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- Cornel, Jan H., et al.
(författare)
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Anticoagulant therapy and outcomes in patients with prior or acute heart failure and acute coronary syndromes : Insights from the APixaban for PRevention of Acute ISchemic Events 2 trial
- 2015
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Ingår i: American Heart Journal. - : Elsevier BV. - 0002-8703 .- 1097-6744. ; 169:4, s. 531-538
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Tidskriftsartikel (refereegranskat)abstract
- Background Clinical outcomes and the effects of oral anticoagulants among patients with acute coronary syndrome (ACS) and either a history of or acute heart failure (HF) are largely unknown. We aimed to assess the relationship between prior HF or acute HF complicating an index ACS event and subsequent clinical outcomes and the efficacy and safety of apixaban compared with placebo in these populations. Methods High-risk patients were randomly assigned post-ACS to apixaban 5.0 mg or placebo twice daily. Median follow-up was 8 (4-12) months. The primary outcome was cardiovascular death, myocardial infarction, or stroke. The main safety outcome was thrombolysis in myocardial infarction major bleeding. Results Heart failure was reported in 2,995 patients (41%), either as prior HF (2,076 [28%]) or acute HF (2,028 [27%]). Patients with HF had a very high baseline risk and were more often managed medically. Heart failure was associated with a higher rate of the primary outcome (prior HF: adjusted hazard ratio [HR] 1.73, 95% CI 1.42-2.10, P < .0001, acute HF: adjusted HR 1.65, 95% CI 1.35-2.01, P < .0001) and cardiovascular death (prior HF: HR 2.54, 95% CI 1.82-3.54, acute HF: adjusted HR 2.52, 95% CI 1.82-3.50). Patients with acute HF also had significantly higher rates of thrombolysis in myocardial infarction major bleeding (prior HF: adjusted HR 1.22, 95% CI 0.65-2.27, P = .54, acute HF: adjusted HR 1.78, 95% CI 1.03-3.08, P = .04). There was no statistical evidence of a differential effect of apixaban on clinical events or bleeding in patients with or without prior HF; however, among patients with acute HF, there were numerically fewer events with apixaban than placebo (14.8 vs 19.3, HR 0.76, 95% CI 0.57-1.01, interaction P = .13), a trend that was not seen in patients with prior HF or no HF. Conclusions In high-risk patients post-ACS, both prior and acute HFs are associated with an increased risk of subsequent clinical events. Apixaban did not significantly reduce clinical events and increased bleeding in patients with and without HF; however, there was a tendency toward fewer clinical events with apixaban in patients with acute HF.
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| 3. |
- Martínez-Gómez, Jesus, et al.
(författare)
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Where Are We After Five Editions? : Robot Vision Challenge, a Competition that Evaluates Solutions for the Visual Place Classification Problem
- 2015
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Ingår i: IEEE robotics & automation magazine. - : IEEE. - 1070-9932 .- 1558-223X. ; 22:4, s. 147-156
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Tidskriftsartikel (refereegranskat)abstract
- This article describes the Robot Vision challenge, a competition that evaluates solutions for the visual place classification problem. Since its origin, this challenge has been proposed as a common benchmark where worldwide proposals are measured using a common overall score. Each new edition of the competition introduced novelties, both for the type of input data and sub-objectives of the challenge. All the techniques used by the participants have been gathered up and published to make it accessible for future developments. The legacy of the Robot Vision challenge includes data sets, benchmarking techniques, and a wide experience in the place classification research that is reflected in this article.
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| 4. |
- Viejo, Diego, et al.
(författare)
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Using GNG to improve 3D features extractio - Application to 6DoF Egomotion
- 2012
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Ingår i: Neural Networks. - : Elsevier BV. - 1879-2782 .- 0893-6080. ; 32, s. 138-146
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Tidskriftsartikel (refereegranskat)abstract
- Abstract in UndeterminedSeveral recent works deal with 3D data in mobile robotic problems, e.g. mapping or egomotion. Data comes from any kind of sensor such as stereo vision systems, time of flight cameras or 3D lasers, providing a huge amount of unorganized 3D data. In this paper, we describe an efficient method to build complete 3D models from a Growing Neural Gas (GNG). The GNG is applied to the 3D raw data and it reduces both the subjacent error and the number of points, keeping the topology of the 3D data. The GNG output is then used in a 3D feature extraction method. We have performed a deep study in which we quantitatively show that the use of GNG improves the 3D feature extraction method. We also show that our method can be applied to any kind of 3D data. The 3D features obtained are used as input in an Iterative Closest Point (ICP)-like method to compute the 6DoF movement performed by a mobile robot. A comparison with standard ICP is performed, showing that the use of GNG improves the results. Final results of 3D mapping from the egomotion calculated are also shown. (C) 2012 Elsevier Ltd. All rights reserved.
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