Obesity and cardiovascular risk. Systematic intervention is the key for prevention

Obesity is a serious public health issue and associated with an increased risk of cardiovascular disease events and mortality. The risk of cardiovascular complications is directly related to excess body fat mass and ectopic fat deposition, but also other obesity-related complications such as pre-type 2 diabetes, obstructive sleep apnoea, and non-alcoholic fatty liver diseases. Body mass index and waist circumference are used to classify a patient as overweight or obese and to stratify cardiovascular risk. Physical activity and diet, despite being key points in preventing adverse events and reducing cardiovascular risk, are not always successful strategies. Pharmacological treatments for weight reduction are promising strategies, but are restricted by possible safety issues and cost. Nonetheless, these treatments are associated with improvements in cardiovascular risk factors, and studies are ongoing to better evaluate cardiovascular outcomes. Bariatric surgery is effective in reducing the incidence of death and cardiovascular events such as myocardial infarction and stroke. Cardiac rehabilitation programs in obese patients improve cardiovascular disease risk factors, quality of life, and exercise capacity. The aim of this review was to critically analyze the current role and future aspects of lifestyle changes, medical and surgical treatments, and cardiac rehabilitation in obese patients, to reduce cardiovascular disease risk and mortality, and to highlight the need for a multidisciplinary approach to improving cardiovascular outcomes

An overview of sport participation and exercise prescription in mitral valve disease

The incidence of heart valve disease (HVD) has been rising over the last few decades, mainly due to the increasing average age of the general population, and mitral valve (MV) disease is the second most prevalent HVD after calcific aortic stenosis, but MV disease is a heterogeneous group of different pathophysiological diseases. It is widely proven that regular physical activity reduces all-cause mortality rates, and exercise prescription is part of the medical recommendations for patients affected by cardiovascular diseases. However, changes in hemodynamic balance during physical exercise (including the increase in heart rate, preload, or afterload) could favor the progression of the MV disease and potentially trigger major cardiac events. In young patients with HVD, it is therefore important to define criteria for allowing competitive sport or exercise prescription, balancing the positive effects as well as the potential risks. This review focuses on mitral valve disease pathophysiology, diagnosis, risk stratification, exercise prescription, and competitive sport participation selection, and offers an overview of the principal mitral valve diseases with the aim of encouraging physicians to embody exercise in their daily practice when appropriate

Ecophysiological Responses to Rainfall Variability in Grassland and Forests Along a Latitudinal Gradient in Italy

In the Mediterranean region, ecosystems are severely affected by climate variability. The Italian Peninsula is a hot spot for biodiversity thanks to its heterogeneous landscape and the Mediterranean, Continental, and Alpine climates hosting a broad range of plant functional types along a limited latitudinal range from 40\u2032 to 46\u2032 N. In this study we applied a comparative approach integrating descriptive statistics, time series analysis, and multivariate techniques to answer the following questions: (i) do the climatic variables affect Gross Primary Productivity (GPP), Reco, Water Use Efficiency (WUE), and ET to a similar extent among different sites? (ii) Does a common response pattern exist among ecosystems along a latitudinal gradient in Italy? And, finally (iii) do these ecosystems respond synchronically to meteorological conditions or does a delayed response exist? Six sites along a latitudinal, altitudinal, and vegetational gradient from semi-arid (southern Italy), to a mountainous Mediterranean site (central Italy), and sub-humid wet Alpine sites (northern Italy) were considered. For each site, carbon and water fluxes, and meteorological data collected during two hydrologically-contrasting years (i.e., a dry and a wet year) were analyzed. Principal Component Analysis (PCA) was adopted to identify temporal and spatial variations in GPP, Ecosystem Respiration (Reco), WUE, and Evapotranspiration (ET). The model outlined differences among Mediterranean semi-arid, Mediterranean mountainous, and Alpine sites in response to contrasting precipitation regimes. GPP, Reco, WUE, and ET increased up to 16, 19, 25, and 28%, respectively in semi-arid Mediterranean sites and up to 15, 32, 15, and 11%, respectively in Alpine sites in the wet year compared to the dry year. Air temperature was revealed to be one of the most important variables affecting GPP, Reco, WUE, and ET in all the study sites. While relative air humidity was more important in southern Mediterranean sites, global radiation was more significant in northern Italy. Our work suggests that a realistic prediction of the main responses of Italian forests under climate change should also take in account delayed responses due to acclimation to abiotic stress or changing environmental conditions

Il Progetto SEE-GeoForm: uno strumento per la consultazione di dati geologici e di pericolosità sismica riferiti all’intero territorio nazionale

Il progetto SEE-GeoForm (Site Effects Evaluation - Geological Form: http://www.seegeoform.it) nasce con l’obiettivo di realizzare uno strumento semplice, potente e completo per la consultazione e la rappresentazione, tramite un WebGIS, di dati geologici, geomorfologici, geotecnici e geofisici relativi all’intero territorio italiano. In questo modo, si vogliono concentrare in un sistema flessibile e intuitivo, dotato di un’unica modalità di accesso e consultazione, una serie di informazioni che attualmente sono disperse in numerosi database mono-tematici consultabili via Internet. Attualmente il WebGIS contiene dati georeferenziati e carte tematiche relative alla pericolosità sismica a differenti scale territoriali e per diverse unità amministrative (regioni, province e comuni). Le informazioni provengono sia da banche dati esistenti che da elaborazioni effettuate “ad hoc” nell’ambito di questo progetto (carte tematiche in scala 1:100.000 del territorio italiano). Per rendere il sistema più flessibile ed aggiornabile è stata sviluppata una piattaforma che utilizza esclusivamente tecnologie “open source”, basate sulle linee guida dell’Open Geospatial Consortium (OGC); in questo modo è stato possibile realizzare alcuni moduli tematici che sono totalmente compatibili con il protocollo standard denominato WMS (Web Map Services) per la consultazione e la visualizzazione spaziale dei dati tramite Internet

SARS-CoV-2 transmission by asymptomatic healthcare workers positive to screening swab: an Italian study

Background SARS-CoV-2 spreads primarily through respiratory droplets of symptomatic individuals. With respect to asymptomatic individuals, there are conflicting results in the literature and a lack of studies specifically examining transmission in healthcare settings. Methods The aim of this retrospective study, conducted in a northeastern Italian region, was to estimate the contagiousness of asymptomatic healthcare workers (HCWs) who tested positive for SARS-CoV-2. Asymptomatic HCWs who tested positive for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (rRT-PCR) at a regular screening nasopharyngeal or oropharyngeal swab between 1 February 2020 and 15 September 2020 were considered index cases. Contacts who were at high risk of infection and had follow-up swabs were included. Contacts were considered infected if they had a positive follow-up swab and/or symptoms associated with COVID-19 confirmed by a positive test within 14 days of exposure. Information was taken from records previously collected to identify contacts. Infectivity was estimated using the attack rate (AR) with a 95% confidence interval (95% CI). Results Thirty-eight asymptomatic HCWs who were positive at the screening swab and 778 contacts were identified. Contacts included 63.8% of colleagues, 25.6% of patients, 7.7% of family members and 3.0% of other contacts. Seven contacts tested positive for SARS-CoV-2 (AR: 0.91%, 95% CI: 0.89-0.93). Five of them were family members (AR: 8.3%), one was a colleague (0.2%) and one was a contact of other type (4.2%). Conclusions Viral spread by asymptomatic HCWs was less than in other settings. Identification of risk factors for transmission and reliable indicators of infectivity would be important to prioritize preventive measures

Ecophysiological Responses to Rainfall Variability in Grassland and Forests Along a Latitudinal Gradient in Italy

In the Mediterranean region, ecosystems are severely affected by climate variability. The Italian Peninsula is a hot spot for biodiversity thanks to its heterogeneous landscape and the Mediterranean, Continental, and Alpine climates hosting a broad range of plant functional types along a limited latitudinal range from 40′ to 46′ N. In this study we applied a comparative approach integrating descriptive statistics, time series analysis, and multivariate techniques to answer the following questions: (i) do the climatic variables affect Gross Primary Productivity (GPP), Reco, Water Use Efficiency (WUE), and ET to a similar extent among different sites? (ii) Does a common response pattern exist among ecosystems along a latitudinal gradient in Italy? And, finally (iii) do these ecosystems respond synchronically to meteorological conditions or does a delayed response exist? Six sites along a latitudinal, altitudinal, and vegetational gradient from semi-arid (southern Italy), to a mountainous Mediterranean site (central Italy), and sub-humid wet Alpine sites (northern Italy) were considered. For each site, carbon and water fluxes, and meteorological data collected during two hydrologically-contrasting years (i.e., a dry and a wet year) were analyzed. Principal Component Analysis (PCA) was adopted to identify temporal and spatial variations in GPP, Ecosystem Respiration (Reco), WUE, and Evapotranspiration (ET). The model outlined differences among Mediterranean semi-arid, Mediterranean mountainous, and Alpine sites in response to contrasting precipitation regimes. GPP, Reco, WUE, and ET increased up to 16, 19, 25, and 28%, respectively in semi-arid Mediterranean sites and up to 15, 32, 15, and 11%, respectively in Alpine sites in the wet year compared to the dry year. Air temperature was revealed to be one of the most important variables affecting GPP, Reco, WUE, and ET in all the study sites. While relative air humidity was more important in southern Mediterranean sites, global radiation was more significant in northern Italy. Our work suggests that a realistic prediction of the main responses of Italian forests under climate change should also take in account delayed responses due to acclimation to abiotic stress or changing environmental conditions

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

Impact of coronary calcification assessed by coronary CT angiography on treatment decision in patients with three-vessel CAD:insights from SYNTAX III trial

 : OBJECTIVES: The aim of this study was to determine Syntax scores based on coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) and to assess whether heavy coronary calcification significantly limits the CCTA evaluation and the impact of severe calcification on heart team’s treatment decision and procedural planning in patients with three-vessel coronary artery disease (CAD) with or without left main disease. METHODS: SYNTAX III was a multicentre, international study that included patients with three-vessel CAD with or without left main disease. The heart teams were randomized to either assess coronary arteries with coronary CCTA or ICA. We stratified the patients based on the presence of at least 1 lesion with heavy calcification defined as arc of calcium >180° within the lesion using CCTA. Agreement on the anatomical SYNTAX score and treatment decision was compared between patients with and without heavy calcifications. RESULTS: Overall, 222 patients with available CCTA and ICA were included in this trial subanalysis (104 with heavy calcification, 118 without heavy calcification). The mean difference in the anatomical SYNTAX score (CCTA derived—ICA derived) was lower in patients without heavy calcifications [mean (−1.96 SD; +1.96 SD) = 1.5 (−19.3; 22.4) vs 5.9 (−17.5; +29.3), P = 0.004]. The agreement on treatment decision did not differ between patients with (Cohen’s kappa 0.79) or without coronary calcifications (Cohen’s kappa 0.84). The agreement on the treatment planning did not differ between patients with (concordance 80.3%) or without coronary calcifications (concordance 82.8%). CONCLUSIONS: An overall good correlation between CCTA- and ICA-derived Syntax score was found. The presence of heavy coronary calcification moderately influenced the agreement between CCTA and ICA on the anatomical SYNTAX score. However, agreement on the treatment decision and planning was high and irrespective of the presence of calcified lesions