1,720,996 research outputs found
Long-term prognostic potential of microRNA-150-5p in optimally treated heart failure patients with reduced ejection fraction: a pilot study
No full textBACKGROUND: In a previous study, we found that miR-150-5p was specifically downregulated in patients with advanced heart failure (HF). Here, we investigated the long-term prognostic potential of miR-150-5p. METHODS: We studied optimally-treated HF outpatients with reduced ejection fraction. The primary outcome comprised the composite of death, urgent heart transplantation (HT) and ventricular assist device (VAD) implantation within 30 months. We used recursive partitioning analysis to identify the optimal log miR-150-5p cut-off. The association of log miR-150-5p with the primary outcome was examined using Cox regression analysis. We used the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score for adjustment in multivariable analysis. Finally, we compared the global fit of three models (MAGGIC score + miR-150-5p, MAGGIC score + NT-proBNP, and NT-proBNP + miR-1505p) using Akaike Information Criterion. RESULTS: Recursive partitioning analysis identified the value of -2.22 as the optimal cut-off for log miR-150-5p. Thirtymonth survival free of urgent HT/VAD implantation was 31% among the patients with log miR-150-5p<-2.22 and 86% among those with log miR-150-5p>-2.22. Crude hazard ratio (HR) of the primary outcome for log miR-150-5p expression level <-2.22 was 6.70 (95% CI: 2.31-19.38; P<0.001). After adjusting for the MAGGIC score in multivariable analysis, the HR was 4.40 (95% CI: 1.52-12.77; P=0.006). Adding log miR-150-5p to the MAGGIC score led to an increase of 0.047 in C-index. The model combining miR-150-5p and MAGGIC score had a 73% likelihood of representing the best-fit model of those evaluated. CONCLUSIONS: Our data generate the hypothesis that miR-150-5p may represent a novel risk marker in HF with reduced ejection fraction
The new frontiers of rehabilitation medicine in people with chronic disabling illnesses
No full textBecause of the demographic shift and the increased proportion of patients surviving acute critical illnesses, the number of people living with severely disabling chronic diseases and, consequently, the demand for rehabilitation are expected to increase sharply over time. As underscored by the World Health Organization, there is substantial evidence that the provision of inpatient rehabilitation in specialized rehabilitation units to people with complex needs is effective in fostering functional recovery, improving health-related quality of life, increasing independence, reducing institutionalization rate, and improving prognosis. Recent studies in the real world setting reinforce the evidence that patients with ischemic heart disease or stroke benefit from rehabilitation in terms of improved prognosis. In addition, there is evidence of the effectiveness of rehabilitation for the prevention of functional deterioration in patients with complex and/or severe chronic diseases. Given this evidence of effectiveness, rehabilitation should be regarded as an essential part of the continuum of care. Nonetheless, rehabilitation still is underdeveloped and underused. Efforts should be devoted to foster healthcare professional awareness of the benefits of rehabilitation and to increase referral and participation
Circulating microRNA-150-5p as a novel biomarker for advanced heart failure: A genome-wide prospective study
No full textBackground: Circulating microRNAs (miRs) are promising biomarkers for heart failure (HF). Previous studies have provided inconsistent miR "signatures." The phenotypic and pathophysiologic heterogeneity of HF may have contributed to this inconsistency. In this study we assessed whether advanced HF (AHF) patients present a distinct miR signature compared with healthy subjects (HS) and mild to moderate HF (MHF) patients. Methods: The study consisted of 2 phases: a screening phase and a validation phase. In the screening phase, 752 miRs were profiled in HS and MHF and AHF patients (N = 15), using the real-time quantitative polymerase chain reaction (RT-qPCR) technique and global mean normalization. In the validation phase, the miRs found to be significantly dysregulated in AHF patients compared with both HS and MHF patients were validated in 15 HS, 25 patients with MHF and 29 with AHF, using RT-qPCR, and normalizing to exogenous (cel-miR-39) and endogenous controls. Results: In the screening phase, 5 miRs were found to be significantly dysregulated: -26a-5p; -145-3p; -150-5p; -485-3p; and -487b-3p. In the validation phase, miR-150-5p was confirmed to be significantly downregulated in AHF patients when compared with both HS and MHF patients, irrespective of the normalization method used. miR-26a-5p was confirmed to be significantly dysregulated only when normalized to cell-miR-39. Dysregulation of the other miRs could not be confirmed. miR-150-5p was significantly associated with maladaptive remodeling, disease severity and outcome. Conclusions: Our data suggest miR-150-5p as a novel circulating biomarker for AHF. The association of miR-150-5p with maladaptive remodeling, disease severity and outcome supports the pathophysiologic relevance of downregulated miR-150-5p expression to AHF
Dataset related to article: "Machine learning to predict mortality after rehabilitation among patients with severe stroke"
No full textWe provide the raw data used for the following article:
Scrutinio D, Ricciardi C, Donisi L, Losavio E, Battista P, Guida P, Cesarelli M, Pagano G, D'Addio G.
Machine learning to predict mortality after rehabilitation among patients with severe stroke. "Sci Rep." 2020 Nov 18;10(1):20127.
doi: 10.1038/s41598-020-77243-3. PMID: 33208913; PMCID: PMC7674405.
Abstract: Stroke is among the leading causes of death and disability worldwide. Approximately 20–25% of stroke survivors present severe disability, which is associated with increased mortality risk. Prognostication is inherent in the process of clinical decision-making. Machine learning (ML) methods have gained increasing popularity in the setting of biomedical research. The aim of this study was twofold: assessing the performance of ML tree-based algorithms for predicting three-year mortality model in 1207 stroke patients with severe disability who completed rehabilitation and comparing the performance of ML algorithms to that of a standard logistic regression. The logistic regression model achieved an area under the Receiver Operating Characteristics curve (AUC) of 0.745 and was well calibrated. At the optimal risk threshold, the model had an accuracy of 75.7%, a positive predictive value (PPV) of 33.9%, and a negative predictive value (NPV) of 91.0%. The ML algorithm outperformed the logistic regression model through the implementation of synthetic minority oversampling technique and the Random Forests, achieving an AUC of 0.928 and an accuracy of 86.3%. The PPV was 84.6% and the NPV 87.5%. This study introduced a step forward in the creation of standardisable tools for predicting health outcomes in individuals affected by stroke
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
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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