, unlike STAT5 signaling, impaired IL-2-induced PC differentiation and rescued the expression profile of BACH2 and IRF8. These results identify IL-2 as a crucial early input in mature B cell fate commitment

Comparing the APGAR score representation in HL7 and OpenEHR formalisms.

International audienceSemantic interoperability, a prerequisite to eHealth projects, relies on sharing both information and knowledge models between information systems. Two of the standards of information models are HL7 v3 and the European norm, EN13606/OpenEHR. The paper compares both standards on a fragment of the prenatal medical record, the APGAR score. Two factors are compared: the formal representation of both information models, and the binding to knowledge models. The HL7v3 perinatality DMIM specification and the OpenEHR APGAR archetype were used. HL7v3 appears to be more formal than OpenEHR and able to represent in an easier way the clinical context. For both standards, the binding to reference terminologies such as LOINC is poor. We provide recommendations to improve the standards