102,422 research outputs found

    Respiratory Syncytial Virus Prefusion F Protein Vaccine Is Efficacious in Older Adults With Underlying Medical Conditions

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    Background: Older adults with chronic cardiorespiratory or endocrine/metabolic conditions are at increased risk of respiratory syncytial virus (RSV)-related acute respiratory illness (RSV-ARI) and severe respiratory disease. In an ongoing, randomized, placebo-controlled, multicountry, phase 3 trial in ≥60-year-old participants, an AS01E-adjuvanted RSV prefusion F protein-based vaccine (RSVPreF3 OA) was efficacious against RSV-related lower respiratory tract disease (RSV-LRTD), severe RSV-LRTD, and RSV-ARI. We evaluated efficacy and immunogenicity among participants with coexisting cardiorespiratory or endocrine/metabolic conditions that increase the risk of severe RSV disease ("conditions of interest"). Methods: Medically stable ≥60-year-old participants received 1 dose of RSVPreF3 OA or placebo. Efficacy against first RSV-LRTD and RSV-ARI episodes was assessed in subgroups with/without coexisting cardiorespiratory or endocrine/metabolic conditions of interest. Immunogenicity was analyzed post hoc in these subgroups. Results: In total, 12 467 participants received RSVPreF3 OA and 12 499 received placebo. Of these, 39.6% (RSVPreF3 OA) and 38.9% (placebo) had ≥1 coexisting condition of interest. The median efficacy follow-up was 6.7 months. Efficacy against RSV-LRTD was high in participants with ≥1 condition of interest (94.6%), ≥1 cardiorespiratory (92.1%), ≥1 endocrine/metabolic (100%), and ≥2 conditions of interest (92.0%). Efficacy against RSV-ARI was 81.0% in participants with ≥1 condition of interest (88.1% for cardiorespiratory, 79.4% for endocrine/metabolic conditions) and 88.0% in participants with ≥2 conditions of interest. Postvaccination neutralizing titers were at least as high in participants with ≥1 condition of interest as in those without. Conclusions: RSVPreF3 OA was efficacious against RSV-LRTD and RSV-ARI in older adults with coexisting medical conditions associated with an increased risk of severe RSV disease

    Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

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    Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

    Criteria for identifying knapping skill level through the analysis of lithic cores : An example from Val Lastari, Late Paleolithic, Italy

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    The application of knapping skill analysis has increased over the years, starting from the Eighties and, by now, being employed all over the world on different material cultures and chronological periods. We studied the cores reduced at Val Lastari, a Recent Epigravettian lithic workshop in north-eastern Italy, for recognizing the most influential technological variables to define stoneknapping behaviours. In our case, knapping accidents and cores appearance had more weight than criteria such as core preparation and raw material features thanks to the strategies of exploitation chosen by hunter-gatherers of Val Lastari, and to the ecological context they interacted with. This is the first time that a study of its kind has been proposed for an Italian site, becoming a unique possibility to enrich our knowledge about Epigravettian social learning and organization with new and stimulating information

    Some two-sample tests for simultaneously comparing both parameters of the shifted exponential models

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    This paper investigates the power performance of five tests, including improved versions of two existing tests, for jointly testing the equality of origin and scale parameters of two samples from a shifted (two-parameter) exponential distribution. The power of the test varies with a shift in either or both of the two parameters. Therefore, a power surface is observed for various tests. Different tests are optimal for different shift sizes. This paper also compares the volume under the five tests’ power surfaces to determine an overall best when the shift size is unknown. The generalized likelihood ratio (GLR) test, the Bayoud and Kittaneh test based on Weitzman’s overlapping coefficient, recently designed Max and Distance tests, and an improved likelihood-based procedure are compared. The shifted exponential distribution is often an appropriate probability model for the lifetime of a product with a warranty, high voltage current in specific semiconductor transistors, and military personnel vehicles’ mileages that failed in operation. The number of survival days for patients with irreversible lung cancer often follows the same distribution. This distribution plays a vital role in the engineering and biomedical sciences. We observe that the newly designed tests and the exact GLR test are almost always preferable to the other tests. We illustrate the proposed exact test procedures with two practical examples

    Methodology to Monitor Early Warnings Before Gas Turbine Trip

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    The current energy scenario requires that gas turbines (GTs) operate at their maximum efficiency and highest reliability. Trip is one of the most disrupting events that reduces GT availability and increases maintenance costs. To tackle the challenge of GT trip prediction, this paper presents a methodology that has the goal of monitoring the early warnings raised during GT operation and trigger an alert to avoid trip occurrence. The methodology makes use of an auto-encoder (prediction model) and a three-stage criterion (detection procedure). The auto-encoder is first trained to reconstruct safe operation data and subsequently tested on new data collected before trip occurrence. The trip detection criterion checks whether the individually tested data points should be classified as normal or anomalous (first stage), provides a warning if the anomaly score over a given time frame exceeds a threshold (second stage), and, finally, combines consecutive warnings to trigger a trip alert in advance (third stage). The methodology is applied to a real-world case study composed of a collection of trips, of which the causes may be different, gathered from various GTs in operation during several years. Historical observations of gas path measurements taken during three days of GT operation before trip occurrence are employed for the analysis. Once optimally tuned, the methodology provides a trip alert with a reliability equal to 75%at least 10 h in advance before trip occurrence

    Machine learning from real data: A mental health registry case study

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    Imbalanced datasets can impair the learning performance of many Machine Learning techniques. Nevertheless, many real-world datasets, especially in the healthcare field, are inherently imbalanced. For instance, in the medical domain, the classes representing a specific disease are typically the minority of the total cases. This challenge justifies the substantial research effort spent in the past decades to tackle data imbalance at the data and algorithm levels. In this paper, we describe the strategies we used to deal with an imbalanced classification task on data extracted from a database generated from the Electronic Health Records of the Mental Health Service of the Ferrara Province, Italy. In particular, we applied balancing techniques to the original data, such as random undersampling and oversampling, and Synthetic Minority Oversampling Technique for Nominal and Continuous (SMOTE-NC). In order to assess the effectiveness of the balancing techniques on the classification task at hand, we applied different Machine Learning algorithms. We employed cost-sensitive learning as well and compared its results with those of the balancing methods. Furthermore, a feature selection analysis was conducted to investigate the relevance of each feature. Results show that balancing can help find the best setting to accomplish classification tasks. Since real-world imbalanced datasets are increasingly becoming the core of scientific research, further studies are needed to improve already existing techniqu

    Per un welfare di comunità. Organizzazione e lavoro nella sanità territoriale

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    Il volume Per un welfare di comunità. Organizzazione e lavoro nella sanità territoriale raccoglie gli atti del Convegno di studi svoltosi a Ferrara il 23 giugno 2023. Affronta, in chiave interdisciplinare, alcune delle questioni più attuali legate alla c.d. prima linea della tutela della salute, sul piano territoriale e della comunità delle persone. In una fase di transizione verso nuovi modelli organizzativi di welfare più prossimi ai cittadini, ci si interroga sulla prospettiva del cambiamento tra risorse, nuovi investimenti e criticità realizzative, senza perdere di vista i principi alla base del Servizio Sanitario Nazionale

    Predicting in-hospital mortality in patients admitted from the emergency department for pulmonary embolism: Incidence and prognostic value of deep vein thrombosis. A retrospective study

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    Background Pulmonary embolism (PE) is one of the most common causes of death from cardiovascular disease. Although deep vein thrombosis (DVT) is the leading cause of PE, its prognostic role is unclear. This study investigated the incidence and prognostic value of DVT in predicting in-hospital mortality (IHM) in patients admitted from the emergency department (ED) for PE.Methods This retrospective cohort study was conducted in the ED of a third-level university hospital. Patients over 18 years admitted for PE between 1 January 2018 and 31 December 2022 were included.Results Five hundred and thirty patients (mean age 73.13 years, 6% IHM) were included. 69.1% of cases had DVT (36.4% unilateral femoral vein, 3.6% bilateral, 39.1% unilateral popliteal vein, 2.8% bilateral, 45.7% distal vein thrombosis and 7.4% iliocaval involvement). Patients who died in hospital had a higher Pulmonary Embolism Severity Index (PESI) (138.6 vs. 99.65, p < 0.001), European Society of Cardiology risk class (15.6% vs. 1%, intermediate-high in 50% vs. 6.4%, p < 0.001) and more DVT involving the iliac-caval vein axis (18.8% vs. 6.6%, p = 0.011). PESI class >II, right ventricular dysfunction, increased blood markers of myocardial damage and involvement of the iliocaval venous axis were independent predictors of IHM on multivariate analysis.Conclusions Although further studies are needed to confirm the prognostic role of DVT at PE, involvement of the iliocaval venous axis should considered to be a sign of a higher risk of IHM and may be a key factor in prognostic stratification

    Changing structures in transnational research networks: an analysis of the impact of COVID-19 on China's scientific collaborations

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    Research networks play pivotal roles in the creation and diffusion of knowledge. It is widely acknowledged that frontier research tends to cluster around transnational research networks (TRNs), which also represent strategic tools for nurturing innovation in R&D-intensive companies. Therefore, they are crucial for promoting the rapid development of the knowledge economy in underdeveloped countries. In this context, China's experience is particularly relevant because the country has invested heavily in knowledge production, which is arguably one of the most important structural changes at the global level in recent decades, with important implications for the division of labor and trade among countries. The country has been investing in order to become the scientific world leader, and in this transition, research collaboration, in particular with other countries, can become strategic. In this work, we analyze whether COVID-19 and related research have affected the shape of the network and the intensity of collaborations involving China in the field of health studies, comparing it to the case of the U.S. as the global leader in research (Fry et al., 2020). In particular, we wish to assess whether COVID-19-related research has pushed toward larger and more intensive collaborations internationally than before the pandemic or whether a tendency to closure has prevailed has prevailed. This also means understanding whether COVID-19, as a global phenomenon, has affected China in rising as an international research leader. To do so, we built an original dataset of international, coauthored publications involving China or the U.S. in selected health research fields. Our analysis first shows that COVID-19 research has assumed specific features distinct from other topics in the same research field, shaping research networks in a peculiar way for both China and the U.S. Second, for China, COVID-19 does not appear to have represented an opportunity to further climb up the international research ladder, as it has attracted a relatively low and more volatile number of collaborators from different countries

    Carbonate factory response through the MECO (Middle Eocene Climate Optimum) event: Insight from the Apulia Carbonate Platform, Gargano Promontory, Italy

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    During the Eocene, shallow-water carbonate systems were significantly impacted by climate fluctuations and hyperthermal events. Following the peak temperatures of the Early Eocene Climatic Optimum (EECO), a general cooling trend began, with short-lived (⁓200 kyr) warming events occurring alongside it. In the early Bartonian (around 40.1 Ma), a warming event known as the Middle Eocene Climatic Optimum (MECO) occurred, lasting approximately 500,000 years. In this scenario, the types and calcification rates of marine organisms such as corals and larger benthic foraminifera (LBF) were influenced by global CO2 and oceanographic changes, which had a major effect on photic carbonate factories. To better understand the effects of these factors on carbonate factories, a detailed study of shallow-water facies types, distributions, and evolution was conducted. The Middle Eocene Monte Saraceno sequence, located on the eastern margin of the Apulia Carbonate Platform (Gargano Promontory, southern Italy), was selected as a case study to investigate the relationships between carbonate factory types and climatic changes around theMECO event. This study identified twodistinct intervalswith different modes of carbonate production, separated by a sharp boundary. The lower interval consists of clinostratified, thick beds of rudstone to floatstone, mostly made up of various large Nummulites tests, indicating an early Bartonian age (Shallow Benthic Zone 17). Instead, the upper interval consists of coral floatstone to rudstone with a packstone matrix, rich in branching corals in association with gastropods, bivalves, and rare small larger benthic foraminifera. The appearance of Heterostegina sp. and Glomalveolina ungaroi in this interval indicates a late Bartonian age (Shallow Benthic Zone 18). By integrating biostratigraphic and stable-isotope data, the lower interval, with abundant Nummulites, was linked to the MECO event, duringwhich higher sea-surface temperatures seem to enhance larger benthic foraminifera proliferation, as already occurred in the Early Eocene. However, in the late Bartonian, the sharp transition to a coral-dominated carbonate factory,with rare larger benthic foraminifera showing smaller sizes, could be attributed to a drop in temperature that created the conditions more favourable to corals. Overall, this study provides compelling evidence of how environmental changes can affect marine carbonate production, also highlighting the importance of investigating these relationships, to better understand climate change in the past, present and near future
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