1,721,168 research outputs found
Biochemical biomarkers alterations in Coronavirus Disease 2019 (COVID-19)
Full text linkCoronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a respiratory disease, which can evolve into multiorgan failure (MOF), leading to death. Several biochemical alterations have been described in COVID-19 patients. To date, many biomarkers reflecting the main pathophysiological characteristics of the disease have been identified and associated with the risk of developing severe disease. Lymphopenia represents the hallmark of the disease, and it can be detected since the early stage of infection. Increased levels of several inflammatory biomarkers, including c-reactive protein, have been found in COVID-19 patients and associated with an increased risk of severe disease, which is characterised by the so-called "cytokine storm". Also, the increase of cardiac and liver dysfunction biomarkers has been associated with poor outcome. In this review, we provide an overview of the main biochemical characteristics of COVID-19 and the associated biomarkers alterations
Do European Cohesion Policies Mitigate the Impact of Fiscal Consolidation on Regional Income Inequality?
Full text linkIn this paper we investigate the role of EU Structural and Investment Funds in affecting the dynamic impact of regional fiscal consolidation on regional income inequality. Relying on a panel of 162 NUTS-2 regions of twelve European countries, we find that regional spending cuts increase regional inequality in the medium-term, with the effects surviving to a large battery of robustness checks. The uneven distributional impact of regional austerity measures is however cushioned by larger EU funds expenditures, especially through the European Regional Development Fund (ERDF), with the effect magnified during periods of recession and when the regional quality of government is higher
Biomarkers for prognosis and treatment response in covid-19 patients
No full textDuring a severe infection such as coronavirus disease 2019 (COVID-19), the level of almost all analytes can change, presenting a correlation with disease severity and survival; however, a biomarker cannot be translated into clinical practice for treatment guidance until it is proven to have a significant impact. Several studies have documented the association between COVID-19 severity and circulating levels of C-reactive protein (CRP) and interleukin-6, and the accuracy of the CRP level in predicting treatment responses has been evaluated. Moreover, promising findings on prothrombin and D-dimer have been reported. However, the clinical usefulness of these biomarkers in COVID-19 is far from proven. The burst of data generation during this pandemic has led to the publication of numerous studies with several notable drawbacks, weakening the strength of their findings. We provide an overview of the key findings of studies on biomarkers for the prognosis and treatment response in COVID-19 patients. We also highlight the main drawbacks of these studies that have limited the clinical use of these biomarkers
Rehabilitation following injury of the rotator cuff
Full text linkThe main aim of this paper is to compare two diffrent rehabilitation tecniques for treatment of the shoulder joint following injury of the rotator cuff. The seriousness of the pathology means patients generally have to endure a considerable period during wich use of the joint in question is impossibl
Metabolic Syndrome
No full textMetabolic syndrome is a biochemical-clinical condition characterized by resistance to insulin action associated with a proinflammatory and prothrombotic state. It represents an important cardiovascular risk factor with a constantly increasing incidence in the general population; therefore, its early detection is fundamental to implement preventive interventions. This chapter describes the main characteristics of metabolic syndrome and the criteria used to diagnose it
The Housing Cycle: What Role for Mortgage Market Development and Housing Finance?
Full text linkWe use duration analysis to assess the impact of securitization, mortgage sector liberalization and government involvement in housing finance on the length of housing booms, busts and normal times in a panel of 20 OECD countries over the period 1970Q1-2015Q4. Our results reveal that a move towards a more liberalized mortgage sector is associated with longer housing booms, while an increase in securitization is linked with shorter housing busts. They also show that the length of housing booms and busts is particularly sensitive to housing finance characteristics, but that does not seem to be the case for normal times. Additionally, government support measures do not necessarily cushion against housing busts. A careful assessment of their distributional impact, as well as their effect on the trade-off between liquidity and guarantee/loan provision, is also required to prevent (longer) housing booms. All in all, housing finance regulation may prove especially relevant to shield against the damaging effects of housing busts and the financial stability risks associated with housing booms. Monetary policy can also be an important complement to macro-prudential policies. Finally, government participation in housing finance should be designed in a way that avoids an undesirable amplification of house price fluctuations
Hydroelectrolytic Disorders
No full textMaintaining body fluid and electrolyte balance is of paramount importance for normal functioning. Any alteration in this balance falls under the definition of “hydroelectrolytic disorders.”
Fever of Unknown Origin
No full textThe term fever of unknown origin (FUO) indicates febrile illnesses with a temperature above 38.3 °C for which an etiological diagnosis has not yet been formulated after 3 days of hospitalization or after three specialist visits. Certainly, in this context, the clinical laboratory provides essential elements to guide the etiological diagnosis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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