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Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV using the STAR Time Projection Chamber at the Relativistic Heavy Ion Collider. The elliptic flow signal, v2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
Begriffe sind häufig nicht eindeutig. Eine „Bank“ kann ein Finanzinstitut oder eine Sitzgelegenheit sein und die Stadt Frankfurt existiert mehr als einmal. Dennoch können sie in vielen Fällen problemlos von Menschen unterschieden werden. Computer sind noch nicht in der Lage, diese Leistung mit vergleichbarer Genauigkeit zu erfüllen.
Der in dieser Arbeit vorgestellte Ansatz baut auf dem für das Deutsche bereits gute Ergebnisse erzielenden fastSense auf und verwendet ein neuronales Netz, um Namen und Begriffe in englischen Texten mit Hilfe der Wikipedia zu disambiguieren. Dabei konnte eine Genauigkeit von bis zu 89,5% auf Testdaten erreicht werden.
Mit dem entwickelten Python-Modul kann das trainierte Modell in bestehende Anwendungen eingebunden werden. Die im Modul enthaltenen Programme ermöglichen es, neue Modelle zu trainieren und zu testen.
Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt(s_NN)=130 GeV using the STAR TPC at RHIC. The elliptic flow signal, v_2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
Background & Aims: In ACLF patients, an adequate risk stratification is essential, especially for liver transplant allocation, since ACLF is associated with high short-term mortality. The CLIF-C ACLF score is the best prognostic model to predict outcome in ACLF patients. While lung failure is generally regarded as signum malum in ICU care, this study aims to evaluate and quantify the role of pulmonary impairment on outcome in ACLF patients.
Methods: In this retrospective study, 498 patients with liver cirrhosis and admission to IMC/ICU were included. ACLF was defined according to EASL-CLIF criteria. Pulmonary impairment was classified into three groups: unimpaired ventilation, need for mechanical ventilation and defined pulmonary failure. These factors were analysed in different cohorts, including a propensity score-matched ACLF cohort.
Results: Mechanical ventilation and pulmonary failure were identified as independent risk factors for increased short-term mortality. In matched ACLF patients, the presence of pulmonary failure showed the highest 28-day mortality (83.7%), whereas mortality rates in ACLF with mechanical ventilation (67.3%) and ACLF without pulmonary impairment (38.8%) were considerably lower (p < .001). Especially in patients with pulmonary impairment, the CLIF-C ACLF score showed poor predictive accuracy. Adjusting the CLIF-C ACLF score for the grade of pulmonary impairment improved the prediction significantly.
Conclusions: This study highlights that not only pulmonary failure but also mechanical ventilation is associated with worse prognosis in ACLF patients. The grade of pulmonary impairment should be considered in the risk assessment in ACLF patients. The new score may be useful in the selection of patients for liver transplantation.