31 research outputs found

    Time course of risk factors associated with mortality of 1260 critically ill patients with COVID-19 admitted to 24 Italian intensive care units

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    Purpose: To evaluate the daily values and trends over time of relevant clinical, ventilatory and laboratory parameters during the intensive care unit (ICU) stay and their association with outcome in critically ill patients with coronavirus disease 19 (COVID-19). Methods: In this retrospective–prospective multicentric study, we enrolled COVID-19 patients admitted to Italian ICUs from February 22 to May 31, 2020. Clinical data were daily recorded. The time course of 18 clinical parameters was evaluated by a polynomial maximum likelihood multilevel linear regression model, while a full joint modeling was fit to study the association with ICU outcome. Results: 1260 consecutive critically ill patients with COVID-19 admitted in 24 ICUs were enrolled. 78% were male with a median age of 63 [55–69] years. At ICU admission, the median ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) was 122 [89–175] mmHg. 79% of patients underwent invasive mechanical ventilation. The overall mortality was 34%. Both the daily values and trends of respiratory system compliance, PaO2/FiO2, driving pressure, arterial carbon dioxide partial pressure, creatinine, C-reactive protein, ferritin, neutrophil, neutrophil–lymphocyte ratio, and platelets were associated with survival, while for lactate, pH, bilirubin, lymphocyte, and urea only the daily values were associated with survival. The trends of PaO2/FiO2, respiratory system compliance, driving pressure, creatinine, ferritin, and C-reactive protein showed a higher association with survival compared to the daily values. Conclusion: Daily values or trends over time of parameters associated with acute organ dysfunction, acid–base derangement, coagulation impairment, or systemic inflammation were associated with patient survival

    Testing TSO-DSO interaction schemes for the participation of distribution energy resources in the balancing market : the SmartNet simulator

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    Many projections of near-future electricity system foresee a constantly increasing necessity of power flexibility services. In particular, thanks to the growing presence of renewable generation and innovative load technologies, distribution resources are becoming attractive productsin ancillary services markets. In order to open the market gates to distribution flexibility, constant interactions between transmission and distribution system operators are required and the European project SmartNet is investigating in detail the possible coordination schemes among these two actors. The paper describes the SmartNet simulator, one of the main tools developed within the project, whi ch precisely estimates the impact of TSO -DSO coordination schemes from the bidding and market clearing perspective, taking into account the consequent effects on the network physics at both transmission and distribution level

    Serological response and breakthrough infection after COVID-19 vaccination in patients with cirrhosis and post-liver transplant

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    BACKGROUND: Vaccine hesitancy and lack of access remain major issues in disseminating COVID-19 vaccination to liver patients globally. Factors predicting poor response to vaccination and risk of breakthrough infection are important data to target booster vaccine programs. The primary aim of the current study was to measure humoral responses to 2 doses of COVID-19 vaccine. Secondary aims included the determination of factors predicting breakthrough infection. METHODS: COVID-19 vaccination and Biomarkers in cirrhosis And post-Liver Transplantation is a prospective, multicenter, observational case-control study. Participants were recruited at 4-10 weeks following first and second vaccine doses in cirrhosis [n = 325; 94% messenger RNA (mRNA) and 6% viral vaccine], autoimmune liver disease (AILD) (n = 120; 77% mRNA and 23% viral vaccine), post-liver transplant (LT) (n = 146; 96% mRNA and 3% viral vaccine), and healthy controls (n = 51; 72% mRNA, 24% viral and 4% heterologous combination). Serological end points were measured, and data regarding breakthrough SARS-CoV-2 infection were collected. RESULTS: After adjusting by age, sex, and time of sample collection, anti-Spike IgG levels were the lowest in post-LT patients compared to cirrhosis (p < 0.0001), AILD (p < 0.0001), and control (p = 0.002). Factors predicting reduced responses included older age, Child-Turcotte-Pugh B/C, and elevated IL-6 in cirrhosis; non-mRNA vaccine in AILD; and coronary artery disease, use of mycophenolate and dysregulated B-call activating factor, and lymphotoxin-α levels in LT. Incident infection occurred in 6.6%, 10.6%, 7.4%, and 15.6% of cirrhosis, AILD, post-LT, and control, respectively. The only independent factor predicting infection in cirrhosis was low albumin level. CONCLUSIONS: LT patients present the lowest response to the SARS-CoV-2 vaccine. In cirrhosis, the reduced response is associated with older age, stage of liver disease and systemic inflammation, and breakthrough infection with low albumin level

    How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

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    COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p &lt; 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p &lt; 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p &lt; 0.0001) or urgent (20.4% vs. 38.5%; p &lt; 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p &lt; 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

    Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

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    The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER – DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of “case studies”, that are the combination of network topology, technical constraints and targets, load and generation profiles and “costs” of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications

    Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

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    The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER – DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of “case studies”, that are the combination of network topology, technical constraints and targets, load and generation profiles and “costs” of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications

    Fast estimation of equivalent capability for active distribution networks

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    The electricity system is subject to continuous evolution stimulated by the integration of renewable energy sources. This transformation is having deep impacts on the planning and operation of networks and new potential roles of system operators are currently investigated. In particular, having assumed a future in which the energy demand is largely satisfied by distributed generation, it can be reasonably expected that distribution networks will be soon enabled to offer balancing and regulation services to the market. In this scenario, the distribution operator may aggregate all the local dispatchable resources and, from their combination, a single capability can be obtained to represent the flexibility limits of the entire network. This study presents few simple and intuitive methods for a fast and accurate construction of this equivalent capability

    Using GIS to assess the impact of electric vehicles on electrical distribution networks: a study applied to the city of Brescia

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    The local environmental concerns and the need to replace fossil fuels with renewable sources to decrease carbon dioxide emissions, are driving the spread of new technologies, such as electric heating/cooling systems, residential photovoltaic generators, and electric mobility. These new equipment will be mostly connected to the electricity distribution networks, managed by distribution system operators. The definition of realistic future scenarios, in terms of network topology and user characteristics, is essential to determine the impact of these resources. This paper shows a methodology for integrating the network data with external public databases information to forecast the future impact of electromobility. In particular, the electromobility scenario is defined by exploiting public information regarding the position of public parking areas and the Origin-Destination (O-D) matrixes. This information, together with a georeferenced description of the distribution network, can be used to determine the impact on the network of electric vehicles recharge. The methodology is applied to the distribution network of Brescia, a city in Northern Italy

    TSO-DSO coordination to acquire services from distribution grids: Simulations, cost-benefit analysis and regulatory conclusions from the SmartNet project

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    The continuously growing distributed generation and the business potential for demand response are gradually enabling significant provision of flexibility and reserve towards distribution networks. For this reason, transmission and distribution system operators need to coordinate their operation in order to develop efficient market arrangements that can help utilize all the resources capable of providing ancillary services. SmartNet project investigated the potential interaction schemes between network operators, together with the possible new services devoted to the optimal distribution grid management. This paper summarizes the main challenges in simulating complex electricity systems and flexibility markets for three European countries (Italy, Denmark and Spain) in 2030 scenarios. The simulation results are then analyzed using cost-benefit analysis and regulatory conclusions are deduced.European Commission's H2020 under grant agreement No 691405
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