Outcomes Associated With Oral Anticoagulants Plus Antiplatelets in Patients With Newly Diagnosed Atrial Fibrillation.

Importance: Patients with nonvalvular atrial fibrillation at risk of stroke should receive oral anticoagulants (OAC). However, approximately 1 in 8 patients in the Global Anticoagulant Registry in the Field (GARFIELD-AF) registry are treated with antiplatelet (AP) drugs in addition to OAC, with or without documented vascular disease or other indications for AP therapy. Objective: To investigate baseline characteristics and outcomes of patients who were prescribed OAC plus AP therapy vs OAC alone. Design, Setting, and Participants: Prospective cohort study of the GARFIELD-AF registry, an international, multicenter, observational study of adults aged 18 years and older with recently diagnosed nonvalvular atrial fibrillation and at least 1 risk factor for stroke enrolled between March 2010 and August 2016. Data were extracted for analysis in October 2017 and analyzed from April 2018 to June 2019. Exposure: Participants received either OAC plus AP or OAC alone. Main Outcomes and Measures: Clinical outcomes were measured over 3 and 12 months. Outcomes were adjusted for 40 covariates, including baseline conditions and medications. Results: A total of 24 436 patients (13 438 [55.0%] male; median [interquartile range] age, 71 [64-78] years) were analyzed. Among eligible patients, those receiving OAC plus AP therapy had a greater prevalence of cardiovascular indications for AP, including acute coronary syndromes (22.0% vs 4.3%), coronary artery disease (39.1% vs 9.8%), and carotid occlusive disease (4.8% vs 2.0%). Over 1 year, patients treated with OAC plus AP had significantly higher incidence rates of stroke (adjusted hazard ratio [aHR], 1.49; 95% CI, 1.01-2.20) and any bleeding event (aHR, 1.41; 95% CI, 1.17-1.70) than those treated with OAC alone. These patients did not show evidence of reduced all-cause mortality (aHR, 1.22; 95% CI, 0.98-1.51). Risk of acute coronary syndrome was not reduced in patients taking OAC plus AP compared with OAC alone (aHR, 1.16; 95% CI, 0.70-1.94). Patients treated with OAC plus AP also had higher rates of all clinical outcomes than those treated with OAC alone over the short term (3 months). Conclusions and Relevance: This study challenges the practice of coprescribing OAC plus AP unless there is a clear indication for adding AP to OAC therapy in newly diagnosed atrial fibrillation

A reverse engineering approach to the suppression of citation biases reveals universal properties of citation distributions

The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions.Comment: 9 pages, 6 figures. Supporting information files available at http://filrad.homelinux.or

Characteristics Associated with Citation Rate of the Medical Literature

BACKGROUND: The citation rate for articles is viewed as a measure of their importance and impact; however, little is known about what features of articles are associated with higher citation rate. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a cohort study of all original articles, regardless of study methodology, published in the Lancet, JAMA, and New England Journal of Medicine, from October 1, 1999 to March 31, 2000. We identified 328 articles. Two blinded, independent reviewers extracted, in duplicate, nine variables from each article, which were analyzed in both univariable and multivariable linear least-squares regression models for their association with the annual rate of citations received by the article since publication. A two-way interaction between industry funding and an industry-favoring result was tested and found to be significant (p = 0.02). In our adjusted analysis, the presence of industry funding and an industry-favoring result was associated with an increase in annual citation rate of 25.7 (95% confidence interval, 8.5 to 42.8) compared to the absence of both industry funding and industry-favoring results. Higher annual rates of citation were also associated with articles dealing with cardiovascular medicine (13.3 more; 95% confidence interval, 3.9 to 22.3) and oncology (12.6 more; 95% confidence interval, 1.2 to 24.0), articles with group authorship (11.1 more; 95% confidence interval, 2.7 to 19.5), larger sample size and journal of publication. CONCLUSIONS/SIGNIFICANCE: Large trials, with group authorship, industry-funded, with industry-favoring results, in oncology or cardiology were associated with greater subsequent citations

New AI Prediction Model Using Serial PT-INR Measurements in AF Patients on VKAs: GARFIELD-AF

Aims: Most clinical risk stratification models are based on measurement at a single time-point rather than serial measurements. Artificial intelligence (AI) is able to predict one-dimensional outcomes from multi-dimensional datasets. Using data from Global Anticoagulant Registry in the Field (GARFIELD)-AF registry, a new AI model was developed for predicting clinical outcomes in atrial fibrillation (AF) patients up to 1 year based on sequential measures of prothrombin time international normalized ratio (PT-INR) within 30 days of enrolment. Methods and results: Patients with newly diagnosed AF who were treated with vitamin K antagonists (VKAs) and had at least three measurements of PT-INR taken over the first 30 days after prescription were analysed. The AI model was constructed with multilayer neural network including long short-term memory and one-dimensional convolution layers. The neural network was trained using PT-INR measurements within days 0–30 after starting treatment and clinical outcomes over days 31–365 in a derivation cohort (cohorts 1–3; n = 3185). Accuracy of the AI model at predicting major bleed, stroke/systemic embolism (SE), and death was assessed in a validation cohort (cohorts 4–5; n = 1523). The model’s c-statistic for predicting major bleed, stroke/SE, and all-cause death was 0.75, 0.70, and 0.61, respectively. Conclusions: Using serial PT-INR values collected within 1 month after starting VKA, the new AI model performed better than time in therapeutic range at predicting clinical outcomes occurring up to 12 months thereafter. Serial PT-INR values contain important information that can be analysed by computer to help predict adverse clinical outcomes

Social Network Analytics for Advanced Bibliometrics: Referring to Actor Roles of Management Journals instead of Journal Rankings

Impact factors are commonly used to assess journals relevance. This implies a simplified view on science as a single-stage linear process. Therefore, few top-tier journals are one-sidedly favored as outlets, such that submissions to top-tier journals explode whereas others are short of submissions. Consequently, the often claimed gap between research and practical application in application-oriented disciplines as business administration is not narrowing but becoming entrenched. A more complete view of the scientific system is needed to fully capture journals ´ contributions in the development of a discipline. Simple citation measures, as e.g. citation counts, are commonly used to evaluate scientific work. There are many known dangers of miss- or over-interpretation of such simple data and this paper adds to this discussion by developing an alternative way of interpreting a discipline based on the positions and roles of journals in their wider network. Specifically, we employ ideas from the network analytic approach. Relative positions allow the direct comparison between different fields. Similarly, the approach provides a better understanding of the diffusion process of knowledge as it differentiates positions in the knowledge creation process. We demonstrate how different modes of social capital create different patterns of action that require a multidimensional evaluation of scientific research. We explore different types of social capital and intertwined relational structures of actors to compare journals with different bibliometric profiles. Ultimately, we develop a multi-dimensional evaluation of actor roles based upon multiple indicators and we test this approach by classifying management journals based on their bibliometric environment

International ranking systems for universities and institutions: a critical appraisal

<p>Abstract</p> <p>Background</p> <p>Ranking of universities and institutions has attracted wide attention recently. Several systems have been proposed that attempt to rank academic institutions worldwide.</p> <p>Methods</p> <p>We review the two most publicly visible ranking systems, the Shanghai Jiao Tong University 'Academic Ranking of World Universities' and the Times Higher Education Supplement 'World University Rankings' and also briefly review other ranking systems that use different criteria. We assess the construct validity for educational and research excellence and the measurement validity of each of the proposed ranking criteria, and try to identify generic challenges in international ranking of universities and institutions.</p> <p>Results</p> <p>None of the reviewed criteria for international ranking seems to have very good construct validity for both educational and research excellence, and most don't have very good construct validity even for just one of these two aspects of excellence. Measurement error for many items is also considerable or is not possible to determine due to lack of publication of the relevant data and methodology details. The concordance between the 2006 rankings by Shanghai and Times is modest at best, with only 133 universities shared in their top 200 lists. The examination of the existing international ranking systems suggests that generic challenges include adjustment for institutional size, definition of institutions, implications of average measurements of excellence versus measurements of extremes, adjustments for scientific field, time frame of measurement and allocation of credit for excellence.</p> <p>Conclusion</p> <p>Naïve lists of international institutional rankings that do not address these fundamental challenges with transparent methods are misleading and should be abandoned. We make some suggestions on how focused and standardized evaluations of excellence could be improved and placed in proper context.</p

Research in User-Centered Design 2009 to 2018: A Systematic Keyword Network Analysis

User-centered design (UCD) has become an important concept in Human-Computer Interaction (HCI) and other disciplines. While there is abundant UCD research, keyword analysis research has been less studied even though keywords are important for achieving better understanding of UCD. Therefore, this study provides keywords network a visual analysis of UCD articles published between 2009 and 2018 to answer the following questions: (1) What UCD-related keywords have been studied and in which disciplines? and (2) How have keywords been connected to on another? The study analyzed 304 keywords articles from IEEE, ACM, and ScienceDirect that included “UCD” in their titles. It utilized Gephi 0.9.2 to visualize keyword frequencies, relationships, and authors’ disciplines. The findings presented that the five most frequently mentioned keywords regarding UCD were “usability,” “HCI,” “User Experiences,” “User-Centered,” and “User Interfaces”. The top five most identified disciplines in the UCD articles were Computer Science, Design, Engineering, Education, and Psychology. In visualizing this data, we created a keyword hierarchy with various sizes of texts and circles, and we denoted various relationship levels between keywords by different weights of edges. This visualization of the selected 43 keywords shows a clear relationship between keywords in which UCD is strongly related to usability, UX, user-centered, HCI, Persona, prototype, interaction design, interface design, assistive technology, design thinking. The findings can be valuable in understanding the current UCD research mainstream for researchers and designers pursuing interdisciplinary approaches

Electrohysterographic characterization of the uterine myoelectrical response to labor induction drugs

[EN] Labor induction is a common practice to promote uterine contractions and labor onset. Uterine electrohysterogram (EHG) has proved its suitability for characterizing the uterus electrophysiological condition in women with spontaneous labor. The aim of this study was to characterize and compare uterine myoelectrical activity during the first 4h in response to labor induction drugs, Misoprostol (G1) and Dinoprostone (G2), by analyzing the differences between women who achieved active phase of labor and those who did not (successful and failed inductions). A set of temporal, spectral and complexity parameters were computed from the EHG-bursts. As for successful inductions, statistical significant and sustained increases with respect to basal period were obtained for EHG amplitude, mean frequency, uterine activity index (UAI) and Teager, after 60¿ for the G1 group; duration, amplitude, number of contractions and UAI for the G2 group, after 120¿. Moreover, Teager showed statistical significant and sustained differences between successful and failed inductions (1.43±1.45 µV2.Hz2.105 vs. 0.40±0.26 µV2.Hz2.105 after 240¿) for the G1 group, but not in the G2 group, probably due to the slower pharmacokinetics of this drug. These results revealed that EHG could be useful for successful induction prediction in the early stages of induction, especially when using Misoprostol.This research project was supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (DPI2015-68397-R) and by the company Bial SA.Benalcazar-Parra, C.; Ye Lin, Y.; Garcia Casado, J.; Monfort-Orti, R.; Alberola Rubio, J.; Perales Marín, AJ.; Prats-Boluda, G. (2018). Electrohysterographic characterization of the uterine myoelectrical response to labor induction drugs. Medical Engineering & Physics. 56:27-35. https://doi.org/10.1016/j.medengphy.2018.04.002S27355