Effect of carbapenem resistance on outcomes of bloodstream infection caused by Enterobacteriaceae in low-income and middle-income countries (PANORAMA): a multinational prospective cohort study

Background Low-income and middle-income countries (LMICs) are under-represented in reports on the burden of antimicrobial resistance. We aimed to quantify the clinical effect of carbapenem resistance on mortality and length of hospital stay among inpatients in LMICs with a bloodstream infection due to Enterobacteriaceae. Methods The PANORAMA study was a multinational prospective cohort study at tertiary hospitals in Bangladesh, Colombia, Egypt, Ghana, India, Lebanon, Nepal, Nigeria, Pakistan, and Vietnam, recruiting consecutively diagnosed patients with carbapenem-susceptible Enterobacteriaceae (CSE) and carbapenem-resistant Entero-bacteriaceae (CRE) bloodstream infections. We excluded patients who had previously been enrolled in the study and those not treated with curative intent at the time of bloodstream infection onset. There were no age restrictions. Central laboratories in India and the UK did confirmatory testing and molecular characterisation, including strain typing. We applied proportional subdistribution hazard models with inverse probability weighting to estimate the effect of carbapenem resistance on probability of discharge alive and in-hospital death, and multistate modelling for excess length of stay in hospital. All patients were included in the analysis. Findings Between Aug 1, 2014, and June 30, 2015, we recruited 297 patients from 16 sites in ten countries: 174 with CSE bloodstream infection and 123 with CRE bloodstream infection. Median age was 46 years (IQR 15–61). Crude mortality was 20% (35 of 174 patients) for patients with CSE bloodstream infection and 35% (43 of 123 patients) for patients with CRE bloodstream infection. Carbapenem resistance was associated with an increased length of hospital stay (3·7 days, 95% CI 0·3–6·9), increased probability of in-hospital mortality (adjusted subdistribution hazard ratio 1·75, 95% CI 1·04–2·94), and decreased probability of discharge alive (0·61, 0·45–0·83). Multilocus sequence typing showed various clades, with marginal overlap between strains in the CRE and CSE clades. Interpretation Carbapenem resistance is associated with increased length of hospital stay and mortality in patients with bloodstream infections in LMICs. These data will inform global estimates of the burden of antimicrobial resistance and reinforce the need for better strategies to prevent, diagnose, and treat CRE infections in LMICs

An Agent-based framework for mitigating hazardous materials transport risk

International audienceDangerous goods transportation (DGT) represents technological and environmental risks for exposed populations, infrastructures and environment. Historical evidence has shown that road-accidents in DGT can lead to various potential consequences characterized by fatalities, injuries, evacuation, property damage, environmental degradation, and traffic disruption. Due to the importance of these products in everyday civil life activities and the increase in demand for these materials, developing tools for risk analysis and mitigation becomes a strategic goal in particular in those countries, like France, in which the majority of goods are transported by road. Based on the complexity of the dangerous goods transportation system DGTS and its related risk (factors that characterized risks are time dependent as traffic conditions, weather conditions, incident probability and population exposure), this analysis can only be made via simulation. This paper describes a generic approach to use agent-based modeling, an interesting approach to modeling systems comprised of autonomous and interacting agents, for risk analysis. It presents a novel generic model facet for representing risk analysis and fault tree propagation in an agent model, where the goal is to analyze the risk related to a system and to simulate its behavior in normal and degraded mode by using multi-agents systems. This approach is used to analyze the risks related to dangerous goods transportation and to minimize these risks by using agent-based model (identifying the best road that having the minimum risk level for transport)

Feedback ARMA Models versus Bayesian Models towards Securing OpenFlow Controllers for SDNs

In software-defined networking (SDN), the control layers are moved away from the forwarding switching layers. SDN gives more programmability and flexibility to the controllers. OpenFlow is a protocol that gives access to the forwarding plane of a network switch or router over the SDN network. OpenFlow uses a centralized control of network switches and routers in and SDN environment. Security is of major importance for SDN deployment. Transport layer security (TLS) is used to implement security for OpenFlow. This paper proposed a new technique to improve the security of the OpenFlow controller through modifying the TLS implementation. The proposed model is referred to as the secured feedback model using autoregressive moving average (ARMA) for SDN networks (SFBARMASDN). SFBARMASDN depended on computing the feedback for incoming packets based on ARMA models. Filtering techniques based on ARMA techniques were used to filter the packets and detect malicious packets that needed to be dropped. SFBARMASDN was compared to two reference models. One reference model was Bayesian-based and the other reference model was the standard OpenFlow

Feedback ARMA Models versus Bayesian Models towards Securing OpenFlow Controllers for SDNs

In software-defined networking (SDN), the control layers are moved away from the forwarding switching layers. SDN gives more programmability and flexibility to the controllers. OpenFlow is a protocol that gives access to the forwarding plane of a network switch or router over the SDN network. OpenFlow uses a centralized control of network switches and routers in and SDN environment. Security is of major importance for SDN deployment. Transport layer security (TLS) is used to implement security for OpenFlow. This paper proposed a new technique to improve the security of the OpenFlow controller through modifying the TLS implementation. The proposed model is referred to as the secured feedback model using autoregressive moving average (ARMA) for SDN networks (SFBARMASDN). SFBARMASDN depended on computing the feedback for incoming packets based on ARMA models. Filtering techniques based on ARMA techniques were used to filter the packets and detect malicious packets that needed to be dropped. SFBARMASDN was compared to two reference models. One reference model was Bayesian-based and the other reference model was the standard OpenFlow

Measuring the energy for the molecular graphs of antiviral agents: Hydroxychloroquine, Chloroquine and Remdesivir

We consider the energy for the molecular graphs of antiviral agents like Hydroxychloroquine, Remdesivir and Chloroquine. These drugs play a vital role in the treatment of COVID-19. Let Ѓ1,Ѓ2 and Ѓ3 be the n-dimensional graphs of the molecular structures of antiviral agents Hydroxychloroquine, Chloroquine and Remdesivir, respectively. We define their energies as E′(Ѓ1)=∑|λi′|, E′(Ѓ2)=∑|λj′| and E′(Ѓ3)=∑|λk′|, respectively. Where the sets {λ1′(Ѓ1),λ2′(Ѓ1),λ3′(Ѓ1),...,λn′(Ѓ1)}, {λ1′(Ѓ2),λ2′(Ѓ2),λ3′(Ѓ2),...,λn′(Ѓ2)} and {λ1′(Ѓ3),λ2′(Ѓ3),λ3′(Ѓ3),...,λn′(Ѓ3)} depict the eigenvalues for the adjacency matrices of Ѓ1,Ѓ2 and Ѓ3, respectively. We have developed some basic ideas and properties in order to measure the energies for the antiviral agents Hydroxychloroquine, Chloroquine and Remdesivir

PRevalence of the Eosinophilic Phenotype Among SeveRE asthma patients in Lebanon: results of the PREPARE study

Abstract Background The prevalence of eosinophilic asthma in Lebanon, one of the most severe phenotypes among severe asthma, is not known. This study aimed at determining the prevalence of the eosinophilic phenotype defined as an eosinophil count ≥ 300 cells/mm3 among severe asthma patients in Lebanon. Methods The Lebanese Chapter of the PREPARE study was a national, multicenter, cross-sectional observational study. Patients aged ≥ 12 years with severe asthma were identified and prospectively enrolled during clinic visits and completed the Global Initiative for Asthma (GINA) assessment of asthma control questionnaire. Patients’ health characteristics were collected from medical records and blood samples were obtained for measurement of serum IgE levels and blood eosinophils count. Results Overall, 101 patients (with mean age of 46.3 ± 17.0 years and 73.27% females) with severe asthma were included and, among them, 37% had eosinophilic phenotype, 67.3% had atopic phenotype with IgE > 100 IU/mL and 25.7% patients had overlapping atopic and eosinophilic phenotypes. Close to 80% had late-onset asthma, beyond 12 years of age, and around 85% had at least one severe exacerbation in the 12 months prior to study enrolment. The majority of participants [64.4%] had uncontrolled asthma, 24.7% had partially controlled symptoms and 10.9% had controlled symptoms. 19.8% of participants were on chronic oral corticosteroids, 78.2% had short course treatment of corticosteroids and all were prescribed a combination of inhaled corticosteroids and long-acting beta-agonist. Conclusions The majority of patients with severe asthma were uncontrolled of which 37% present with an eosinophilic phenotype, which should be taken into consideration for better management of these patients in view of the novel phenotype-specific therapeutic options