Financial crises and the attainment of the SDGs: an adjusted multidimensional poverty approach

This paper analyses the impact of financial crises on the Sustainable Development Goal of eradicating poverty. To do so, we develop an adjusted Multidimensional Poverty Framework (MPF) that includes 15 indicators that span across key poverty aspects related to income, basic needs, health, education and the environment. We then use an econometric model that allows us to examine the impact of financial crises on these indicators in 150 countries over the period 1980–2015. Our analysis produces new estimates on the impact of financial crises on poverty’s multiple social, economic and environmental aspects and equally important captures dynamic linkages between these aspects. Thus, we offer a better understanding of the potential impact of current debt dynamics on Multidimensional Poverty and demonstrate the need to move beyond the boundaries of SDG1, if we are to meet the target of eradicating poverty. Our results indicate that the current financial distress experienced by many low-income countries may reverse the progress that has been made hitherto in reducing poverty. We find that financial crises are associated with an approximately 10% increase of extreme poor in low-income countries. The impact is even stronger in some other poverty aspects. For instance, crises are associated with an average decrease of government spending in education by 17.72% in low-income countries. The dynamic linkages between most of the Multidimensional Poverty indicators, warn of a negative domino effect on a number of SDGs related to poverty, if there is a financial crisis shock. To pre-empt such a domino effect, the specific SDG target 17.4 on attaining long-term debt sustainability through coordinated policies plays a key role and requires urgent attention by the international community

Self-Management for Men With Lower Urinary Tract Symptoms: A Systematic Review and Meta-Analysis

Three-dimensional (3D)-imaging provides important information on cardiac anatomy during electrophysiological procedures. Real-time updates of modalities with high soft-tissue contrast are particularly advantageous during cardiac procedures. Therefore, a beat to beat 3D visualization of cardiac anatomy by intracardiac echocardiography (ICE) was developed and tested in phantoms and animals. An electronic phased-array 5-10 MHz ICE-catheter (Acuson, AcuNav (TM)/Siemens Medical Solutions USA/64 elements) providing a 90A degrees sector image was used for ICE-imaging. A custom-made mechanical prototype controlled by a servo motor allowed automatic rotation of the ICE-catheter around its longitudinal axis. During a single heartbeat, the ICE-catheter was rotated and 2D-images were acquired. Reconstruction into a 3D volume and rendering by a prototype software was performed beat to beat. After experimental validation using a rigid phantom, the system was tested in an animal study and afterwards, for quantitative validation, in a dynamic phantom. Acquisition of beat to beat 3D-reconstruction was technically feasible. However, twisting of the ICE-catheter shaft due to friction and torsion was found and rotation was hampered. Also, depiction of catheters was not always ensured in case of parallel alignment. Using a curved sheath for depiction of cardiac anatomy there was no congruent depiction of shape and dimension of static and moving objects. Beat to beat 3D-ICE-imaging is feasible. However, shape and dimension of static and moving objects cannot always be displayed with necessary steadiness as needed in the clinical setting. As catheter depiction is also limited, clinical use seems impossible

Fully Automated Versus Standard Tracking of Left Ventricular Ejection Fraction and Longitudinal Strain the FAST-EFs Multicenter Study

none10siBACKGROUND: Echocardiographic determination of ejection fraction (EF) by manual tracing of endocardial borders is time consuming and operator dependent, whereas visual assessment is inherently subjective. OBJECTIVES: This study tested the hypothesis that a novel, fully automated software using machine learning-enabled image analysis will provide rapid, reproducible measurements of left ventricular volumes and EF, as well as average biplane longitudinal strain (LS). METHODS: For a total of 255 patients in sinus rhythm, apical 4- and 2-chamber views were collected from 4 centers that assessed EF using both visual estimation and manual tracing (biplane Simpson's method). In addition, datasets were saved in a centralized database, and machine learning-enabled software (AutoLV, TomTec-Arena 1.2, TomTec Imaging Systems, Unterschleissheim, Germany) was applied for fully automated EF and LS measurements. A reference center reanalyzed all datasets (by visual estimation and manual tracking), along with manual LS determinations. RESULTS: AutoLV measurements were feasible in 98% of studies, and the average analysis time was 8 ± 1 s/patient. Interclass correlation coefficients and Bland-Altman analysis revealed good agreements among automated EF, local center manual tracking, and reference center manual tracking, but not for visual EF assessments. Similarly, automated and manual LS measurements obtained at the reference center showed good agreement. Intraobserver variability was higher for visual EF than for manual EF or manual LS, whereas interobserver variability was higher for both visual and manual EF, but not different for LS. Automated EF and LS had no variability. CONCLUSIONS: Fully automated analysis of echocardiography images provides rapid and reproducible assessment of left ventricular EF and LS.openKnackstedt, Christian; Bekkers, Sebastiaan C.A.M.; Schummers, Georg; Schreckenberg, Marcus; Muraru, Denisa; Badano, Luigi; Franke, Andreas; Bavishi, Chirag; Omar, Alaa Mabrouk Salem; Sengupta, Partho P.Knackstedt, Christian; Bekkers, Sebastiaan C. A. M.; Schummers, Georg; Schreckenberg, Marcus; Muraru, Denisa; Badano, Luigi; Franke, Andreas; Bavishi, Chirag; Omar, Alaa Mabrouk Salem; Sengupta, Partho P