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With seismic catalogues becoming progressively larger, extracting information becomes challenging and calls upon using sophisticated statistical analysis. Data are typically clustered by machine learning algorithms to find patterns or identify regions of interest that require further exploration. Here, we investigate two density-based clustering algorithms, DBSCAN and OPTICS, for their capability to analyse the spatial distribution of seismicity and their effectiveness in discovering highly active seismic volumes of arbitrary shapes in large data sets. In particular, we study the influence of varying input parameters on the cluster solutions. By exploring the parameter space, we identify a crossover region with optimal solutions in between two phases with opposite behaviours (i.e. only clustered and only unclustered data points). Using a synthetic case with various geometric structures, we find that solutions in the crossover region consistently have the largest clusters and best represent the individual structures. For identifying strong anisotropic structures, we illustrate the usefulness of data rescaling. Applying the clustering algorithms to seismic catalogues of recent earthquake sequences (2016 Central Italy and 2016 Kumamoto) confirms that cluster solutions in the crossover region are the best candidates to identify 3-D features of tectonic structures that were activated in a seismic sequence. Finally, we propose a list of recipes that generalizes our analyses to obtain such solutions for other seismic sequences. [ABSTRACT FROM AUTHOR]

Background The proportion of reported causes of death (CoDs) that are not underlying causes can be relevant even in high-income countries and seriously affect health planning. The Global Burden of Disease (GBD) study identifies these 'garbage codes' (GCs) and redistributes them to underlying causes using evidence-based algorithms. Planners relying on vital registration data will find discrepancies with GBD estimates. We analyse these discrepancies, through the analysis of GCs and their redistribution. Methods We explored the case of Italy, at national and regional level, and compared it to nine other Western European countries with similar population sizes. We analysed differences between official data and GBD 2019 estimates, for the period 1990–2017 for which we had vital registration data for most select countries. Results In Italy, in 2017, 33 000 deaths were attributed to unspecified type of stroke and 15 000 to unspecified type of diabetes, these making a fourth of the overall garbage. Significant heterogeneity exists on the overall proportion of GCs, type (unspecified or impossible underlying causes), and size of specific GCs among regions in Italy, and among the select countries. We found no pattern between level of garbage and relevance of specific GCs. Even locations performing below average show interesting lower levels for certain GCs if compared to better performing countries. Conclusions This systematic analysis suggests the heterogeneity in GC levels and causes, paired with a more detailed analysis of local practices, strengths and weaknesses, could be a positive element in a strategy for the reduction of GCs in Italy. [ABSTRACT FROM AUTHOR]

A rockfall (RF) is a ubiquitous geohazard that is difficult to monitor or predict and poses a significant risk for people and transportation in several hilly and mountainous environments. The seismic signal generated by RF carries abundant physical and mechanical information. Thus, signals can be used by researchers to reconstruct the event location, onset time, volume and trajectory, and develop an efficient early warning system. Therefore, the precise automatic detection and classification of RF events are important objectives for scientists, especially in seismic monitoring arrays. An algorithm called DESTRO (DEtection and STorage of ROckfalls) aimed at combining seismic event automatic detection and classification was implemented ad hoc within the MATLAB environment. In event detection, the STA/LTA (short-time-average through long-time-average) method combined with other parameters, such as the minimum duration of an RF and the minimum interval time between two continuous seismic events is used. Furthermore, nine significant features based on the frequency, amplitude, seismic waveform, duration and multiple station attributes are newly proposed to classify seismic events in a RF environment. In particular, a three-step classification method is proposed for the discrimination of five different source types: RFs, earthquakes (EQs), tremors, multispike events (MSs) and subordinate MS events. Each component (vertical, east–west and north–south) at each station within the monitoring network is analysed, and a three-step classification is performed. At a given time, the event series detected from each component are integrated and reclassified component by component and station by station into a final event-type series as an output result. By this algorithm, a case study of the seven-month-long seismic monitoring of a former quarry in Central Italy was investigated by means of four triaxial velocimeters with continuous acquisition at a sampling rate of 200 Hz. During this monitoring period, a human-induced RF simulation was performed, releasing 95 blocks (in which 90 blocks validated) of different sizes from the benches of the quarry. Consequently, 64.9 per cent of EQs within 100 km were confirmed in a one-month monitoring period, 88 blocks in the RF simulation were classified correctly as RF events and 2 blocks were classified as MSs given their small energy. Finally, an ad hoc section of the algorithm was designed specifically for RF classification combined with EQ recognition. The algorithm could be applied in slope seismic monitoring to monitor the dynamic states of rock masses, as well as in slope instability forecasting and risk evaluation in EQ-prone areas. [ABSTRACT FROM AUTHOR]

Human cytomegalovirus (HCMV) infections are among the most common complications arising in transplant patients, elevating the risk of various complications including loss of graft and death. HCMV infections are also responsible for more congenital infections worldwide than any other agent. Congenital HCMV (cCMV) infections are the leading nongenetic cause of sensorineural hearing loss and a source of significant neurological disabilities in children. While there is overlap in the clinical and laboratory approaches to diagnosis of HCMV infections in these settings, the management, follow-up, treatment, and diagnostic strategies differ considerably. As yet, no country has implemented a universal screening program for cCMV. Here, we summarize the issues, limitations, and application of diagnostic strategies for transplant recipients and congenital infection, including examples of screening programs for congenital HCMV that have been implemented at several centers in Japan, Italy, and the United States. [ABSTRACT FROM AUTHOR]

Background The article examines gender differences in happy life expectancy at age 50 (LE50) and computes the age-specific contributions of mortality and happiness effects to gender differences in happy LE50 in 16 European countries. Methods Abridged life tables and happy LE50 were calculated using conventional life tables and Sullivan's method. Age-specific death rates were calculated from deaths and population exposures in the Human Mortality Database. Happiness prevalence was estimated using the 2010–11 Survey of Health, Ageing and Retirement in Europe. Happiness was defined using a single question about life satisfaction on a scale of 0–10. A decomposition algorithm was applied to estimate the exact contributions of the differences in mortality and happiness to the overall gender gap in happy LE50. Results Gender differences in happy LE50 favour women in all countries except Portugal (0.43 years in Italy and 3.55 years in Slovenia). Generally, the contribution of the gender gap in happiness prevalence is smaller than the one in mortality. The male advantage in the prevalence of happiness partially offsets the effects of the female advantage in mortality on the total gender gap in happy LE50. Gender differences in unhappy life years make up the greatest share of the gender gap in total LE50 in all countries except Denmark, Germany, Netherlands, Slovenia and Sweden. Conclusion Countries with the largest gender gap in LE are not necessarily the countries with larger differences in happy LE50. The remaining years of life of women are expected to be spent not only in unhealthy but also in unhappy state. [ABSTRACT FROM AUTHOR]

Aim: The aim of this multicentre, observational, transversal study was to evaluate pacemaker (PM) choice and setting in a large number of patients, in order to understand their relationship with the patients' clinical characteristics.Methods and Results: The study enrolled a total of 1858 patients (71 ± 14 years, 54% male), consecutively evaluated during scheduled PM follow-up visits in 7 Italian cardiac arrhythmia centres. To evaluate the appropriateness of PM choice in relation to the patients' clinical characteristics, we analysed their rhythm disorders at the time of device implantation and the characteristics of the devices implanted. To evaluate the appropriateness of device setting, current rhythm disorders and device setting at the time of enrolment were analysed. In the overall study population, 64.3% of the patients received a PM with all of the features required for their rhythm disorder [80.8% in persistent atrioventricular (AV) block, 76.5% in atrial fibrillation needing pacing, 71.0% in sinus node disease, 58.7% in non-persistent atrioventricular block (AVB), 52.7% in neuro-mediated syncope]. The most frequent cause of inappropriate PM choice was the lack of an algorithm to promote intrinsic AV conduction in non-persistent AVB patients (38.1%). In 76.2% of the patients with an appropriate PM (n = 1301), the PM was optimally set for their rhythm disorder.Conclusions: In the present 'real-world' registry, a large number of patients (35.7%) did not receive an optimal PM for their rhythm disorders. Moreover, one-fourth of appropriate PMs were not programmed according to the patients' clinical characteristics. [ABSTRACT FROM AUTHOR]

Objective. The aim of this study was to develop and validate an algorithm to assist the attribution of neuropsychiatric (NP) events to underlying disease in SLE patients. Methods. Phase 1 identified and categorized candidate items to be included in the algorithm for the attribution of an NP event to SLE and their relative weights through a literature-informed consensus-driven process. Using a retrospective training cohort of SLE, phase 2 validated items selected in phase 1 and refined weights through a data-driven process, fitting items as independent variables and expert evaluation (clinical judgement) as reference standard in logistic models. Phase 3 consisted of a validation process using an external multicentre retrospective SLE cohort. Results. Phase 1 identified four different items: timing of the NP event, type of event, confounding factors and favouring factors. The training and validating cohorts included 228 and 221 patients, respectively. Each patient experienced at least one NP event characterized using the ACR case definition. In these samples, items selected in phase 1 showed good performance in discriminating patients with NPSLE: the area under the receiver operating characteristic curve using dichotomous outcomes was 0.87 in the training set and 0.82 in the validating set. Relevant cut-offs of the validated score identify events with a positive predictive value of 100% (95% CI 93.2, 100) and 86.3% (95% CI 76.2, 93.2) in the training and validating cohorts, respectively. Conclusion. A new algorithm based on a probability score was developed and validated to determine the relationship between NP events and SLE. [ABSTRACT FROM AUTHOR]

Aims To explore the potentiality of cardiovascular magnetic resonance (CMR) in the quantitative evaluation of mitral valve annulus (MVA) and tricuspid valve annulus (TVA) morphology and dynamics. Methods and results CMR was performed in 13 normal subjects and 9 patients with mitral (n = 7) or tricuspid regurgitation (n = 2), acquiring cine-images in 18 radial long-axis planes passing through the middle of MVA or TVA. A novel algorithm was used to obtain dynamic three-dimensional (3D) reconstruction of MVA and TVA. Analysis was feasible in all cases, allowing accurate 3D annular reconstruction and tracking. The 3D area increased from systole [MVA, median = 10.0 cm2 (first quartile = 8.6, third quartile = 11.4); TVA, 11.2 cm2 (8.8–13.2)] to diastole [MVA, 10.6 cm2 (9.4, 11.7); TVA, 11.9 cm2 (9.2–13.5)], with TVA larger than MVA. While the longest diameter showed similar systolic and diastolic values, the shortest diameter elongated from systole [MVA, 30 mm (29–33); TVA, 33 mm (31–36)] to diastole [MVA, 31 mm (29–32); TVA, 36 mm (33–39)]. Also, TVA became more circular than MVA. TVA showed lower peak systolic excursion in the septal [15.9 mm (13.0–18.5)] and anterior regions [17.9 mm (12.2–20.7)] compared with the posterior [21.9 mm (18.6–24.0)] segment. Values in MVA were smaller than in TVA, slightly higher in anterior [11.2 mm (9.5–13.0)] than in posterior [12.4 mm (10.2–14.6)] segments. Valvular regurgitation was associated with enlarged, flattened, and more circular annuli. Conclusion The applied method was feasible and accurate in normal and regurgitant valves, and may potentially have an impact on diagnosis, improvement of surgical techniques and design of annular prostheses. [ABSTRACT FROM AUTHOR]