1,721,029 research outputs found
Uncommon cause of ST-segment elevation in V1-V3: incremental value of cardiac magnetic resonance imaging
No full textAlthough ST-segment elevation in precordial leads is a
characteristic of anterior left ventricular infarction (LVI), it
may also be observed in patients with proximal right coronary
occlusion. An isolated right ventricular infarction
(RVI) accounts for only 3 % of all myocardial infarctions
(MI) [1]; in these cases, the ST-segment elevation in the
precordial leads V1–V3 also may occur in the absence of
inferior electrocardiographic changes [2], whereas the
combination of RVI with inferior LVI suppresses ST-segment
elevation in the precordial leads and yields an STsegment
elevation in leads DII, DIII, and aVF [3].
Although certain electrocardiographic features have been
suggested to help differentiate ST-segment elevation secondary
to isolated RVI from LVI [3], it may be impossible
to make a differential diagnosis on the basis of electrocardiography
alone because these features are not pathognomonic.
Furthermore, when a patient is admitted for
typical chest pain, slight ST-segment elevation in leads
V1–V3 and significant increase of cardiac troponin but
with normal coronary main vessels at the coronary angiography,
the diagnosis of a RVI is challenging; taking into
account the multiple causes of myocardial injury and
treatment consequences, there is great clinical need to
clarify the underlying reason for cardiac troponin release.
Although some studies report that echocardiography is a
valuable clinical tool for the evaluation of global RV
function [4], geometric assumptions in modeling the
complex RV shape restricts the ability of this technique in
accurate and precise quantification of RV function; furthermore,
RV function assessment can be difficult in
patients with poor acoustic window or when minor alterations
of RV function are present.
Cardiac magnetic resonance (CMR) provides a comprehensive,
multifaceted view of the heart and can be
useful to characterize an infarct site and size accurately [5].
CMR in this particular setting can confirm the presence of
a minor RVI and aid to exclude other potential causes of
troponin rise with normal coronary main vessels at the coronary
angiography, such as embolic myocardial infarction or
myocarditis [6]. Acute MI treatment [7–10] and traditional
predictors of long-term mortality after acute MI are well
characterized [11–14] but with introduction of CMR, new
predictors of cardiovascular events are emerging [15, 16] and
the evaluation of RV function using CMR can improve risk
stratification and potentially refine patient management after
MI [17]. Moreover, the extent of myocardial scar characterized
by CMR is significantly associated with the occurrence
of spontaneous ventricular arrhythmias [18].
There have been few reports of anterior ST-segment
elevation caused by isolated RVI due to right ventricle
branch occlusion [19–21]. Occlusion of the conus branch
has been described essentially as a complication of coronary
angioplasty or during cardiac surgery [19–21]. Only
one report described a spontaneous RVI with culprit lesion
in the conus branch [22]. Assessment of isolated RVI due
to a critical stenosis of the conus branch by magnetic resonance
is never been reported
Calcific degeneration and rupture of the aortic valve and ascending aorta: From cardiac auscultation to multimodality imaging
No full textn/
Unsupervised phenotypic clustering of cardiac MRI data reveals distinct subgroups associated with outcomes in ischemic cardiomyopathy
No full textIschemic cardiomyopathy (ICM) shows significant heterogeneity in clinical outcomes, challenging traditional risk stratification methods. Cardiac magnetic resonance (CMR) imaging offers detailed insights into myocardial structure and function, yet integrating this multidimensional data remains complex. Aim of the current study was to assess whether unsupervised machine learning could help identify distinct phenotypic subgroups and enhance prognostic accuracy. This study included 319 clinically stable ICM patients. CMR-derived variables, including left ventricular ejection fraction (LVEF), ventricular volumes, and myocardial scar burden, were analysed using KAMILA clustering algorithm. The optimal number of clusters was determined through silhouette analysis, within-cluster sum of squares, and gap statistics. Principal Component Analysis (PCA) visualized the clustering results, and prognostic value was assessed using Cox regression and Kaplan-Meier survival analysis. SHAP (SHapley Additive exPlanations) values were used to evaluate feature importance. Two distinct phenotypic clusters were identified. Cluster 1 (n = 219) demonstrated better cardiac function, with higher LVEF, smaller ventricular volumes, and lower scar burden. Cluster 2 (n = 100) indicated advanced disease, with lower LVEF, larger volumes, higher scar burden, and greater midwall fibrosis. PCA confirmed clear separation between clusters, explaining 62.6% of the variance. After a median follow-up of 13 months, the composite endpoint was observed in 37 (12%) patients. Patients in Cluster 2 had a significantly higher risk of experiencing the composite outcome (HR = 3.96, p < 0.001). SHAP analysis identified ischaemic scar burden, sphericity index, and midwall fibrosis as key predictors of outcomes. Unsupervised clustering of CMR-derived variables identified distinct ICM phenotypes with important prognostic implications. This method improves risk stratification and could help tailor personalised treatment plans, highlighting the potential of machine learning in understanding ICM heterogeneity
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
Longitudinal Effects of Lipid-Lowering Treatment on High-Risk Plaque Features and Pericoronary Adipose Tissue Attenuation Using Serial Coronary Computed Tomography
No full textAim: To evaluate the impact of different lipid-lowering treatment intensities on high-risk plaque features and pericoronary adipose tissue (PCAT) attenuation in patients undergoing serial coronary computed tomography angiography (CCTA). Methods: Individuals with suspected or known coronary artery disease (CAD) from 11 imaging centers who underwent serial CCTA examinations were retrospectively analyzed. Plaque volumes and PCAT were quantified, and the presence of high-risk plaque features was semi-quantitatively assessed using the plaque feature score (PFS). Results: In total, 216 consecutive patients (mean age 63.1 ± 9.7 years, 26.4% female) were included. The mean observation and treatment timespan between the CCTA scans was 824.5 (interquartile range (IQR) = 463.0–1323.0) days (27.5 months). The regression of high-risk features was more common with high-intensity versus low or no lipid-lowering treatment (HR = 4.6, 95%CI = 1.8–12.0, p < 0.001) and was associated with the attenuated increase in non-calcified plaque volume (p < 0.001). PCATmean decreased with increasing intensity of lipid-lowering treatment (p = 0.01) but no associations were observed between the changes in PCAT and PFS or plaque volumes. Lipid-lowering drug intensity was predictive of PFS regression (p < 0.001), whereas baseline PCATRCA was predictive for PFS progression (p = 0.03), both independent of age, cardiovascular risk factors, and baseline plaque volumes. Conclusions: PCAT predicts the progression of high-risk coronary plaque features. High-intensity lipid-lowering drugs may cause the regression of high-risk plaque features through a plaque ‘delipidization’ process. Future trials are now warranted, studying if this process is potentially associated with improved clinical outcomes
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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