1,720,970 research outputs found
The impact of early therapies for COVID-19 on death, hospitalization and persisting symptoms: a retrospective study
PurposeOral antivirals (nirmatrelvir/ritonavir and molnupiravir), intravenous short treatment of remdesivir and anti-SARS-CoV-2 monoclonal antibodies (mAbs) have been used for early COVID-19 treatments in high risk of disease progression patients. The term long COVID has been used to refer to a range of new, returning, or ongoing symptoms after SARS-CoV-2 infection. Little is known about the impact of such therapies on long COVID.MethodsThis is a retrospective observational study, including all outpatients evaluated from April 2021 to March 2022 in Brescia, Lombardy, northern Italy. Patients were stratified in three groups: (a) treated with mAbs, (b) treated with antivirals drugs and (c) controls (patients eligible for a or b who refused treatment). Data were collected at baseline and at month 1 and 3 (data on self-reported symptoms were collected using a telephone-administered questionnaire). We assessed early COVID-19 therapies effectiveness in preventing hospitalization, death at 1 or 3 months and persisting symptoms at 3 months after the onset of SARS-CoV-2 infection.ResultsA total of 649 patients were included in the study, of which 242 (37.3%) were treated with mAbs, 197 (30.3%) with antiviral drugs and 210 (32.4%) were not treated. Patients most frequently reported cerebro-cardiovascular diseases (36.7%) followed by obesity (22%). Overall, 29 patients (4.5%) died or were hospitalized at 1 or 3-month follow-up. Death or hospitalization was positively associated with older ages, with a significant linear trend (OR 3.05; 95% CI 1.16-8.06, for patients aged 80 or more years compared to those aged less than 65). Data on long COVID at 3 months were available for 323 (49.8%) patients. A positive association emerged for females compared to men, with an OR of 2.14 (95% CI 1.30-3.53) for any symptoms. Conversely, inverse associations were found for treatment groups as compared to the control one, with significant estimates among patients treated with antiviral drugs for any symptoms (OR 0.43, 95% CI 0.21-0.87) and patients treated with mAbs for any neuro-behavioral symptoms (OR 0.48, 95% CI 0.25-0.92).ConclusionsWe report beneficial effect of early use of anti-SARS-CoV-2 antivirals and mAbs on long COVID
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
Recurrent Neural Networks for Daily Estimation of COVID-19 Prognosis with Uncertainty Handling
Most ML-based applications for COVID-19 assess the general conditions of a patient trained and tested on cohorts of patients collected over a short period of time and are capable of providing an alarm a few days in advance, helping clinicians in emergency situations, monitor hospitalised patients and identify potentially critical situations at an early stage. However, the pandemic continues to evolve due to new variants, treatments, and vaccines; considering datasets over short periods could not capture this aspect. In addition, these applications often avoid dealing with the uncertainty associated with the prediction provided by machine learning models, potentially causing costly mistakes. In this work, we present a system based on Recurrent Neural Networks (RNN) for the daily estimate of the prognosis of COVID-19 patients that is built and tested using data collected over a long period of time. Our system achieves high predictive performance and uses an algorithm to effectively determine and discard those patients for whom RNN cannot predict the prognosis with sufficient confidence
Present and future of HIV pre-exposure prophylaxis: a narrative review
Introduction: Pre-exposure prophylaxis (PrEP) has revolutionized HIV prevention, reducing the risk of transmission among at-risk populations. However, challenges remain in ensuring accessibility and adherence. Recent innovations, including long-acting injectable and implantable formulations, offer promising alternatives to daily oral regimens. Areas Covered: This narrative review examines the evolution of PrEP, covering tenofovir-based oral regimens, long-acting cabotegravir, lenacapavir, and dapivirine ring, as well as alternative delivery methods, including microneedle patches, rectal douches, and subdermal implants. We conducted a comprehensive literature search of clinical trials, real-world studies, and guidelines from major health organizations to assess the efficacy, safety, and implementation strategies of the intervention. Expert Opinion: While PrEP innovations enhance HIV prevention, their impact depends on accessibility, adherence support, and integration into public health programs. Long-acting formulations reduce adherence burdens but require strategic implementation and a robust organizational structure. Expanding provider involvement and addressing social and structural barriers will be crucial to optimizing PrEP uptake. Future research should prioritize equitable access, real-world effectiveness, and combined prevention strategies to accelerate progress toward the elimination of HIV
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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