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Träfflista för sökning "WFRF:(Gutiérrez Eduardo) srt2:(2020-2023)"

Sökning: WFRF:(Gutiérrez Eduardo) > (2020-2023)

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1.
  • Axfors, Cathrine, et al. (författare)
  • Association between convalescent plasma treatment and mortality in COVID-19 : a collaborative systematic review and meta-analysis of randomized clinical trials
  • 2021
  • Ingår i: BMC Infectious Diseases. - : BioMed Central (BMC). - 1471-2334. ; 21:1
  • Forskningsöversikt (refereegranskat)abstract
    • Background: Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, ). Methods: In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the Hartung-Knapp-Sidik-Jonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. Results: A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I-2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. Conclusions: Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care.
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2.
  • Micah, Angela E., et al. (författare)
  • Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
  • 2021
  • Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
  • Forskningsöversikt (refereegranskat)abstract
    • Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.
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3.
  • Almeida, Tiago Rodrigues de, 1996-, et al. (författare)
  • Context-free Self-Conditioned GAN for Trajectory Forecasting
  • 2022
  • Ingår i: 21st IEEE International Conference on Machine Learning and Applications. ICMLA 2022. - : IEEE. - 9781665462839 ; , s. 1218-1223
  • Konferensbidrag (refereegranskat)abstract
    • In this paper, we present a context-free unsupervised approach based on a self-conditioned GAN to learn different modes from 2D trajectories. Our intuition is that each mode indicates a different behavioral moving pattern in the discriminator's feature space. We apply this approach to the problem of trajectory forecasting. We present three different training settings based on self-conditioned GAN, which produce better forecasters. We test our method in two data sets: human motion and road agents. Experimental results show that our approach outperforms previous context-free methods in the least representative supervised labels while performing well in the remaining labels. In addition, our approach outperforms globally in human motion, while performing well in road agents.
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4.
  • Almeida, Tiago, 1996-, et al. (författare)
  • THÖR-Magni : Comparative Analysis of Deep Learning Models for Role-Conditioned Human Motion Prediction
  • 2023
  • Ingår i: 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). - : IEEE. - 9798350307450 - 9798350307443 ; , s. 2192-2201
  • Konferensbidrag (refereegranskat)abstract
    • Autonomous systems, that need to operate in human environments and interact with the users, rely on understanding and anticipating human activity and motion. Among the many factors which influence human motion, semantic attributes, such as the roles and ongoing activities of the detected people, provide a powerful cue on their future motion, actions, and intentions. In this work we adapt several popular deep learning models for trajectory prediction with labels corresponding to the roles of the people. To this end we use the novel THOR-Magni dataset, which captures human activity in industrial settings and includes the relevant semantic labels for people who navigate complex environments, interact with objects and robots, work alone and in groups. In qualitative and quantitative experiments we show that the role-conditioned LSTM, Transformer, GAN and VAE methods can effectively incorporate the semantic categories, better capture the underlying input distribution and therefore produce more accurate motion predictions in terms of Top-K ADE/FDE and log-likelihood metrics.
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5.
  • Alonso-Rosa, Manuel, et al. (författare)
  • An IoT based mobile augmented reality application for energy visualization in buildings environments
  • 2020
  • Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 10:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Augmented reality (AR) improves how we acquire, understand, and display information without distracting us from the real world. These technologies can be used in different applications and industries as they can incorporate domain-specific visualizations on a real-world screen. Mobile augmented reality (MAR) essentially consists of superimposing virtual elements over real objects on the screen, to give added value and enrich the interaction with reality. In numerous plants, it is being used for maintenance and repair tasks, as well as training. The Internet of Things (IoT) is increasingly pervading every aspect of our lives, including the power infrastructure of our buildings. IoT-enabled devices offer many connectivity options for helping supervise all-important energy assets. Aggregating data to cloud-based platforms enables operations teams to have on-time information access to make fast decisions and have a fast response regarding energy use, while maintenance teams keep on top of the appliance power quality and reliability needed by using MAR. This paper presents a novel approximation for visualizing appliance-related power quality to enhance awareness about the consumed electricity. A combined solution of MAR with IoT technologies is employed. Engineered solutions’ hands-free way to get data about surrounding appliances reduces the complexity, saves energy, and speeds up the operations. An innovative way to measure things at the right time leads to a competitive advantage.
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6.
  • Baenas, Isabel, et al. (författare)
  • Does Confinement Affect Treatment Dropout Rates in Patients With Gambling Disorder? A Nine-Month Observational Study
  • 2021
  • Ingår i: Frontiers in Psychology. - : Frontiers Media SA. - 1664-1078. ; 12
  • Tidskriftsartikel (refereegranskat)abstract
    • Background and Aims: COVID-19 pandemic and confinement have represented a challenge for patients with gambling disorder (GD). Regarding treatment outcome, dropout may have been influenced by these adverse circumstances. The aims of this study were: (a) to analyze treatment dropout rates in patients with GD throughout two periods: during and after the lockdown and (b) to assess clinical features that could represent vulnerability factors for treatment dropout. Methods: The sample consisted of n=86 adults, mostly men (n=79, 91.9%) and with a mean age of 45years old (SD=16.85). Patients were diagnosed with GD according to DSM-5 criteria and were undergoing therapy at a Behavioral Addiction Unit when confinement started. Clinical data were collected through a semi-structured interview and protocolized psychometric assessment. A brief telephone survey related to COVID-19 concerns was also administered at the beginning of the lockdown. Dropout data were evaluated at two moments throughout a nine-month observational period (T1: during the lockdown, and T2: after the lockdown). Results: The risk of dropout during the complete observational period was R=32/86=0.372 (37.2%), the Incidence Density Rate (IDR) ratio T2/T1 being equal to 0.052/0.033=1.60 (p=0.252). Shorter treatment duration (p=0.007), lower anxiety (p=0.025), depressive symptoms (p=0.045) and lower use of adaptive coping strategies (p=0.046) characterized patients who abandoned treatment during the lockdown. Briefer duration of treatment (p=0.001) and higher employment concerns (p=0.044) were highlighted in the individuals who dropped out after the lockdown. Treatment duration was a predictor of dropout in both periods (p=0.005 and p<0.001, respectively). Conclusion: The present results suggest an impact of the COVID-19 pandemic on treatment dropout among patients with GD during and after the lockdown, being treatment duration a predictor of dropout. Assessing vulnerability features in GD may help clinicians identify high-risk individuals and enhance prevention and treatment approaches in future similar situations.
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7.
  • Calatrava-Nicolás, Francisco M., et al. (författare)
  • Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities
  • 2021
  • Ingår i: Sensors. - : MDPI. - 1424-8220. ; 21:20
  • Tidskriftsartikel (refereegranskat)abstract
    • The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot's autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.
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8.
  • Cruz, Raquel, et al. (författare)
  • Novel genes and sex differences in COVID-19 severity
  • 2022
  • Ingår i: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 31:22, s. 3789-3806
  • Tidskriftsartikel (refereegranskat)abstract
    • Here, we describe the results of a genome-wide study conducted in 11 939 coronavirus disease 2019 (COVID-19) positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (P < 5 × 10−8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (P = 1.3 × 10−22 and P = 8.1 × 10−12, respectively), and for variants in 9q21.32 near TLE1 only among females (P = 4.4 × 10−8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (P = 2.7 × 10−8) and ARHGAP33 (P = 1.3 × 10−8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative (HGI) confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, P = 4.1 × 10−8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (<60 or ≥60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.
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9.
  • Dufey, Estefanie, et al. (författare)
  • Genotoxic stress triggers the activation of IRE1α-dependent RNA decay to modulate the DNA damage response
  • 2020
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11
  • Tidskriftsartikel (refereegranskat)abstract
    • The molecular connections between homeostatic systems that maintain both genome integrity and proteostasis are poorly understood. Here we identify the selective activation of the unfolded protein response transducer IRE1α under genotoxic stress to modulate repair programs and sustain cell survival. DNA damage engages IRE1α signaling in the absence of an endoplasmic reticulum (ER) stress signature, leading to the exclusive activation of regulated IRE1α-dependent decay (RIDD) without activating its canonical output mediated by the transcription factor XBP1. IRE1α endoribonuclease activity controls the stability of mRNAs involved in the DNA damage response, impacting DNA repair, cell cycle arrest and apoptosis. The activation of the c-Abl kinase by DNA damage triggers the oligomerization of IRE1α to catalyze RIDD. The protective role of IRE1α under genotoxic stress is conserved in fly and mouse. Altogether, our results uncover an important intersection between the molecular pathways that sustain genome stability and proteostasis.
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10.
  • Granero, Roser, et al. (författare)
  • Phenotype of Gambling Disorder Patients with Lotteries as a Preferred Form of Gambling
  • 2023
  • Ingår i: International Journal of Mental Health and Addiction. - : Springer Science and Business Media LLC. - 1557-1874 .- 1557-1882. ; 21, s. 3306-3329
  • Tidskriftsartikel (refereegranskat)abstract
    • Lottery gambling can become an addictive behavior which can significantly interfere with daily functioning. The objectives of this work were to estimate the prevalence of lottery gambling, to assess the profile related to this gambling type in a large clinical sample of patients who met criteria for gambling disorder (GD), and to compare this profile with the other two non-strategic forms of gambling (slot-machines and bingo). Sample included n = 3,531 patients consecutively attended for treatment-seeking due to gambling-related problems. All the participants met criteria for GD and were into the range of 18 to 85 years old. Sociodemographic variables, GD severity, psychopathological state, and personality traits were assessed. Statistical comparisons between the groups defined by the patients’ gambling preference (lotteries versus other gambling activities) were conducted, with chi-square test and analysis of variance. The prevalence of lotteries as the only gambling activity was 2.5%, 8.9% for lottery gambling as primary activity with other secondary gambling types, and 20.6% for lotteries as primary or secondary gambling activity. Lottery gambling and bingo gambling were more prevalent among women (bingo included the highest percentage of women). Compared to slot machine gambling, lotteries and bingo grouped older patients and those with later age of onset of the gambling-related problems. Bingo gambling showed the highest psychological distress and the most dysfunctional personality traits. This study shows the high frequency of lottery gambling among treatment-seeking for GD patients, and it provides empirical evidence about the profile associated with this gambling activity compared to other non-strategic gambling forms. The likelihood of lottery gambling is higher for women, patients married or living with a stable partner, and those within higher social position indexes.
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