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The building sector has a significant impact on the environment due to its unproductive and technologically outdated practices. Although digital tools have emerged as potential solutions, current building practices often lack automation and efficiency. Throughout history, several self-supporting techniques, i.e., construction methods dedicated to the building of shells that do not need support during the construction works, have been developed. These techniques allow for reducing waste and minimizing construction costs. Combining self-supporting techniques and digital tools could aid the development of contemporary, highly sustainable, and efficient building practices that permit the use of alternative and sustainable materials. Building on this, the research conducted defines an approach for evaluating the balanced state of masonry structures during construction works and built using robotic technologies. The approach considers the factors that govern the stability under construction derived through studying self-supporting building techniques. The proposed approach assesses the structural state under construction, evaluating the need for temporary supports. An example of a masonry arch is provided to emphasize the importance of construction factors in sustainable building practices. Then the method is applied to a real case study. Overall, integrating self-supporting techniques with digital tools has the potential to revolutionize the building sector, and create highly sustainable and efficient practices.

This paper explores the corner tower of the Anagni Cathedral, a Romanesque structure built in the eleventh and thirteenth centuries. The tower, located beneath the baptistery, was likely constructed to support a small chapel with a font. Through digital surveying and geometric analysis, this study examines the tower's structural element and speculates on the ideal stereotomic apparatus and reference models. The paper also delves into the mechanism responsible for maintaining the cantilevering structure’s equilibrium. The tower and baptistery exemplify the role of stereotomy and friction in maintaining equilibrium, with internal tensile forces and unilateral contact between the structure's blocks. This study provides valuable insights into the Anagni Cathedral's structural elements and highlights the importance of understanding stereotomy and friction principles.

Geometry forms the basis for the study of equilibrium of masonry structures. The dependence of the stability of masonry structures on geometry rather than on material strength was well known to the ancient builders who, over time, empirically worked out rules of proportion for good structural building design. We propose a new graphical approach to assess, the equilibrium in compression for planar and non-planer arches and curves according to the Safe Theorem of Limit Analysis. The approach extends an existing two-dimensional funicular polygon strategy into three dimensions for the first time. The method finds robust applications in the study of masonry flying staircases made of monolithic blocks, giving an alternative for equilibrium to the pure torsional solution. The advantage of the presented approach is that it can be solved solely graphically. The approach is demonstrated by assessing the equilibrium of the main flying or open-well staircase in the Palazzo delle Poste (Trapani, 1924, designed and constructed by Francesco La Grassa), an expressive yet poorly understood structure.

This study aimed at evaluating the efficacy and safety of high-dose (> 0.2 L/kg of treated plasma per day) coupled plasma filtration-adsorption (CPFA) in treating patients with septic shock. Multicentre, randomised, adaptive trial, performed in 12 Italian intensive care units (ICUs). Patients aged 14 or more, admitted to the ICU with septic shock, or had developed it during the stay were eligible. The final outcome was mortality at discharge from the last hospital at which the patient received care. Between May 2015, and October 2017, 115 patients were randomised. The first interim analysis revealed a number of early deaths, prompting an unplanned analysis. Last hospital mortality was non-significantly higher in the CPFA (55.6%) than in the control group (46.2%, p = 0.35). The 90-day survival curves diverged in favour of the controls early after randomisation and remained separated afterwards (p = 0.100). An unplanned analysis showed higher mortality in CPFA compared to controls among patients without severe renal failure (p = 0.025); a dose–response relationship was observed between treated plasma volume and mortality (p = 0.010). The COMPACT-2 trial was stopped due to the possible harmful effect of CPFA in patients with septic shock. The harmful effect, if present, was particularly marked in the early phase of septic shock. Patients not requiring renal replacement therapy seemed most exposed to the possible harm, with evidence of a dose–response effect. Until the mechanisms behind these results are fully understood, the use of CPFA for the treatment of patients with septic shock is not recommended.

Since the beginning of the COVID-19 pandemic, the impact of superinfections in intensive care units (ICUs) has progressively increased, especially carbapenem-resistant Acinetobacter baumannii (CR-Ab). This observational, multicenter, retrospective study was designed to investigate the characteristics of COVID-19 ICU patients developing CR-Ab colonization/infection during an ICU stay and evaluate mortality risk factors in a regional ICU network. A total of 913 COVID-19 patients were admitted to the participating ICUs; 19% became positive for CR-Ab, either colonization or infection (n = 176). The ICU mortality rate in CR-Ab patients was 64.7%. On average, patients developed colonization or infection within 10 ± 8.4 days from ICU admission. Scores of SAPS II and SOFA were significantly higher in the deceased patients (43.8 ± 13.5, p = 0.006 and 9.5 ± 3.6, p < 0.001, respectively). The mortality rate was significantly higher in patients with extracorporeal membrane oxygenation (12; 7%, p = 0.03), septic shock (61; 35%, p < 0.001), and in elders (66 ± 10, p < 0.001). Among the 176 patients, 129 (73%) had invasive infection with CR-Ab: 105 (60.7%) Ventilator-Associated Pneumonia (VAP), and 46 (26.6%) Bloodstream Infections (BSIs). In 22 cases (6.5%), VAP was associated with concomitant BSI. Colonization was reported in 165 patients (93.7%). Mortality was significantly higher in patients with VAP (p = 0.009). Colonized patients who did not develop invasive infections had a higher survival rate (p < 0.001). Being colonized by CR-Ab was associated with a higher risk of developing invasive infections (p < 0.001). In a multivariate analysis, risk factors significantly associated with mortality were age (OR = 1.070; 95% CI (1.028–1.115) p = 0.001) and CR-Ab colonization (OR = 5.463 IC95% 1.572–18.988, p = 0.008). Constant infection-control measures are necessary to stop the spread of A. baumannii in the hospital environment, especially at this time of the SARS-CoV-2 pandemic, with active surveillance cultures and the efficient performance of a multidisciplinary team.

Multidrug resistance has become a serious threat for health, particularly in hospital-acquired infections. To improve patients’ safety and outcomes while maintaining the efficacy of antimicrobials, complex interventions are needed involving infection control and appropriate pharmacological treatments in antibiotic stewardship programs. We conducted a multicenter pre-post study to assess the impact of a stewardship program in seven Italian intensive care units (ICUs). Each ICU was visited by a multidisciplinary team involving clinicians, microbiologists, pharmacologists, infectious disease specialists, and data scientists. Interventions were targeted according to the characteristics of each unit. The effect of the program was measured with a panel of indicators computed with data from the MargheritaTre electronic health record. The median duration of empirical therapy decreased from 5.6 to 4.6 days and the use of quinolones dropped from 15.3% to 6%, both p < 0.001. The proportion of multi-drug-resistant bacteria (MDR) in ICU-acquired infections fell from 57.7% to 48.8%. ICU mortality and length of stay remained unchanged, indicating that reducing antibiotic administration did not harm patients’ safety. This study shows that our stewardship program successfully improved the management of infections. This suggests that policy makers should tackle multidrug resistance with a multidisciplinary approach based on continuous monitoring and personalised interventions.

The containment of unwanted electromagnetic radiation and interference is a relevant topic for the system design of any electrical system, and even more for data centers. In this context, the racks hosting piles of servers are one of the main sources of electromagnetic noise. Such unwanted radiation can couple and interact with other computing machines, but also with sensitive electronic devices needed for the management and/or maintenance of the center. The aim of this work is to show how the proper stack-up of the trays in the rack gives rise to a decrease in the unwanted physical electromagnetic radiation. Based on the application of the spherical wave expansion technique, a multi-objective genetic algorithm is developed to evaluate the optimal set of rack configurations that allows for a reduction of the external radiated field. The algorithm and the implemented constraints are described, and the results are discussed.

Background: As the global outbreak of COVID-19 continues to ravage the world, it is important to understand how frontline clinicians manage ventilatory support and the various limiting factors. / Methods: An online survey composed of 32 questions was developed and validated by an international expert panel. / Results: Overall, 502 respondents from 40 countries across six continents completed the survey. The mean number (±SD) of ICU beds was 64 ± 84. The most popular initial diagnostic tools used for treatment initiation were arterial blood gas (48%) and clinical presentation (37.5%), while the national COVID-19 guidelines were the most used (61.2%). High flow nasal cannula (HFNC) (53.8%), non-invasive ventilation (NIV) (47%), and invasive mechanical ventilation (IMV) (92%) were mostly used for mild, moderate, and severe COVID-19 cases, respectively. However, only 38.8%, 56.6% and 82.9% of the respondents had standard protocols for HFNC, NIV, and IMV, respectively. The most frequently used modes of IMV and NIV were volume control (VC) (36.1%) and continuous positive airway pressure/pressure support (CPAP/PS) (40.6%). About 54% of the respondents did not adhere to the recommended, regular ventilator check interval. The majority of the respondents (85.7%) used proning with IMV, with 48.4% using it for 12– 16 hours, and 46.2% had tried awake proning in combination with HFNC or NIV. Increased staff workload (45.02%), lack of trained staff (44.22%) and shortage of personal protective equipment (PPE) (42.63%) were the main barriers to COVID-19 management. / Conclusion: Our results show that general clinical practices involving ventilatory support were highly heterogeneous, with limited use of standard protocols and most frontline clinicians depending on isolated and varied management guidelines. We found increased staff workload, lack of trained staff and shortage of PPE to be the main limiting factors affecting global COVID-19 ventilatory support management.

As the clinical outcome of octogenarian patients hospitalised for COVID-19 is very poor, here we assessed the clinical characteristics and outcomes of patients aged 80 year or older hospitalised for COVID-19 receiving non-invasive respiratory support (NIRS). A multicentre, retrospective, observational study was conducted in seven hospitals in Northern Italy. All patients aged ≥80 years with COVID-19 associated hypoxemic acute respiratory failure (hARF) undergoing NIRS between 24 February 2020, and 31 March 2021, were included. Out of 252 study participants, 156 (61.9%) and 163 (64.6%) died during hospital stay and within 90 days from hospital admission, respectively. In this case, 228 (90.5%) patients only received NIRS (NIRS group), while 24 (9.5%) were treated with invasive mechanical ventilation (IMV) after NIRS failure (NIRS+IMV group). In-hospital mortality did not significantly differ between NIRS and NIRS+IMV group (61.0% vs. 70.8%, respectively; p = 0.507), while survival probability at 90 days was significantly higher for NIRS compared to NIRS+IMV patients (0.379 vs. 0.147; p = 0.0025). The outcome of octogenarian patients with COVID-19 receiving NIRS is quite poor. Caution should be used when considering transition from NIRS to IMV after NIRS failure.

This paper carries on a systematic analysis of the behavior of the time reversal (TR) voltage and current transfer functions used to locate faults and defects along lines in function of their terminal conditions expressed in terms of reflection coefficients. Transfer functions for solid and soft transversal faults and longitudinal defects are considered, covering all the possible scenarios. The reflection coefficients swing from values very close to 1 (open-end condition) up to values close to −1 (short-circuit condition) passing through values near zero (matching condition). The results are discussed to assess the accuracy and scalability of the electromagnetic TR method for unmatched media.

In this paper, the analysis of the accuracy of the electromagnetic time reversal method for unmatched media is carried out when the terminal impedances of the transmission line and/or of the defects along it are frequency dependent. Some numerical examples involving a medium-voltage power line and a high-speed interconnect are considered and the results discussed.

This paper applies the electromagnetic time reversal method to the identification of the location and to the quantification of the impedance Zd of longitudinal defects along transmission lines. A closed-form expression for the time-reversal current transfer function is derived. This new transfer function benefits from the same properties of that for solid or soft transversal faults, and hence, can be used for locating the defects along the line. Different scenarios are considered ranging from power lines to signals channels for high-speed digital systems at printed circuit board and package level. The results are discussed and used to assess the accuracy and scalability of the proposed method.

This contribution deals with the optimal placement of the decoupling capacitances on the gridded power delivery network of a multichip assembly with interposer. The optimization is performed by means of a nature-inspired algorithm of the genetic class. Different placement strategies are considered and compared. The cost function is based on the evaluation of the input impedance looked into the power and ground rails of the power distribution network and its comparison with a user-defined mask.

This paper analytically demonstrates that the boun-ded phase property of the voltage transfer function developed by Codino for the electromagnetic time-reversal method in unmatched media is also valid for the time-reversal current transfer function used as an estimator of the location along the line of soft defects with defect impedance different from zero. Few examples are proposed ranging from medium-voltage power lines to high-speed interconnects, which demonstrate the accuracy and scalability of the method.

(1) Methods for checking the condition of monumental masonry structures can still be considered understudied. Among the different approaches available in the literature, the graphical ones have a special role, due to their simplicity and effectiveness. (2) In this work, a 2D method (Thrust Line Analysis (TLA)), the Modified Thrust Line Method (MTLM), and the 3D Membrane Equilibrium Analysis (MEA) method are compared. All methods have the same starting concept: no tensile strength, no sliding between the stone blocks, infinite compressive strength. (3) The methods are compared in terms of stress distribution (for the same—or similar—thrust line), and in terms of the Geometrical Safety Factor ensured. (4) The work shows that these theories, if properly conveyed in a scientific methodology (as many authors are doing currently and have done in the past) demonstrate the effectiveness and the advantages of graphical methods for simple structures.

PURPOSE: Severe coronavirus disease 2019 (COVID-19) is strongly related to interstitial pneumonia with frequent development of acute respiratory distress syndrome (ARDS). The role of corticosteroids (CS) treatment in these patients is still controversial. Some studies evidenced a possible role of an early short-term course of CS treatment in the treatment of severe pneumonia. PATIENTS AND METHODS: This is a single-center, retrospective study considering the patients with confirmed COVID-19 pneumonia admitted to our hospital between 9th March and 15th June 2020. Two groups were considered: early high-dose of methyl-prednisolone (eHDM; n ​= ​31) and the control group (n ​= ​52). Patients in the eHDM group received the dose of 5-8 ​mg/kg/day of methyl-prednisolone for 2 consecutive days. Primary outcome was the mortality evaluation; secondary outcomes were clinical improvement, side-effects and laboratory/radiographic changes. RESULTS: Significant differences between the two groups were: length of hospitalization (21.5 vs 28.4 days, p ​= ​0.026), length of non-invasive ventilation (NIV) or mechanical ventilation (11.5 vs 14.5 days, p ​= ​0.031), death (5 vs 12, p ​= ​0.006) and clinical improvement (16 vs 11, p=0.018). The following factors were related to in-hospital mortality in the multivariate analysis: comorbidities (OR ​= ​2.919; 95%CI ​= ​1.515-16.705; p

In many seismically active regions of the world there are large numbers of masonry buildings. Most of these buildings have not been designed for seismic loads. Recent earthquakes have shown that many of these buildings are seismically vulnerable and should be considered for retrofitting. Different conventional and unconventional retrofitting techniques are available to increase the strength and/or ductility of unreinforced masonry (URM) walls. This paper reviews and discusses seismic retrofitting of masonry walls with emphasis on the conventional techniques. Retrofitting procedures are discussed with regard to a case study: a stone masonry building in Irpinia region, damaged by the 1980 earthquake. The interventions are evaluated by means of finite elements with a macroelement obtained with an homogenization technique. Linear and nonlinear procedures are compared, and peculiarities of each procedure are shown

In patients intubated for hypoxemic acute respiratory failure (ARF) related to novel coronavirus disease (COVID-19), we retrospectively compared two weaning strategies, early extubation with immediate non-invasive ventilation (NIV) versus standard weaning encompassing spontaneous breathing trial (SBT), with respect to IMV duration (primary endpoint), extubation failures and reintubations, rate of tracheostomy, intensive care unit (ICU) length of stay and mortality (additional endpoints). All COVID-19 adult patients, intubated for hypoxemic ARF and subsequently extubated, were enrolled. Patients were included in two groups, early extubation followed by immediate NIV application, and conventionally weaning after passing SBT. 121 patients were enrolled and analyzed, 66 early extubated and 55 conventionally weaned after passing an SBT. IMV duration was 9 [6–11] days in early extubated patients versus 11 [6–15] days in standard weaning group (p = 0.034). Extubation failures [12 (18.2%) vs. 25 (45.5%), p = 0.002] and reintubations [12 (18.2%) vs. 22 (40.0%) p = 0.009] were fewer in early extubation compared to the standard weaning groups, respectively. Rate of tracheostomy, ICU mortality, and ICU length of stay were no different between groups. Compared to standard weaning, early extubation followed by immediate NIV shortened IMV duration and reduced the rate of extubation failure and reintubation.

The de-embedding of measurement fixtures is relevant for an accurate experimental characterization of radio frequency and digital electronic devices. The standard technique consists in removing the effects of the measurement fixtures by the calculation of the transfer scattering parameters (T-parameters) from the available measured (or simulated) global scattering parameters (S-parameters). The standard de-embedding is achieved by a multiple steps process, involving the S-to-T and subsequent T-to-S parameter conversion. In a typical measurement setup, two fixtures are usually placed before and after the device under test (DUT) allowing the connection of the device to the calibrated vector network analyzer coaxial ports. An alternative method is proposed in this paper: it is based on the newly developed multi-network cascading algorithm. The matrices involved in the fixture-DUT-fixture cascading gives rise to a non-linear set of equations that is in one step analytically solved in closed form, obtaining a unique solution. The method is shown to be effective and at least as accurate as the standard multi-step de-embedding one.

An accurate monitoring of power system behavior is a hot-topic for modern grid operation. Low-frequency oscillations (LFO), such as inter-area electromechanical oscillations, are detrimental phenomena impairing the development of the grid itself and also the integration of renewable sources. An interesting countermeasure to prevent the occurrence of such oscillations is to continuously identify their characteristic electromechanical mode parameters, possibly realizing an online monitoring system. In this paper an attempt to develop an online modal parameters identification system is done using machine learning techniques. An approach based on the development of a proper artificial neural network exploiting the frequency measurements coming from actual PMU devices is presented. The specifically developed offline training stage is fully detailed. The output results from the dynamic mode decomposition method are considered as reference in order to validate the machine learning approach. Some results are presented in order to validate the effectiveness of the proposed approach on data coming from recordings of real grid events. The main key points affecting the performance of the proposed technique are discussed by means of proper validation scenarios. This contribution is the first step of a more extended project whose final aim is the development of an artificial neural networks (ANN) architecture able to predict the system behavior (in a given time span) in terms of LFO modal parameters, and to classify the contingencies/disturbances based on an online training that has memory of the passed training samples.

Background As delayed intubation may worsen the outcome of coronavirus disease 2019 (COVID-19) patients treated with continuous positive airway pressure (CPAP), we sought to determine COVID-specific early predictors of CPAP failure. Methods In this observational retrospective multicentre study, we included all COVID-19 patients treated with out-of-ICU CPAP, candidates for intubation in case of CPAP failure. From these patients, we collected demographic and clinical data. Results A total of 397 COVID-19 patients were treated with CPAP for respiratory failure, with the therapeutic goal of providing intubation in case of CPAP failure. Univariable analysis showed that, age, lactate dehydrogenase (LDH) and white cell counts were all significantly lower in patients with successful CPAP treatment compared to those failing it and undergoing subsequent intubation. The percentage changes between baseline and CPAP application in the ratio of partial pressure arterial oxygen (PaO2) and fraction of inspired oxygen (FiO2), PaO2, respiratory rate and ROX index were higher in patients experiencing successful CPAP compared to those failing it. FiO2 and male gender were also significantly associated with intubation. Multivariable analysis adjusting for age, gender, Charlson comorbidity index, percentage change in PaO2/FiO2 or PaO2 and FiO2 separately, lactate, white blood cell count, LDH and C-reactive protein levels led to an area under the curve of 0.818 and confirmed that age, LDH and percentage increase in PaO2/FiO2 are predictors of intubation. Conclusions In COVID-19 patients requiring CPAP, age, LDH and percentage change in PaO2/FiO2 after starting CPAP are predictors of intubation.

AimWe aimed to characterise a large population of coronavirus disease 2019 (COVID-19) patients with moderate-to-severe hypoxaemic acute respiratory failure (ARF) receiving continuous positive airway pressure (CPAP) outside the intensive care unit (ICU), and to ascertain whether the duration of CPAP application increased the risk of mortality for patients requiring intubation.MethodsIn this retrospective, multicentre cohort study, we included adult COVID-19 patients, treated with CPAP outside ICU for hypoxaemic ARF from 1 March to 15 April, 2020. We collected demographic and clinical data, including CPAP therapeutic goal, hospital length of stay and 60-day in-hospital mortality.ResultsThe study included 537 patients with a median (interquartile range (IQR) age of 69 (60–76) years. 391 (73%) were male. According to the pre-defined CPAP therapeutic goal, 397 (74%) patients were included in the full treatment subgroup, and 140 (26%) in the do not intubate (DNI) subgroup. Median (IQR) CPAP duration was 4 (1–8) days, while hospital length of stay was 16 (9–27) days. 60-day in-hospital mortality was 34% (95% CI 0.304–0.384%) overall, and 21% (95% CI 0.169–0.249%) and 73% (95% CI 0.648–0.787%) for full treatment and DNI subgroups, respectively. In the full treatment subgroup, in-hospital mortality was 42% (95% CI 0.345–0.488%) for 180 (45%) CPAP failures requiring intubation, and 2% (95% CI 0.008–0.035%) for the remaining 217 (55%) patients who succeeded. Delaying intubation was associated with increased mortality (hazard ratio 1.093, 95% CI 1.010–1.184).ConclusionsWe described a large population of COVID-19 patients treated with CPAP outside ICU. Intubation delay represents a risk factor for mortality. Further investigation is needed for early identification of CPAP failures.

Background As the global outbreak of COVID-19 continues to ravage the world, it is important to understand how frontline clinicians manage ventilatory support and the various limiting factors. Methods An online survey composed of 32 questions was developed and validated by an international expert panel. Results Overall, 502 respondents from 40 countries across six continents completed the survey. The mean number (±SD) of ICU beds was 64 ± 84. The most popular initial diagnostic tools used for treatment initiation were arterial blood gas (48%) and clinical presentation (37.5%), while the national COVID-19 guidelines were the most used (61.2%). High flow nasal cannula (HFNC) (53.8%), non-invasive ventilation (NIV) (47%), and invasive mechanical ventilation (IMV) (92%) were mostly used for mild, moderate, and severe COVID-19 cases, respectively. However, only 38.8%, 56.6% and 82.9% of the respondents had standard protocols for HFNC, NIV, and IMV, respectively. The most frequently used modes of IMV and NIV were volume control (VC) (36.1%) and continuous positive airway pressure/pressure support (CPAP/PS) (40.6%). About 54% of the respondents did not adhere to the recommended, regular ventilator check interval. The majority of the respondents (85.7%) used proning with IMV, with 48.4% using it for 12–16 hours, and 46.2% had tried awake proning in combination with HFNC or NIV. Increased staff workload (45.02%), lack of trained staff (44.22%) and shortage of personal protective equipment (PPE) (42.63%) were the main barriers to COVID-19 management. Conclusion Our results show that general clinical practices involving ventilatory support were highly heterogeneous, with limited use of standard protocols and most frontline clinicians depending on isolated and varied management guidelines. We found increased staff workload, lack of trained staff and shortage of PPE to be the main limiting factors affecting global COVID-19 ventilatory support management.

An iterative optimization for decoupling capacitor placement on a power delivery network (PDN) is presented based on Genetic Algorithm (GA) and Artificial Neural Network (ANN). The ANN is first trained by an appropriate set of results obtained by a commercial simulator. Once the ANN is ready, it is used within an iterative GA process to place a minimum number of decoupling capacitors for minimizing the differences between the input impedance at one or more location, and the required target impedance. The combined GA&ndash, ANN process is shown to effectively provide results consistent with those obtained by a longer optimization based on commercial simulators. With the new approach the accuracy of the results remains at the same level, but the computational time is reduced by at least 30 times. Two test cases have been considered for validating the proposed approach, with the second one also being compared by experimental measurements.

The objective of this study is the development of an efficient methodology, based on the spherical wave expansion theory, to evaluate the total unwanted electromagnetic radiation of multiple radiation sources starting from the knowledge of the radiation characteristic of every single source considered as isolated. The specific application domain deals with the estimation of the electromagnetic interference from stacked trays in server racks. After having computed the radiation of each isolated tray, by using the spherical expansion technique the proper expansion coefficients are calculated. They are combined in a set of new coefficients that are used to reconstruct the estimated total field from the server rack. This study discusses the proposed methodology step by step and offers practical considerations on its implementation when measured data are given as input. The adopted numerical examples show in a quantitative way, through different graphs and comparisons, the limits and the advantages of the technique. The proposed method has been shown to reliably predict the radiation from stacked trays with only a few dB of uncertainty. The examples are based on numerically computed data sets of electromagnetic emissions from trays and racks but the proposed procedure is valid also for measured data.

Noninvasive continuous positive airway pressure (NIV-CPAP) is effective in patients with hypoxemic respiratory failure. Building evidence during the COVID-19 emergency reported that around 50% of patients in Italy treated with NIV-CPAP avoided the need for invasive mechanical ventilation. Standard NIV-CPAP systems operate at high gas flow rates responsible for noise generation and inadequate humidification. Furthermore, open-configuration systems require a high concentration of oxygen to deliver the desired FiO2 . Concerns outlined the risk for aerosolization in the ambient air and the possible pressure drop in hospital supply pipes. A new NIV-CPAP system is proposed that includes automatic control of patient respiratory parameters. The system operates as a closed-loop breathing circuit that can be assembled, combining a sleep apnea machine with existing commercially available components. Analytical simulation of a breathing patient and simulation with a healthy volunteer at different FiO2 were performed. Inspired and expired oxygen fraction and inspired and expired carbon dioxide pressure were recorded at different CPAP levels with different oxygen delivery. Among the main findings, we report (a) a significant (up to 30-fold) reduction in oxygen feeding compared to standard open high flow NIV-CPAP systems, to assure the same FiO2 levels, and (b) a negligible production of the noise generated in ventilatory systems, and consequent minimization of patients' discomfort. The proposed NIV-CPAP circuit, reshaped in closed-loop configuration with the blower outside of the circuit, has the advantages of minimizing aerosol generation, environmental contamination, oxygen consumption, and noise to the patient. The system is easily adaptable and can be implemented using standard CPAP components.

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.