Cómo jugar al pádel

La visión general de Cómo jugar al pádel nos introduce en el desarrollo contextualizado en el ámbito específico de la actividad física y deportiva de los deportes de raqueta. Las oportunidades que ofrece permiten obtener herramientas técnicas y tácticas para la introducción coherente en esta modalidad deportiva que, tal como se puede apreciar en la actualidad,pasa a ocupar un lugar destacado en el escaparate mundial debido fundamentalmente al número de practicantes, que aumenta de tal manera que se ha convertido en un fenómenosocial

Temporal series analysis of population cycle threshold counts as a predictor of surge in cases and hospitalizations during the SARS-CoV-2 pandemic

Tools to predict surges in cases and hospitalizations during the COVID-19 pandemic may help guide public health decisions. Low cycle threshold (CT) counts may indicate greater SARS-CoV-2 concentrations in the respiratory tract, and thereby may be used as a surrogate marker of enhanced viral transmission. Several population studies have found an association between the oscillations in the mean CT over time and the evolution of the pandemic. For the first time, we applied temporal series analysis (Granger-type causality) to validate the CT counts as an epidemiological marker of forthcoming pandemic waves using samples and analyzing cases and hospital admissions during the third pandemic wave (October 2020 to May 2021) in Madrid. A total of 22,906 SARS-CoV-2 RT-PCR-positive nasopharyngeal swabs were evaluated; the mean CT value was 27.4 (SD: 2.1) (22.2% below 20 cycles). During this period, 422,110 cases and 36,727 hospital admissions were also recorded. A temporal association was found between the CT counts and the cases of COVID-19 with a lag of 9–10 days (p ≤ 0.01) and hospital admissions by COVID-19 (p < 0.04) with a lag of 2–6 days. According to a validated method to prove associations between variables that change over time, the short-term evolution of average CT counts in the population may forecast the evolution of the COVID-19 pandemic

Effectiveness, safety/tolerability of OBV/PTV/r ± DSV in patients with HCV genotype 1 or 4 with/without HIV-1 co-infection, chronic kidney disease (CKD) stage IIIb-V and dialysis in Spanish clinical practice - Vie-KinD study

Limited data are available on the effectiveness and tolerability of direct-acting antivirals (DAAs) therapies in the real world for HCV-infected patients with comorbidities. This study aimed to describe the effectiveness of OBV/PTV/r ± DSV (3D/2D regimen) with or without ribavirin (RBV) in HCV or HCV/HIV co-infected patients with GT1/GT4 and CKD (IIIb-V stages), including those under hemodialysis and peritoneal dialysis in routine clinical practice in Spain in 2015.Non-interventional, retrospective, multicenter data collection study in 31 Spanish sites. Socio-demographic, clinical variables, study treatment characteristics, effectiveness and tolerability data were collected from medical records.Data from 135 patients with a mean age (SD) of 58.3 (11.4) years were analyzed: 92.6% GT1 (81.6% GT1b and 17.6% GT1a) and 7.4% GT4, 14 (10.4%) HIV/HCV co-infected, 19.0% with fibrosis F3 and 28.1% F4 by FibroScan®, 52.6% were previously treated with pegIFN and RBV. 11.1%, 14.8% and 74.1% of patients had CKD stage IIIb, IV and V respectively. 68.9% of patients were on hemodialysis; 8.9% on peritoneal dialysis and 38.5% had history of renal transplant. A total of 125 (96.2%) of 135 patients were treated with 3D, 10 (7.4%) with 2D and 30.4% received RBV. The overall intention-to-treat (ITT) sustained virologic response at week 12 (SVR12) was 92.6% (125/135) and the overall modified-ITT (mITT) SVR12 was 99.2% (125/126). The SVR12 rates (ITT) per sub-groups were: HCV mono-infected (91.7%), HCV/HIV co-infected (100%), GT1 (92.0%), GT4 (100%), CKD stage IIIb (86.7%), stage IV (95%) and stage V (93%). Among the 10 non-SVR there was only 1 virologic failure (0.7%); 4 patients had missing data due lost to follow up (3.0%) and 5 patients discontinued 3D/2D regimen (3.7%): 4 due to severe adverse events (including 3 deaths) and 1 patient´s decision.These results have shown that 3D/2D regimens are effective and tolerable in patients with advanced CKD including those in dialysis with GT 1 or 4 chronic HCV mono-infection and HIV/HCV coinfection in a real-life cohort. The overall SVR12 rates were 92.6% (ITT) and 99.2% (mITT) without clinically relevant changes in eGFR until 12 weeks post-treatment. These results are consistent with those reported in clinical trials

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030