1,721,114 research outputs found
Reply-Letter to the Editor – Methodological issues on prediction of early- and long-term mortality in adult patients acutely admitted to internal medicine
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Multi-state models for hospitalizations of heart failure patients in Trieste
No full textIn Italy, heart failure (HF) is the most common clinical diagnosis among
people over 65 and about 80,000 new cases per year are recorded [1]. This is a
chronic condition whose incidence is strictly connected with age.
A very flexible tool for modelling the chronic nature of this disease is multi-state
model. Multi-state models are based on continuous time stochastic process, that can
have Markov or semi-Markov property. In this presentation we show a multi-state
model in which the states are the admission from and discharge to the first five hospitalizations,
and death, an absorbing state. This representation aims at describing
the main characteristics of heart failure patients’ hospitalization progression considering
various covariates recorded
An ICA approach to detect functionally different intra-regional neuronal signals in MEG data
No full textOptimization of an Independent Component Analysis approach for artifact identification and removal in MEG signals
No full textCompeting risks between mortality and heart failure hospital re-admissions: a community-based investigation from the Trieste area
No full textPredictors of mortality and readmission among patients hospitalized for heart failure (HF) were investigated in a large, unselected population of the Trieste area. The cohort of 4666 patients survived at the index admission in the period 2009-2014 was followed after discharge. Incidence of mortality and re-HF admission within 30 days and one year were computed, by comparing cumulative incidence probabilities with cause-specific Kaplan-Meier curves. Competing risks regression was used to find factors associated respectively with re-HF admission and death. Two distinct risk profiles were obtained, particularly for early outcomes, useful for better targeting treatment of these high-risk patients
Functional Source Separation and hand cortical representation for a brain-computer interface feature extraction
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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
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