Comparison of Figulla Flex® and Amplatzer™ devices for atrial septal defect closure: A meta-analysis

Background: Atrial septal defect (ASD) is one of the most common congenital heart diseases. Percutaneousclosure is the preferred treatment, but certain complications remain a concern. The most common devices are AMPLATZER™ (ASO) (St. Jude Medical, St. Paul, MN, USA) and Figulla Flex® septal occluders (FSO) (Occlutech GmbH, Jena, Germany). The present study aimed to assess main differences in outcomes.Methods: A systematic search in Pubmed and Google scholarship was performed by two independent reviewers for any study comparing ASO and FSO. Searched terms were “Figulla”, “Amplatzer”, and “atrial septal defect”. A random-effects model was used.Results: A total of 11 studies including 1770 patients (897 ASO; 873 FSO) were gathered. Baseline clinical and echocardiographic characteristics were comparable although septal aneurysm was more often reported in patients treated with ASO (32% vs. 25%; p = 0.061). Success rate (94% vs. 95%; OR: 0.81; 95% CI: 0.38–1.71; p = 0.58) and peri-procedural complications were comparable. Procedures were shorter, requiring less fluoroscopy time with an FSO device (OR: 0.59; 95% CI: 0.20–0.97; p = 0.003). Although the global rate of complications in long-term was similar, the ASO device was associated with a higher rate of supraventricular arrhythmias (14.7% vs. 7.8%, p = 0.009).Conclusions: Percutaneous closure of ASD is a safe and effective, irrespective of the type of device. No differences exist regarding procedural success between the ASO and FSO devices but the last was associated to shorter procedure time, less radiation, and lower rate of supraventricular arrhythmias in follow-up. Late cardiac perforation did not occur and death in the follow-up was exceptional

Impact of the presence of heart disease, cardiovascular medications and cardiac events on outcome in COVID-19

Background: Cardiovascular risk factors and usage of cardiovascular medication are prevalent among coronavirus disease 2019 (COVID-19) patients. Little is known about the cardiovascular implications of COVID-19. The goal herein, was to evaluate the prognostic impact of having heart disease (HD) and taking cardiovascular medications in a population diagnosed of COVID-19 who required hospitalization. Also, we studied the development of cardiovascular events during hospitalization. Methods: Consecutive patients with definitive diagnosis of COVID-19 made by a positive real time- -polymerase chain reaction of nasopharyngeal swabs who were admitted to the hospital from March 15 to April 14 were included in a retrospective registry. The association of HD with mortality and with mortality or respiratory failure were the primary and secondary objectives, respectively. Results: A total of 859 patients were included in the present analysis. Cardiovascular risk factors were related to death, particularly diabetes mellitus (hazard ratio in the multivariate analysis: 1.810 [1.159– –2.827], p = 0.009). A total of 113 (13.1%) patients had HD. The presence of HD identified a group of patients with higher mortality (35.4% vs. 18.2%, p < 0.001) but HD was not independently related to prognosis; renin–angiotensin–aldosterone system inhibitors, calcium channel blockers, diuretics and beta-blockers did not worsen prognosis. Statins were independently associated with decreased mortality (0.551 [0.329–0.921], p = 0.023). Cardiovascular events during hospitalization identified a group of patients with poor outcome (mortality 31.8% vs. 19.3% without cardiovascular events, p = 0.007). Conclusions: The presence of HD is related to higher mortality. Cardiovascular medications taken before admission are not harmful, statins being protective. The development of cardiovascular events during the course of the disease is related to poor outcome

Reducing sampling costs in multivariate SPC with a double-dimension T-2 control chart

[EN] In some real situations there is the need of controlling p variables of a multivariate process, where p1 out of these p variables are easy and inexpensive to monitor, while the p(2)=p-p(1) remaining variables are difficult and/or expensive to measure. However, this set of p(2) variables is important to quickly detect the process shifts. This paper develops a control chart based on the T-2 statistic where normally only the set of p1 variables is monitored, and only when the T-2 value falls in a warning area the rest of variables (p(2)) are measured and combined with the sample values from the p(1) variables, in order to obtain a new T-2 statistic. This new chart is the double dimension T-2 (DDT2) control chart. The ARL of the DDT2 chart is obtained and the chart's parameters are optimized using genetic algorithms with the aim of maximizing the performance in detecting a given process shift. The optimized DDT2 chart is compared against the standard T-2 chart when all the variables are monitored. The results show that the DDT2 clearly outperforms T-2 chart in terms of cost, and in some cases even detects process shifts faster than the latter. In addition, friendly software has been developed with the objective of promoting the real application of this new control chart.S90104144

Spanish ATLAS Tier-1 & Tier-2 perspective on computing over the next years

Since the beginning of the WLCG Project the Spanish ATLAS computing centers have participated with reliable and stable resources as well as personnel for the ATLAS Collaboration. Our contribution to the ATLAS Tier2s and Tier1s computing resources (disk and CPUs) in the last 10 years has been around 4-5%. In 2016 an international advisory committee recommended to revise our contribution according to the participation in the ATLAS experiment. With this scenario, we are optimizing the federation of three sites located in Barcelona, Madrid and Valencia, considering that the ATLAS collaboration has developed workflows and tools to flexibly use all the resources available to the collaboration, where the tiered structure is somehow vanishing. In this contribution, we would like to show the evolution and technical updates in the ATLAS Spanish Federated Tier2 and Tier1. Some developments we are involved in, like the Event Index project, as well as the use of opportunistic resources will be useful to reach our goal. We discuss the foreseen/proposed scenario towards a sustainable computing environment for the Spanish ATLAS community in the HL-LHC period

Computing Activities at the Spanish Tier-1 and Tier-2s for the ATLAS experiment towards the LHC Run3 and High Luminosity (HL-LHC periods)

The ATLAS Spanish Tier-1 and Tier-2s have more than 15 years of experience in the deployment and development of LHC computing components and their successful operations. The sites are already actively participating in, and even coordinating, emerging R&D computing activities developing the new computing models needed in the LHC Run3 and HL-LHC periods. In this contribution, we present details on the integration of new components, such as HPC computing resources to execute ATLAS simulation workflows; the development of new techniques to improve efficiency in a cost-effective way, such as storage and CPU federations; and improvements in Data Organization, Management and Access through storage consolidations ("data-lakes"), the use of data Caches, and improving experiment data catalogues, like Event Index. The design and deployment of novel analysis facilities using GPUs together with CPUs and techniques like Machine Learning will also be presented. ATLAS Tier-1 and Tier-2 sites in Spain are, and will be, contributing to significant R&D in computing, evaluating different models for improving performance of computing and data storage capacity in the LHC High Luminosity era

Spanish ATLAS Tier-1 &Tier-2 perspective on computing over the next years

Since the beginning of the WLCG Project the Spanish ATLAS computer centres have contributed with reliable and stable resources as well as personnel for the ATLAS Collaboration. Our contribution to the ATLAS Tier2s and Tier1s computing resources (disk and CPUs) in the last 10 years has been around 5%, even though the Spanish contribution to the ATLAS detector construction as well as the number of authors are both close to 3%. In 2015 an international advisory committee recommended to revise our contribution according to the participation in the ATLAS experiment. With this scenario, we are optimising the federation of three sites located in Barcelona, Madrid and Valencia, taking into account that the ATLAS collaboration has developed workflows and tools to flexibly use all the resources available to the collaboration, where the Tiered structure is somehow vanishing. In this contribution, we would like to show the evolution and technical updates in the ATLAS Spanish Federated Tier2 and Tier1. Some developments we are involved in, like the Event Index and Event WitheBoard projects, as well as the use of opportunistic resources will be useful to reach our goal. We discuss the foreseen/proposed scenario towards a sustainable computing environment for the Spanish ATLAS community in the HL-LHC period

Computing Activities at the Spanish Tier-1 and Tier-2s for the ATLAS experiment in the LHC Run3 period and towards High Luminosity (HL-LHC)

The ATLAS Spanish Tier-1 and Tier-2s have more than 18 years of experience in the deployment and development of LHC computing components and their successful operations. The sites are actively participating in, and even coordinating, R&D computing activities in the LHC Run3 and developing the computing models needed in HL-LHC period. In this contribution, we present details on the integration of some components, such as HPC computing resources to execute ATLAS simulation workflows; the development of new techniques to improve efficiency in a cost-effective way; and improvements in Data Organization, Management and Access through storage consolidations, the use of data Caches, and improving experiment data catalogues, like Event Index. The design and deployment of novel analysis facilities using GPUs together with CPUs and techniques like Machine Learning will also be presented. ATLAS Tier-1 and Tier-2 sites in Spain are, and will be, contributing to significant R&D in computing, evaluating different models for improving performance of computing and data storage capacity in the LHC High Luminosity era

Computing Activities at the Spanish Tier-1 and Tier-2s for the ATLAS experiment in the LHC Run3 period and towards High Luminosity (HL-LHC)

The ATLAS Spanish Tier-1 and Tier-2s have more than 18 years of experience in the deployment and development of LHC computing components and their successful operation. The sites are actively participating in, and even coordinating, R&D computing activities in the LHC Run3 and developing the computing models needed in the HL-LHC period. In this contribution, we present details on the integration of some components, such as HPC computing resources to execute ATLAS simulation workflows; the development of new techniques to improve efficiency in a cost-effective way; and improvements in Data Organization, Management and Access through storage consolidations, the use of data Caches, and improving experiment data catalogues, through contributions such as Event Index. The design and deployment of novel analysis facilities using GPUs together with CPUs and techniques like Machine Learning will also be presented. ATLAS Tier-1 and Tier-2 sites in Spain, are, and will be, contributing to significant R&D in computing and evaluating different models for improving performance of computing and data storage capacity in the LHC High Luminosity era

Impact of renal function on admission in COVID-19 patients: an analysis of the international HOPE COVID-19 (Health Outcome Predictive Evaluation for COVID 19) Registry.

Coronavirus disease 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite its international aggressive extension, with a significant morbidity and mortality, the impact of renal function on its prognosis is uncertain. Analysis from the international HOPE-Registry (NCT04334291). The objective was to evaluate the association between kidney failure severity on admission with the mortality of patients with SARS-CoV-2 infection. Patients were categorized in 3 groups according to the estimated glomerular filtration rate on admission (eGFR > 60 mL/min/1.73 m2, eGFR 30-60 mL/min/1.73 m2 and eGFR  60 mL/min/1.73 m2, eGFR 30-60 mL/min/1.73 m2 and eGFR  758 patients were included: mean age was 66 ± 18 years, and 58.6% of patient were male. Only 8.5% of patients had a history of chronic kidney disease (CKD); however, 30% of patients had kidney dysfunction upon admission (eGFR  60 vs eGFR 30-60 vs and eGFR  Renal failure on admission in patients with SARS-CoV-2 infection is frequent and is associated with a greater number of complications and in-hospital mortality. Our data comes from a multicenter registry and therefore does not allow to have a precise mortality risk assessment. More studies are needed to confirm these findings

Does there exist an obesity paradox in COVID-19? Insights of the international HOPE-COVID-19-registry.

Obesity has been described as a protective factor in cardiovascular and other diseases being expressed as 'obesity paradox'. However, the impact of obesity on clinical outcomes including mortality in COVID-19 has been poorly systematically investigated until now. We aimed to compare clinical outcomes among COVID-19 patients divided into three groups according to the body mass index (BMI). We retrospectively collected data up to May 31st, 2020. 3635 patients were divided into three groups of BMI (30 kg/m2; n = 1061). Demographic, in-hospital complications, and predictors for mortality, respiratory insufficiency, and sepsis were analyzed. The rate of respiratory insufficiency was more recorded in BMI 25-30 kg/m2 as compared to BMI 30 kg/m2 than BMI 30 kg/m2 as compared to BMI 30 kg/m2 as compared to BMI 30 kg/m2 did not impact the mortality rate (HR 1.15, 95% CI: 0.889-1.508; p = 0.27) (HR 1.15, 95% CI: 0.893-1.479; p = 0.27). In multivariate logistic regression analyses for respiratory insufficiency and sepsis, BMI HOPE COVID-19-Registry revealed no evidence of obesity paradox in patients with COVID-19. However, Obesity was associated with a higher rate of respiratory insufficiency and sepsis but was not determined as an independent predictor for a high mortality