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- Ruilope, LM, et al.
(författare)
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Design and Baseline Characteristics of the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease Trial
- 2019
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Ingår i: American journal of nephrology. - : S. Karger AG. - 1421-9670 .- 0250-8095. ; 50:5, s. 345-356
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Tidskriftsartikel (refereegranskat)abstract
- <b><i>Background:</i></b> Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. <b><i>Patients and</i></b> <b><i>Methods:</i></b> The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate ≥25 mL/min/1.73 m<sup>2</sup> and albuminuria (urinary albumin-to-creatinine ratio ≥30 to ≤5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level α = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. <b><i>Conclusions:</i></b> FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049.
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- Sugita, S., et al.
(författare)
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The geomorphology, color, and thermal properties of Ryugu: Implications for parent-body processes
- 2019
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Ingår i: Science. - : AAAS. - 0036-8075 .- 1095-9203. ; 364:6437
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Tidskriftsartikel (refereegranskat)abstract
- Asteroids fall to Earth in the form of meteorites, but these provide little information about their origins. The Japanese mission Hayabusa2 is designed to collect samples directly from the surface of an asteroid and return them to Earth for laboratory analysis. Three papers in this issue describe the Hayabusa2 team's study of the near-Earth carbonaceous asteroid 162173 Ryugu, at which the spacecraft arrived in June 2018 (see the Perspective by Wurm). Watanabeet al.measured the asteroid's mass, shape, and density, showing that it is a “rubble pile” of loose rocks, formed into a spinning-top shape during a prior period of rapid spin. They also identified suitable landing sites for sample collection. Kitazatoet al.used near-infrared spectroscopy to find ubiquitous hydrated minerals on the surface and compared Ryugu with known types of carbonaceous meteorite. Sugitaet al.describe Ryugu's geological features and surface colors and combined results from all three papers to constrain the asteroid's formation process. Ryugu probably formed by reaccumulation of rubble ejected by impact from a larger asteroid. These results provide necessary context to understand the samples collected by Hayabusa2, which are expected to arrive on Earth in December 2020.Science, this issue p.268, p.272, p.eaaw0422; see also p.230
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- Le, H. H., et al.
(författare)
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Fast Generation of Clinical Pathways including Time Intervals in Sequential Pattern Mining on Electronic Medical Record Systems
- 2018
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Ingår i: Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1726-1731
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Konferensbidrag (refereegranskat)abstract
- Machine-based generation of clinical pathways that utilizes sequential pattern mining to extract the pathways from historical electronic medical record (EMR) systems has gained much attention. We previously proposed a method to generate clinical pathways including time intervals that provides rich information to medical workers. However, this method is difficult to use in real applications because of slow clinical pathway generation as a large number of duplicate patterns are included. In this paper, to speed up the clinical pathway generation, we deploy an occurrence check that adds only closed sequential patterns to the results during mining while considering time intervals between events. Experiments on real data sets showed that our proposal can be more than 13 times faster than our earlier method and can significantly improve the decision-making process for medical actions at large hospitals.
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