1,720,957 research outputs found
Empowering Health Care Actors to Contribute to the Implementation of Health Data Integration Platforms: Retrospective of the medEmotion Project
No full textHealth data integration platforms are vital to drive collaborative, interdisciplinary medical research projects. Developing such a platform requires input from different stakeholders. Managing these stakeholders and steering platform development is challenging, and misaligning the platform to the partners' strategies might lead to a low acceptance of the final platform. We present the medEmotion project, a collaborative effort among 7 partners from health care, academia, and industry to develop a health data integration platform for the region of Limburg in Belgium. We focus on the development process and stakeholder engagement, aiming to give practical advice for similar future efforts based on our reflections on medEmotion. We introduce Personas to paraphrase different roles that stakeholders take and Demonstrators that summarize personas' requirements with respect to the platform. Both the personas and the demonstrators serve 2 purposes. First, they are used to define technical requirements for the medEmotion platform. Second, they represent a communication vehicle that simplifies discussions among all stakeholders. Based on the personas and demonstrators, we present the medEmotion platform based on components from the Microsoft Azure cloud. The demonstrators are based on real-world use cases and showcase the utility of the platform. We reflect on the development process of medEmotion and distill takeaway messages that will be helpful for future projects. Investing in community building, stakeholder engagement, and education is vital to building an ecosystem for a health data integration platform. Instead of academic-led projects, the health care providers themselves ideally drive collaboration among health care providers. The providers are best positioned to address hospital-specific requirements, while academics take a neutral mediator role. This also includes the ideation phase, where it is vital to ensure the involvement of all stakeholders. Finally, balancing innovation with implementation is key to developing an innovative yet sustainable health data integration platform.We thank our 3 partner hospitals Jessa Ziekenhuis, Noorderhart, and Ziekenhuis Oost-Limburg for their contributions toward the medEmotion project. Further, we thank the Limburg Clinical Research Center for sharing their expertise in clinical research projects. The software development of the medEmotion platform was funded by LRM, with the support of the European Regional Development Fund (EFRO-1308). This research received funding from the Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” program
An alternative strategy for COVID-pneumonitis: a retrospective analysis from a tertiary center in Belgium
No full textAt the start of the COVID-19 pandemic in Europe no clear guidelines on its treatment were available. While early intubation and the avoidance of steroids was proposed, an alternative strategy of noninvasive ventilation and steroid use in case of refractory hypoxemia after one week was implemented to decrease the burden on resources. This single center retrospective analysis assessed the feasibility and safety of such a strategy. All patients admitted to the ICU with a confirmed COVID-19 pneumonitis from March to June 2020 were included in the analysis. Multivariable logistic regression was done to assess (1) the feasibility of ICU mortality prediction by the Charlson Comorbidity Index and the Clinical Frailty Score (2) the impact of invasive mechanical ventilation and steroid administration in ICU mortality. 97 patients were admitted to the ICU. Mean APACHEIII was 67 (16), with a predicted ICU mortality of 30%. Median P/F ratio was 91 (IQR 67-118) on admission. Only 37 (40%) patients were intubated and mechanically ventilated within their ICU stay. The ICU mortality rate was 20.6% (n=20). The multivariable logistic regression model for ICU mortality, using gender, Charlson Comorbidity Index and Clinical Frailty Score had an AUROC of 0.81, with an R-2 of 0.23. Thirty eight patients (39%) of 97 patients received steroids. Adding steroid administration to the multivariable model did not yield the latter as an independent factor of ICU-mortality (p=0.06). However, mechanical ventilation remained an independent risk factor for ICU-mortality (p=0.004) with an odds ratio of 9.9 (95%CI 1.8-53.6), after adjustment for baseline risk factors Charlson Comorbidity Index, Clinical Frailty Score and APACHE-III score. This single center retrospective analysis demonstrated a safe alternative strategy using a non-invasive ventilation strategy and late administration of steroids. These findings need to be confirmed in multi-center prospective randomised controlled trials
An alternative strategy for COVID-pneumonitis: a retrospective analysis from a tertiary center in Belgium
No full textAt the start of the COVID-19 pandemic in Europe no clear guidelines on its treatment were available. While early intubation and the avoidance of steroids was proposed, an alternative strategy of noninvasive ventilation and steroid use in case of refractory hypoxemia after one week was implemented to decrease the burden on resources. This single center retrospective analysis assessed the feasibility and safety of such a strategy. All patients admitted to the ICU with a confirmed COVID-19 pneumonitis from March to June 2020 were included in the analysis. Multivariable logistic regression was done to assess (1) the feasibility of ICU mortality prediction by the Charlson Comorbidity Index and the Clinical Frailty Score (2) the impact of invasive mechanical ventilation and steroid administration in ICU mortality. 97 patients were admitted to the ICU. Mean APACHEIII was 67 (16), with a predicted ICU mortality of 30%. Median P/F ratio was 91 (IQR 67-118) on admission. Only 37 (40%) patients were intubated and mechanically ventilated within their ICU stay. The ICU mortality rate was 20.6% (n=20). The multivariable logistic regression model for ICU mortality, using gender, Charlson Comorbidity Index and Clinical Frailty Score had an AUROC of 0.81, with an R-2 of 0.23. Thirty eight patients (39%) of 97 patients received steroids. Adding steroid administration to the multivariable model did not yield the latter as an independent factor of ICU-mortality (p=0.06). However, mechanical ventilation remained an independent risk factor for ICU-mortality (p=0.004) with an odds ratio of 9.9 (95%CI 1.8-53.6), after adjustment for baseline risk factors Charlson Comorbidity Index, Clinical Frailty Score and APACHE-III score. This single center retrospective analysis demonstrated a safe alternative strategy using a non-invasive ventilation strategy and late administration of steroids. These findings need to be confirmed in multi-center prospective randomised controlled trials
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
Variations on the Author
Full text link“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
Full text linkWe 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
Detecting Paroxysmal Atrial Fibrillation From an Electrocardiogram in Sinus Rhythm
No full textBACKGROUND Atrial fibrillation (AF) may occur asymptomatically and can be diagnosed only with electrocardiography (ECG) while the arrhythmia is present.OBJECTIVES The aim of this study was to independently validate the approach of using artificial intelligence (AI) to identify underlying paroxysmal AF from a 12-lead ECG in sinus rhythm (SR).METHODS An AI algorithm was trained to identify patients with underlying paroxysmal AF, using electrocardiographic data from all in-and outpatients from a single center with at least 1 ECG in SR. For patients without AF, all ECGs in SR were included. For patients with AF, all ECGs in SR starting 31 days before the first AF event were included. The patients were randomly allocated to training, internal validation, and testing datasets in a 7:1:2 ratio. In a secondary analysis, the AF prevalence of the testing group was modified. Additionally, the performance of the algorithm was validated at an external hospital.RESULTS The dataset consisted of 494,042 ECGs in SR from 142,310 patients. Testing the model on the first ECG of each patient (AF prevalence 9.0%) resulted in accuracy of 78.1% (95% CI: 77.6%-78.5%), area under the receiver operating characteristic curve of 0.87 (95% CI: 0.86-0.87), and area under the precision recall curve (AUPRC) of 0.48 (95% CI: 0.46-0.50). In a low-risk group (AF prevalence 3%), the AUPRC decreased to 0.21 (95% CI: 0.18-0.24). In a high-risk group (AF prevalence 30%), the AUPRC increased to 0.76 (95% CI: 0.75-0.78). This performance was robust when validated in an external hospital.CONCLUSIONS The approach of using an AI-enabled electrocardiographic algorithm for the identification of patients with underlying paroxysmal AF from ECGs in SR was independently validated. (J Am Coll Cardiol EP 2023;9:1771-1782)& COPY; 2023 by the American College of Cardiology Foundation.Dr Gruwez is supported as predoctoral strategic basic research fellow by the Fund for Scientific Research Flanders (FWO 1S83221N). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
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