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Aims: A set of indicators to assess the quality of care for patients hospitalized for heart failure was developed by an expert working group of the Italian Health Ministry. Because a better performance profile measured using these indicators does not necessarily translate to better outcomes, a study to validate these indicators through their relationship with measurable clinical outcomes and healthcare costs supported by the Italian National Health System was carried out. Methods and results: Residents of four Italian regions (Lombardy, Marche, Lazio, and Sicily) who were newly hospitalized for heart failure (irrespective of stage and New York Heart Association class) during 2014–2015 entered in the cohort and followed up until 2019. Adherence to evidence‐based recommendations [i.e. renin–angiotensin–aldosterone system (RAS) inhibitors, beta‐blockers, mineralocorticoid receptor antagonists (MRAs), and echocardiograms (ECCs)] experienced during the first year after index discharge was assessed. Composite clinical outcomes (cardiovascular hospital admissions and all‐cause mortality) and healthcare costs (hospitalizations, drugs, and outpatient services) were assessed during the follow‐up. The restricted mean survival time at 5 years (denoted as the number of months free from clinical outcomes), the hazard of clinical outcomes (according to the Cox model), and average annual healthcare cost (expressed in euros per person‐year) were compared between adherent and non‐adherent patients. A non‐parametric bootstrap method based on 1000 resamples was used to account for uncertainty in cost‐effectiveness estimates. A total of 41 406 patients were included in this study (46.3% males, mean age 76.9 ± 9.4 years). Adherence to RAS inhibitors, beta‐blockers, MRAs, and ECCs were 64%, 57%, 62%, and 20% among the cohort members, respectively. Compared with non‐adherent patients, those who adhered to ECCs, RAS inhibitors, beta‐blockers, and MRAs experienced (i) a delay in the composite outcome of 1.6, 1.9, 1.6, and 0.6 months and reduced risks of 9% (95% confidence interval, 2–14%), 11% (7–14%), 8% (5–11%), and 4% (−1–8%), respectively; and (ii) lower (€262, €92, and €571 per year for RAS inhibitors, beta‐blockers, and MRAs, respectively) and higher costs (€511 per year for ECC). Adherence to RAS inhibitors, beta‐blockers, and MRAs showed a delay in the composite outcome and a saving of costs in 98%, 84%, and 93% of the 1000 bootstrap replications, respectively. Conclusions: Strict monitoring of patients with heart failure through regular clinical examinations and drug therapies should be considered the cornerstone of national guidelines and audits. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) pollution has long been considered a severe environmental issue. The Road Transport sector is recognized as one of the biggest contributors to carbon emissions. In tackling climate change, the Kyoto Protocol was signed by developed and developing countries and represents a voluntary international treaty that aims to reduce carbon emissions. This work seeks to identify similarities in trend emission performance among 31 countries that ratified the agreement. The data come from the Emissions Database for Global Atmospheric Research, which contains the annual values of polluting gas emissions from 1970 to 2018. To do this, time series cluster analyses have been applied using two distance measures and considering different sub-periods. [ABSTRACT FROM AUTHOR]

This paper introduces SEISMONOISY, an application designed for monitoring the spatiotemporal characteristic and variability of the seismic noise of an entire seismic network with a quasi-real-time monitoring approach. Actually, we have applied the developed system to monitor 12 seismic networks distributed throughout the Italian territory. These networks include the Rete Sismica Nazionale (RSN) as well as other regional networks with smaller coverage areas. Our noise monitoring system uses the methods of Spectral Power Density (PSD) and Probability Density Function (PDF) applied to 12 h long seismic traces in a 24 h cycle for each station, enabling the extrapolation of noise characteristics at seismic stations after a Seismic Noise Level Index (SNLI), which takes into account the global seismic noise model, is derived. The SNLI value can be used for different applications, including network performance evaluation, the identification of operational problems, site selection for new installations, and for scientific research applications (e.g., volcano monitoring, identification of active seismic sequences, etc.). Additionally, it aids in studying the main noise sources across different frequency bands and changes in the characteristics of background seismic noise over time. [ABSTRACT FROM AUTHOR]