von Hans-Josef Feistritzer ; Alexander Jobs ; Uwe Zeymer ; Steffen Schneider ; Philipp Lauten ; Miroslaw Ferenc ; Maren Weferling ; Regine Brinkmann ; Sebastian Winkler ; Ulf Landmesser ; Tobias Daniel Trippel ; Christoph Stellbrink ; Harm Wienbergen ; Georg Fürnau ; Helge Möllmann ; Axel Linke ; Christian Jung ; Alexander Lauten ; Stephan Achenbach ; Tienush Rassaf ; Thomas Schmitz ; Sebastian Cremer ; Christoph Olivier ; Volker Schächinger ; Samuel Tobias Sossalla ; Karl Toischer ; Christian Templin ; Daniel Sedding ; Peter Clemmensen ; Eike Philipp Tigges ; Felix Meincke ; Haitham Abu Sharar ; Saarraaken Kulenthiran ; Paul Christian Schulze ; Claudius Jacobshagen ; Derk Frank ; Stephan Baldus ; Ralf Lehmann ; Christian Spies ; Norbert Klein ; Ingo Eitel ; Ralf Zahn ; Alexander Schmeisser ; Tommaso Gori ; Philipp Lurz ; Ibrahim Akın ; Georgios Chatzis ; Konstantinos Rizas ; Thorsten Keßler ; Fadil Ademaj ; Albrecht Elsässer ; Lars Siegfried Maier ; Alper Öner ; Alexander Staudt ; Nikos Werner ; Tobias Geisler ; Mirjam Keßler ; Markus Ferrari ; Melchior Seyfarth ; Peter Johann Nordbeck ; Sebastian Ewen ; Christian Bietau ; Arash Haghikia ; Sebastian J. Reinstadler ; Alexander Geppert ; Nadine Hösler ; Gabor Toth-Gayor ; Björn Ulrich Nicolas Billmann ; Ramon Tschierschke ; Christian Schmidt ; Stephan Fichtlscherer ; Holger Thiele
Online verfügbar: 8. April 2025, Artikelversion: 1. Mai 2025 ; Gesehen am 19.08.2025
Background - Multivessel coronary artery disease (CAD) is present in 30% to 70% of patients presenting with non-ST-segment elevation myocardial infarction (NSTEMI) depending on varying age and risk profiles. In contrast to the STEMI cohort, there is only limited scientific evidence derived from randomized controlled trials directing the general decision for or against complete revascularization in the NSTEMI population. - Primary hypothesis - The COMPLETE-NSTEMI trial aims to investigate whether multivessel percutaneous coronary intervention (PCI) is superior over culprit-lesion only PCI in patients with NSTEMI and multivessel CAD. - Design - COMPLETE-NSTEMI is a prospective, randomized, controlled, multicenter, parallel group, open-label trial. It will enroll 3390 NSTEMI patients with multivessel CAD at 65 to 70 sites in Germany and Austria. Patients will be randomized 1:1 to either complete revascularization with PCI or culprit lesion-only PCI. - Endpoints - The primary efficacy endpoint is a composite of cardiovascular death or rehospitalization for nonfatal myocardial infarction during follow-up. The trial is event-driven and will be stopped as soon as 578 primary endpoint events and a minimal follow-up duration of 12 months for each patient are reached. - Current status - The first patient was enrolled at October 27, 2023. By April 2025, 51 sites have been activated and >500 patients have been randomized. Completion of recruitment is expected for the first half of 2027. The final results of the primary endpoint are expected in 2028. - Outlook - COMPLETE NSTEMI will be the first dedicated trial to answer the question about the optimal revascularization strategy in patients with NSTEMI and multivessel CAD. - Trial registration: ClinicalTrials.gov - NCT05786131
American heart journal Amsterdam [u.a.] : Elsevier, 1925 287(2025), Seite 94-106 Online-Ressource
Diese Arbeit beschreibt eine Methodik für die Erstellung von Modellen der Leistungsaufnahme von eingebetteten Speichern. Speichern kommt unter den Strukturblöcken eine besondere Bedeutung zu, da sie in 10 Jahren voraussichtlich über 90% der Fläche neuentwickelter Schaltungen einnehmen werden. Neben den Anforderungen an die Modelle, wie Genauigkeit, Geschwindigkeit und mathematischer Geschlossenheit berücksichtigt der vorgestellte Ansatz insbesondere Anforderungen an den Modellierungsprozess selbst. Dies sind hauptsächlich der Schutz intellektuellen Eigentums, sowie die Gewährleistung niedriger Modellierungskosten. Als Kernpunkt der Methodik wird ein Verfahren zur Generierung nichtlinearer (signomialer) Modelle aus empirischen Daten vorgestellt. Das regressionsbasierte Verfahren erlaubt die Erzeugung stückweiser Modellfunktionen, welche über geometrische Programme optimierbar sind. Die vorgestellten Modelle reduzieren den Vorhersagefehler um bis zu 95% verglichen mit bisherigen Ansätzen. <dt.>
This thesis describes a methodology for the generation of models of the power consumption of embedded memories. Memories have a special importance among the system blocks as it is forecast that more than 90% of the area of newly developed systems will be occupied by memory within ten years. In addition to the requirements on models, like accuracy, speed and mathematically closed form the presented approach specifically adresses the requirements on the modeling procedure. These are mainly the protection of intellectual property and low modeling costs. As a key point of the approach a method for the generation of nonlinear (signomial) models from empirical data is presented. This regression based method allows the generation of piecewise model functions, which can be used for optimisation through geometric programs. The presented models reduce the prediction error by up to 95% compared to existing approaches. <engl.>
