2,135 research outputs found
Modelización de la formación isotérmica de ferrita idiomórfica en aceros de medio carbono microaleados con vanadio-titanio
Facing climate change and improving emergency responses in Southern America by analysing urban cyclonic wind events
Funding Information: Funding for open access charge: Universidad de Granada / CBUA. Publisher Copyright: © 2023 The AuthorsPeer reviewedPublisher PD
RESECCIÓN HISTEROSCÓPICA DEL SEPTO UTERINO EN MUJERES INFÉRTILES
Análisis retrospectivo de 11 pacientes con útero septado sintomático que fueron tratadas con metroplastía histeroscópica en un período de 10 años. Estas pacientes presentaban un total de 16 embarazos, con 14 abortos de primer trimestre y 2 partos pretérmino inmaduros con neomortinatos, sin niños vivos. El propósito de este estudio fue mostrar la eficacia de la histeroscopia quirúrgica en resolver esta patología y mejorar el pronóstico reproductivo. Se intervinieron 7 pacientes con septo parcial y 4 con septo completo. En 8 casos hubo resección del tabique con resectoscopio y en 3 con tijera histeroscópica flexible. Se obtuvo embarazo de término en 6 pacientes (55%) con recién nacidos normales. De las 5 pacientes que no embarazaron, 3 tenían infertilidad por factor tuboperitoneal extenso, una sin relación de pareja y otra sin controles. Se demuestra la utilidad de la resección histeroscópica del útero septado en cuanto al menor tiempo de hospitalización, la baja morbilidad y los buenos resultados reproductivo
A multi-stakeholder multicriteria decision analysis for the reimbursement of orphan drugs (FinMHU-MCDA study)
Background: Patient access to orphan medicinal products (OMPs) is limited and varies between countries, reimbursement decisions on OMPs are complex, and there is a need for more transparent processes to know which criteria should be considered to inform these decisions. This study aimed to determine the most relevant criteria for the reimbursement of OMPs in Spain, from a multi-stakeholder perspective, and using multicriteria decision analysis (MCDA). Methods: An MCDA was developed in 3 phases and included 28 stakeholders closely related to the field of rare diseases (6 physicians, 5 hospital pharmacists, 7 health economists, 4 patient representatives and 6 members from national and regional health authorities). Initially [phase A], a bibliographic review was conducted to identify the potential reimbursement criteria. Then, a reduced advisory board (8 members) proposed, selected, and defined the final list of criteria that could be relevant for reimbursement. A discrete choice experiment (DCE) [phase B] was developed to determine the relevance and relative importance weight of such criteria according to the stakeholders’ preferences by choosing between pairs of hypothetical financing scenarios. A multinomial logit model was fitted to analyze the DCE responses. Finally [phase C], the advisory board review the results using a deliberative process. Results: Thirteen criteria were selected, related to 4 dimensions: patient population, disease, treatment, and economic evaluation. Nine criteria were deemed relevant for decision-making and associated with a higher relative importance: Health-related quality of life (HRQL) (23.53%), treatment efficacy (14.64%), availability of treatment alternatives (13.51%), disease severity (12.62%), avoided costs (11.21%), age of target population (7.75%), safety (seriousness of adverse events) (4.72%), quality of evidence (3.82%) and size of target population (3.12%). The remaining criteria had a < 3% relative importance: economic burden of disease (2.50%), cost of treatment (1.73%), cost-effectiveness (0.83%) and safety (frequency of adverse events) (0.03%). Conclusion: The reimbursement of OMPs in Spain should be determined by its effect on patient’s HRQL, the extent of its therapeutic benefit from efficacy and the availability of other therapeutic options. Furthermore, the severity of the rare disease should also influence the decision along with the potential of the treatment to avoid associated costs
Palbociclib in combination with endocrine therapy versus capecitabine in hormonal receptor-positive, human epidermal growth factor 2-negative, aromatase inhibitor-resistant metastatic breast cancer: a phase III randomised controlled trial—PEARL
Background: Palbociclib plus endocrine therapy (ET) is the standard treatment of hormone receptor-positive and human epidermal growth factor receptor 2-negative, metastatic breast cancer (MBC). However, its efficacy has not been compared with that of chemotherapy in a phase III trial. Patients and methods: PEARL is a multicentre, phase III randomised study in which patients with aromatase inhibitor (AI)-resistant MBC were included in two consecutive cohorts. In cohort 1, patients were randomised 1 : 1 to palbociclib plus exemestane or capecitabine. On discovering new evidence about estrogen receptor-1 (ESR1) mutations inducing resistance to AIs, the trial was amended to include cohort 2, in which patients were randomised 1 : 1 between palbociclib plus fulvestrant and capecitabine. The stratification criteria were disease site, prior sensitivity to ET, prior chemotherapy for MBC, and country of origin. Co-primary endpoints were progression-free survival (PFS) in cohort 2 and in wild-type ESR1 patients (cohort 1 + cohort 2). ESR1 hotspot mutations were analysed in baseline circulating tumour DNA. Results: From March 2014 to July 2018, 296 and 305 patients were included in cohort 1 and cohort 2, respectively. Palbociclib plus ET was not superior to capecitabine in both cohort 2 [median PFS: 7.5 versus 10.0 months; adjusted hazard ratio (aHR): 1.13; 95% confidence interval (CI): 0.85-1.50] and wild-type ESR1 patients (median PFS: 8.0 versus 10.6 months; aHR: 1.11; 95% CI: 0.87-1.41). The most frequent grade 3-4 toxicities with palbociclib plus exemestane, palbociclib plus fulvestrant and capecitabine, respectively, were neutropenia (57.4%, 55.7% and 5.5%), hand/foot syndrome (0%, 0% and 23.5%), and diarrhoea (1.3%, 1.3% and 7.6%). Palbociclib plus ET offered better quality of life (aHR for time to deterioration of global health status: 0.67; 95% CI: 0.53-0.85). Conclusions: There was no statistical superiority of palbociclib plus ET over capecitabine with respect to PFS in MBC patients resistant to AIs. Palbociclib plus ET showed a better safety profile and improved quality of life
Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications
Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02.
PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc
Regional development gaps in Argentina: A multidimensional approach to identify the location of policy priorities
Spatial inequalities within Latin American countries have historically attracted the interest ofacademics, policy-makers, and international agencies. This article aims to provide amultidimensional diagnosis of provincial development gaps in Argentina, in order to identifythe location of policy priorities. Therefore, we built a large database, which covers sevendevelopment dimensions, and applied multivariate analysis techniques to overcome someanalytical limitations of previous studies. Results show the stability of provincial developmentgaps between 2003 and 2013 and some heterogeneity within geographic regions. Instead,cluster analysis offers a better classification of Argentine provinces according to theirdevelopment gaps, which can help the government to prioritize the places wheredevelopment policies are strategic.Fil: Niembro, Andrés Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Universidad Nacional de Río Negro; ArgentinaFil: Sarmiento, Jesica Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Universidad Nacional de Río Negro; Argentin
Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications
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