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The point at which clinical development programs transition from early-phase to pivotal trials is a critical milestone. Substantial uncertainty about the outcome of pivotal trials may remain even after seeing positive early-phase data, and companies may need to make difficult prioritization decisions for their portfolio. The probability of success (PoS) of a program, a single number expressed as a percentage reflecting the multitude of risks that may influence the final program outcome, is a key decision making tool. Despite its importance, companies often rely on crude industry benchmarks that may be "adjusted" by experts based on undocumented criteria and which are typically misaligned with the definition of success used to drive commercial forecasts, leading to overly optimistic expected net present value calculations. We developed a new framework to assess the PoS of a program before pivotal trials begin. Our definition of success encompasses the successful outcome of pivotal trials, regulatory approval, and meeting the requirements for market access as outlined in the target product profile. The proposed approach is organized in four steps and uses an innovative Bayesian approach to synthesize all relevant evidence. The new PoS framework is systematic and transparent. It will help organizations to make more informed decisions. In this paper, we outline the rationale and elaborate on the structure of the proposed framework, provide examples, and discuss the benefits and challenges associated with its adoption.

Significant paravalvular leak regurgitation (PVLR) after transcatheter aortic valve replacement (TAVR) is a well-known complication associated with disabling symptoms related to heart failure and hemolysis or both, with poor prognostic implications. Although challenging and technically demanding, percutaneous closure is an effective treatment option for high-risk patients with symptomatic PVLR. Here, we present two cases of transcatheter PVLR closure after replacement of third-generation (one self-expandable and one balloon-expandable) transcatheter aortic valves, each with peculiar challenges, and the strategies adopted to increase the success rate of percutaneous closure.

Performing transcatheter aortic valve implantation with high implantation technique, i.e. with an aorto-ventricular ratio 60/40, reduces the need of permanent pacemaker implantation. Valve calcification and prosthesis oversizing are predictors of permanent pacemaker implantation, but there are no available data on their role when transcatheter aortic valve implantation is performed with an aorto-ventricular ratio 60/40. The aim of this study was to evaluate the effect of leaflets/annulus calcification and prosthesis oversizing on the incidence of permanent pacemaker implantation after transcatheter aortic valve implantation with a high implantation technique. Transcatheter aortic valve implantation was performed in 48 patients implanting a balloon-expandable transcatheter heart valve with an aorto-ventricular ratio 60/40. Calcium burden was assessed by preprocedural multidetector computed tomography. An invasive electrophysiological study was performed before and after transcatheter aortic valve implantation. Five patients (10.4%) needed permanent pacemaker implantation. At univariate analysis, baseline right bundle branch block and postprocedural PR, QRS and His-ventricular interval elongation significantly predicted permanent pacemaker implantation (p 0.05). Receiver-operating characteristic curve analysis showed a correlation between transcatheter heart valve oversizing and permanent pacemaker implantation need, with the best cut-off being 17% (AUC = 0.72, p = 0.033). Linear regression analysis demonstrated that QRS complex elongation was related to total, left and non-coronary leaflet calcification (p 0.05). This study demonstrates that, when transcatheter aortic valve implantation is performed using a balloon-expandable transcatheter heart valve deployed with an aorto-ventricular ratio 60/40, the presence of leaflets/annulus calcification or the need to oversize the prosthesis correlate with the occurrence of pathological cardiac conduction delays.

The expansion of coronavirus disease 2019 (COVID-19) prompted measures of disease containment by the Italian government with a national lockdown on March 9, 2020. The purpose of this study is to evaluate the rate of hospitalization and mode of in-hospital treatment of patients with chronic limb-threatening ischemia (CLTI) before and during lockdown in the Campania region of Italy. The study population includes all patients with CLTI hospitalized in Campania over a 10-week period: 5 weeks before and 5 weeks during lockdown ( n = 453). Patients were treated medically and/or underwent urgent revascularization and/or major amputation of the lower extremities. Mean age was 69.2 ± 10.6 years and 27.6% of the patients were women. During hospitalization, 21.9% of patients were treated medically, 78.1% underwent revascularization, and 17.4% required amputations. In the weeks during the lockdown, a reduced rate of hospitalization for CLTI was observed compared with the weeks before lockdown (25 vs 74/100,000 inhabitants/year; incidence rate ratio: 0.34, 95% CI 0.32–0.37). This effect persisted to the end of the study period. An increased amputation rate in the weeks during lockdown was observed (29.3% vs 13.4%; p < 0.001). This study reports a reduced rate of CLTI-related hospitalization and an increased in-hospital amputation rate during lockdown in Campania. Ensuring appropriate treatment for patients with CLTI should be prioritized, even during disease containment measures due to the COVID-19 pandemic or other similar conditions.

Background Endarterectomy is considered the gold standard therapy for common femoral artery (CFA) steno-occlusive lesions, but a significant risk of perioperative mortality and complications has been reported. Objective Aim of this study is to evaluate the efficacy at a long-term follow-up of patients with CFA steno-occlusive lesions treated with directional atherectomy and drug coated balloon (DCB). Material and methods In this single-center registry, 78 patients (male: 80.7%; age: 71 ± 15 years; occlusions: 25%) with 80 CFA lesions were included, with 39.7% of them undergoing directional atherectomy and drug coated balloon due to critical limb ischemia and 60.3% due to lower-limb intermittent claudication. The long-term follow-up was completed by 75 patients (3 years). The 31 patients with critical ischemia (39.7%) were further subdivided into 20 (25.6%) patients with pain at rest and 11 (14.1%) with trophic changes, ulcers and/or tissue loss. We considered the primary and the secondary outcome, referring, respectively to peak systolic velocity ratio (PSVR) ≥ 2.4 on duplex or > 50% stenosis on digital subtraction angiography at 36 months and to clinically driven target lesion revascularization at 36 months. Results The primary and secondary outcome was obtained in 84% and 86.7% of patients, at 36 months of follow up. Bailout stenting was necessary in 6/80 cases (7.5%) for suboptimal result. Freedom from MALE was obtained in 98.6% of patients. Conclusions These results confirm that directional atherectomy and drug coated balloon strategy for the treatment of CFA lesions is effective at a long-term follow-up and could be considered as a good alternative to surgery.

SummaryBackgroundThe emerging threat represented by SARS-CoV-2 variants, demands the development of therapies for better clinical management of COVID-19. MAD0004J08 is an extremely potent Fc-engineered monoclonal antibody (mAb) able to neutralise in vitro all current SARS-CoV-2 variants of concern (VoCs). This ongoing study, evaluates safety, pharmacokinetics and SARS-CoV-2 sera neutralization effect of MAD0004J08 when administered as single dose intramuscularly in healthy adults.MethodWe conducted a dose escalation study with sequential enrolment of three cohorts, each with an increasing dose level of MAD0004J08 (48mg, 100mg and 400mg). Within each cohort, 10 young healthy adults were randomized with 4:1 ratio to a single intramuscular (i.m.) injection of MAD0004J08 or placebo. The primary endpoint is the proportion of subjects with severe and/or serious treatment emergent adverse events (TEAEs) within 7 days post-treatment. Secondary endpoints reported in this paper are the proportion of subjects with solicited TEAEs up 7 days post dosing, MAD0004J08 serum concentrations and neutralising activity versus the original SARS-COV-2 Wuhan virus at different timepoints post-dosing. As post-hoc analyses, we compared the sera neutralising titres of subjects who received MAD0004J08 with those of people that had received the COVID-19 BNT162b2 mRNA vaccine in the previous sixty days (n=10) and COVID-19 convalescent patients (n=20), and assessed serum neutralisation activity against the B.1.1.7 (alpha), B.1.351 (beta) and B.1.1.248 (gamma) SARS-CoV-2 variants of concern.FindingsA total of 30 subjects, 10 per cohort, were enrolled and randomized. Data up to 30 days were available and analysed in this report. No severe TEAEs were reported in any of the cohorts in the 7 days post-treatment. MAD0004J08 was detected in the sera of treated subjects within few hours post-administration and reached almost maximal levels on day 8. The geometric mean neutralising titres (GMT) assessed against the original Wuhan virus peaked on day 8 and ranged 226 – 905, 905 – 2,560, and 1,280 – 5,120 for cohort 1, 2 and 3 respectively. The sera neutralising GMT in MAD0004J08 treated subjects in all the three cohorts were found to be 1·5-54·5-fold higher compared to sera from convalescent patients and 1·83– 76·4-fold higher compared to sera from COVID-19 vaccinees. Finally, GMT in MAD0004J08 treated subjects showed high neutralising titres versus the B.1.1.7 (alpha), B.1.351 (beta) and B.1.1.248 (gamma) SARS-CoV-2 VoCs.InterpretationA single dose administration of MAD0004J08 via i.m. route is safe and well tolerated and results in a rapid systemic distribution of the MAD0004J08 and sera neutralising titres higher than COVID-19 convalescent and vaccinated subjects. A single dose administration of MAD0004J08 is also sufficient to effectively neutralise major SARS-CoV-2 variants of concern. Based on these results, a Phase 2-3 trial is ongoing to further assess the safety, dosage, and efficacy of MAD0004J08 in asymptomatic or mild-moderate symptomatic COVID-19 patients.FundingEU Malaria Fund, Ministero dello Sviluppo Economico, Ministero della Salute, Regione Toscana, Toscana Life Sciences Sviluppo and European Research Council.Research in contextEvidence before this studyWe searched PUBMED, MEDLINE and MedRxiv for clinical trials, meta-analyses and randomized controlled trials evaluating the antibody neutralization titres vs. different SARS-CoV-2 variants of concern obtained from subjects who received monoclonal antibodies for the treatment of COVID-19 using the following search terms: (“COVID-19” OR “SARS-CoV-2”) AND (“monoclonal antibody” OR “neutralising antibody”) AND (“variants” OR “variants of concern”). No relevant studies were identified.Added value of this studyThis is the first human study assessing safety, PK and neutralising potential of MAD0004J08, a monoclonal antibody against SARS-CoV-2 wild type Wuhan virus and variants of concern, administered intramuscularly at low dosages (48, 100 and 400 mg). MAD0004J08 showed to be safe and well tolerated in the tested dose range. Anti-spike antibodies were detected in the sera of tested SARS-CoV-2 negative healthy adults few hours post-injection. In addition, the sera obtained from MAD0004J08treated subjects, showed to have high neutralisation titres against the Wuhan virus, the B.1.1.7 (alpha), B.1.351 (beta) and B.1.1.248 (gamma) variants of concern.Implications of all the available evidenceA potent monoclonal antibody such as MAD0004J08, capable of neutralising multiple variants of concern of SARS-CoV-2 rapidly and long lastingly when given as a single intramuscular injection. The antibody, presently tested in a phase 2-3 efficacy trial, can be a major advancement in the prophylaxis and clinical management of COVID-19, because of its broad spectrum, ease of use in non-hospital settings and economic sustainability.

Background: Acute kidney injury (AKI) after transcatheter aortic valve implantation (TAVI) is frequent and associated with adverse outcomes and mortality; to date, in such setting of patients there is no consistent evidence that either low-osmolar contrast media (LOCM) or iso‐osmolar contrast medium (IOCM) are superior to the other in terms of renal safety. Methods: 697 consecutive patients not in hemodialysis treatment who underwent TAVI (327 males, mean age 81.01 ± 5.75 years, mean european system for cardiac operative risk evaluation II 6.17 ± 0.23%) were enrolled. According to osmolality of the different iodinated CM, the population was divided in 2 groups: IOCM (n = 370) and LOCM group (n = 327). Preoperatively, 40.54% of patients in IOCM vs 39.14% in LOCM group (p = 0.765) suffered from chronic kidney disease (CKD). Results: The incidence of AKI was significantly lower with IOCM (9.73%) than with LOCM (15.90%; p = 0.02), and such significant difference (p < 0.001) in postprocedural change of renal function parameters persisted at discharge too. The incidence of AKI was also significantly lower with IOCM in younger patients, without diabetes, anemia, coronary artery disease history, CKD, chronic or persistent atrial fibrillation, left ventricular ejection fraction ≤35%, and in patients with low operative mortality risk scores, receiving lower amounts of dye (p < 0.05 for all). Importantly, multivariate analysis identified LOCM administration as an independent risk factor for both AKI (p = 0.006) and 1-year mortality (p = 0.001). Conclusions: The use of IOCM have a favorable impact on renal function with respect to LOCM, but it should be considered especially for TAVI patients at lower AKI risk.

Coronavirus disease 2019 (COVID-19) outbreak is a public health emergency of international concern due to a highly pathogenic human coronavirus (HCoV), actually named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite much emerging data about the epidemiological association between cardiovascular diseases and COVID-19, little is still known atrial fibrillation (AF) and its optimal management in this clinical contest. The aim of our review is to describe the pharmacological interactions between cardiovascular drugs more commonly used in AF management and experimental COVID-19 therapies, based on European (EU) and Unites States (US) summaries of product characteristics.

Using baseline data from a community-collaborative cohort of women living with HIV in Canada, we assessed the prevalence and correlates of help-seeking among 1,057 women who reported experiencing violence in adulthood (≥16 years). After violence, 447 (42%) sought help, while 610 (58%) did not. Frequently accessed supports included health care providers ( n = 313, 70%), family/friends ( n = 244, 55%), and non-HIV community organizations ( n = 235, 53%). All accessed supports were perceived as helpful. Independent correlates of help-seeking included reporting a previous mental health diagnosis, a history of injection drug use, experiencing childhood violence, and experiencing sexism. We discuss considerations for better supporting women who experience violence.

Diabetes mellitus is a lifelong disease in which either the pancreas fails to produce insulin or the produced amount is insufficient to control blood sugar levels. A way to tackle this malfunctioning is to devise an artificial pancreas endowed with a personalized control algorithm able to regulate the insulin dosage. A crucial step in realizing such a device is to effectively forecast future glucose levels starting from past glucose values, the knowledge of the food intake, and of the basal and the injected insulin. The increasing availability of medical diabetes data sets is providing unprecedented opportunities to identify correlations inside these data even harnessing innovative investigation methods, such as deep learning. As an alternative to the deep learning methods successfully used as forecasting models, we exploit a neuroevolution algorithm to model and predict future personalized blood glucose levels. The discovered subjective regression model can represent the control algorithm of an artificial pancreas. This model is assessed through experiments performed on a real-world database containing data of six patients suffering from Type 1 diabetes. To further evaluate the effectiveness of the predictions derived from the proposed approach, the results are also compared against those obtained by other state-of-the-art recently proposed methods.

Objective To keep patients healthy and safe during the pandemic, payers and the federal government temporarily relaxed restrictions, expanded the eligible provider list for providing telehealth services, and developed a reimbursement structure. Physical therapists were uniquely challenged during the pandemic, requiring a reassessment of techniques and strategies in order to best support patients. The purpose of this case report is to describe a musculoskeletal institution’s experience with implementing telehealth physical therapy. Methods Previous telehealth experience enabled the infrastructure of a wide-scale adoption across institutions to respond to the COVID-19 pandemic. However, to fill in training gaps for Hospital for Special Surgery (HSS) outpatient physical therapists, HSS Rehabilitation developed a robust education and implementation program. This training was influenced by clinician and patient surveys as well as the development of a published HSS Rehabilitation telehealth guide. Prior to performing telehealth physical therapist visits, clinicians were required to complete all training material to ensure comfortability and confidence. Results The adoption of telehealth among clinicians was born out of necessaity; however, the speed with which HSS Rehabilitation pivoted was critical to avoid lapses in care. In a 4-week period after the New York City shelter in-place orders, 173 therapists were trained and performing virtual visits. HSS Rehabilitation determined telehealth physical therapy had quicker access to care, similar patient satisifaction, and increased geographical outreach compared with in-person care. Conclusion The transition to telehealth physical therapy included a multi-step process that provided clinician training, established protocols and guidelines, and obtained a better understanding of the patient experience. Telehealth physical therapy has shown early benefits such as improving patient access to care and better continuity of care for traveling patients. Even after the current public health emergency, there is a place for high-value telehealth physical therapy in caring for patients with musculoskeletal conditions.

Soccer broadcast video understanding has been drawing a lot of attention in recent years within data scientists and industrial companies. This is mainly due to the lucrative potential unlocked by effective deep learning techniques developed in the field of computer vision. In this work, we focus on the topic of camera calibration and on its current limitations for the scientific community. More precisely, we tackle the absence of a large-scale calibration dataset and of a public calibration network trained on such a dataset. Specifically, we distill a powerful commercial calibration tool in a recent neural network architecture on the large-scale SoccerNet dataset, composed of untrimmed broadcast videos of 500 soccer games. We further release our distilled network, and leverage it to provide 3 ways of representing the calibration results along with player localization. Finally, we exploit those representations within the current best architecture for the action spotting task of SoccerNet-v2, and achieve new state-of-the-art performances., Paper accepted at the CVsports workshop at CVPR2021

A comprehensive description of baseline characteristics, procedural features and outcomes related to the development of acute kidney injury (AKI) after transcatheter aortic valve implantation (TAVI) is reported in our research paper (Impact of contrast medium osmolality on the risk of acute kidney injury after transcatheter aortic valve implantation: insights from the Magna Graecia TAVI registry. Int J Cardiol. DOI: 10.1016/j.ijcard.2020.12.049). Three Italian heart centers were involved in this multicentric observational study. Between March 2011 and February 2019, a total of 888 patients underwent TAVI; according to the inclusion and exclusion criteria, 697 patients were included in the post-hoc analysis. This Data in Brief paper aims to report demographic, clinical, laboratory, echocardiographic, intraprocedural, periprocedural, postprocedural and follow-up data; all of them were prospectively collected from each patient's health record, whereas the analysis was performed retrospectively. Targets of this data analysis were: 1) to evaluate the impact of contrast medium (CM) osmolality on TAVI-related AKI; 2) to identify the most of risk factors involved in the development of such complication, and consequently in the occurrence of 1-year mortality; 3) to estimate the impact of CM osmolality on AKI in specific patient subgroups.

The management of diabetes is a very complex task, hence devising automatic procedures able to predict the glycemic level can represent a significant step towards the building of an artificial pancreas capable of providing the needed amounts of insulin boluses.This paper presents a Grammatical Evolution-based algorithm aiming at extrapolating a regression model able to estimate the blood glucose level in future instants of time through interstitial glucose measurements. The hypothesis is that the amounts of carbohydrates assumed, of basal insulin levels and of those administered with boluses are known. Experiments, performed on a real-world database made up of five patients suffering from Type 1 diabetes, are shown in terms of Clark Error Grid analysis. To evaluate the effectiveness of the predictions derived from the proposed approach, the results obtained are compared against those obtained by other state-of-the-art evolutionary-based methods very recently proposed.

Understanding broadcast videos is a challenging task in computer vision, as it requires generic reasoning capabilities to appreciate the content offered by the video editing. In this work, we propose SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production. Specifically, we release around 300k annotations within SoccerNet's 500 untrimmed broadcast soccer videos. We extend current tasks in the realm of soccer to include action spotting, camera shot segmentation with boundary detection, and we define a novel replay grounding task. For each task, we provide and discuss benchmark results, reproducible with our open-source adapted implementations of the most relevant works in the field. SoccerNet-v2 is presented to the broader research community to help push computer vision closer to automatic solutions for more general video understanding and production purposes., Paper accepted for the CVsports workshop at CVPR2021. This document contains 8 pages + references + supplementary material

Aims Surgical endarterectomy is the therapy of choice for atherosclerotic common femoral artery (CFA) obstruction. Recently, some large single-centre series have shown encouraging results for the percutaneous treatment of CFA obstructions. The purpose of this study was to evaluate the safety, feasibility, and one-year efficacy of the endovascular treatment of CFA obstructions with combined use of directional atherectomy (DA) and a paclitaxel-coated balloon (DCB). Methods and results Between January 2012 and July 2014, 30 consecutive patients with severely calcified obstructions of the common femoral artery were treated in our centre using DA followed by DCB dilatation. Provisional stenting was allowed in the case of a suboptimal result. Twenty cases (66%) were isolated CFA interventions, whereas five (17%) and five (17%) also involved inflow and outflow vessels, respectively. Chronic total CFA occlusions (CTO) were recanalised in six cases (20%). Procedural success was achieved in all cases; stenting was needed in three cases (10%). At one year, restenosis and target lesion revascularisation were observed in two of 30 (6.6%) and one of 30 (3.3%) patients, respectively. The secondary patency rate was 96.7%. Conclusions This single-centre prospective study suggests that the combined use of DA and DCB is a safe and effective alternative to surgery, a treatment option for common femoral artery lesions and provides encouraging results in this setting.

This review aims at summarizing essential aspects of epidemiology and pathophysiology of hyponatremia in chronic heart failure (CHF), to set the ground for a practical as well as evidence-based approach to treatment. As a guide through the discussion of the available evidence, a clinical case of hyponatremia associated with CHF is presented. For this case, the severe neurological signs at presentation justified an emergency treatment with hypertonic saline plus furosemide, as indicated. Subsequently, as the neurological emergency began to subside, the reversion of the trend toward hyponatremia overcorrection was realized by continuous infusion of hypotonic solutions, and administration of desmopressin, so as to prevent the very feared risk of an osmotic demyelination syndrome. This very disabling complication of the hyponatremia correction is then briefly outlined. Moreover, the possible advantages related to systematic correction of the hyponatremia that occurs in the course of CHF are mentioned. Additionally, the case of tolvaptan, a vasopressin receptor antagonist, is concisely presented in order to underline the different views that have led to different norms in Europe with respect to the USA or Japan as regards the use of this drug as a therapeutic resource against the hyponatremia.

Background: A two-incision technique, in association with inter-muscular positioning of the subcutaneous defibrillator (S-ICD), is now the most frequently adopted implantation approach in Europe. Ultrasound-guided serratus anterior plane block (SAPB) has been proposed to provide anesthesia/analgesia during S-ICD implantation. Objective: We performed a case-control analysis in which a standardized SAPB approach was compared with the typical local anesthesia and sedation approach. Methods: Ninety-one consecutive patients underwent implantation of an S-ICD with the SAPB approach for anesthesia/analgesia at 10 centers. The control group consisted of 55 consecutive patients who underwent S-ICD implantation with a standard local approach. Results: The mean procedure duration was 59 ± 15 minutes in the SAPB group and 76 ± 23 minutes in the control group (P

Background There are still many pendent issues about the effective evaluation of cardiac resynchronization therapy impact on functional mitral regurgitation. In order to reduce the intrinsic difficulties of quantification of functional mitral regurgitation itself, an automatic quantification of real-time three-dimensional full-volume color Doppler transthoracic echocardiography was proposed as a new, rapid, and accurate method for the assessment of functional mitral regurgitation severity. Recent studies suggested that images of left ventricle flow by echo-particle imaging velocimetry could be a useful marker of synchrony. Echo-particle imaging velocimetry has shown that regional anomalies of synchrony/synergy of the left ventricle are related to the alteration, reduction, or suppression of the physiological intracavitary pressure gradients. Case summary We describe a case in which the two technologies are used in combination during acute echocardiographic optimization of left pacing vector in a 63-year-old man, Caucasian, who showed worsening heart failure symptoms a few days after an implant, and the effect of the device’s optimization at 6-month follow-up. Discussion The degree of realignment of hemodynamic forces, with quantitative analysis of the orientation of blood flow momentum (φ), can represent improvement of fluid dynamics synchrony of the left ventricle, and explain, with a new deterministic parameter, the effects of cardiac resynchronization therapy on functional mitral regurgitation. Real-time three-dimensional color flow Doppler quantification is feasible and accurate for measurement of mitral inflow, left ventricular outflow stroke volumes, and functional mitral regurgitation severity. Conclusion This clinical case offers an innovative and accurate approach for acute echocardiographic optimization of left pacing vector. It shows clinical utility of combined three-dimensional full-volume color Doppler transthoracic echocardiography/echo-particle imaging velocimetry assessment to increase response to cardiac resynchronization therapy, in terms of reduction of functional mitral regurgitation, improving fluid dynamics synchrony of the left ventricle. Electronic supplementary material The online version of this article (10.1186/s13256-019-2048-1) contains supplementary material, which is available to authorized users.

Semantic background subtraction SBS has been shown to improve the performance of most background subtraction algorithms by combining them with semantic information, derived from a semantic segmentation network. However, SBS requires high-quality semantic segmentation masks for all frames, which are slow to compute. In addition, most state-of-the-art background subtraction algorithms are not real-time, which makes them unsuitable for real-world applications. In this paper, we present a novel background subtraction algorithm called Real-Time Semantic Background Subtraction (denoted RT-SBS) which extends SBS for real-time constrained applications while keeping similar performances. RT-SBS effectively combines a real-time background subtraction algorithm with high-quality semantic information which can be provided at a slower pace, independently for each pixel. We show that RT-SBS coupled with ViBe sets a new state of the art for real-time background subtraction algorithms and even competes with the non real-time state-of-the-art ones. Note that we provide python CPU and GPU implementations of RT-SBS at https://github.com/cioppaanthony/rt-sbs., Comment: Accepted and Published at ICIP 2020

Recent advances in human motion sensing technologies and machine learning have enhanced the potential of AI to simulate artificial agents exhibiting human-like movements. Human movements are typically explored via experimental recordings with the aim of establishing relationships between neural and mechanical activities. A recent trend in AI research shows that AI algorithms work remarkably well when combined with sufficient computing resources and data. One common criticism is that all of these methods are gradient-based, which involves a gradient approximation, thus suffering of the well-known vanishing gradient problem. In this paper, the goal is to build an ANN-based controller that enables an agent to walk in a human-like way. In particular, the proposed methodology is based on a new approach to Neuroevolution based on NeuroEvolution of Augmenting Topologies (NEAT). The original algorithm has been endowed with a different type of selection-reproduction mechanism and a modified management of the population, with the aim to improve the performance and to reduce the computational effort. Experiments have evidenced the effectiveness of the proposed approach and have highlighted the interdependence among three key aspects: the reward framework, the Evolutionary Algorithm chosen and the hyper-parameters' configuration. As a consequence, none of the above aspects can be ignored and their balancing is crucial for achieving suitable results and good performance.

Monitoring the occupancy of public sports facilities is essential to assess their use and to motivate their construction in new places. In the case of a football field, the area to cover is large, thus several regular cameras should be used, which makes the setup expensive and complex. As an alternative, we developed a system that detects players from a unique cheap and wide-angle fisheye camera assisted by a single narrow-angle thermal camera. In this work, we train a network in a knowledge distillation approach in which the student and the teacher have different modalities and a different view of the same scene. In particular, we design a custom data augmentation combined with a motion detection algorithm to handle the training in the region of the fisheye camera not covered by the thermal one. We show that our solution is effective in detecting players on the whole field filmed by the fisheye camera. We evaluate it quantitatively and qualitatively in the case of an online distillation, where the student detects players in real time while being continuously adapted to the latest video conditions., Accepted for the CVSports workshop of CVPR 2020 ; 8 pages + references

Funding Acknowledgements No Funding OnBehalf RHYTHM DETECT study group Background A two-incision technique, in association with inter-muscular positioning of the subcutaneous defibrillator (S-ICD), is now the most frequently adopted implantation approach in Europe. Ultrasound-guided serratus anterior plane block (SAPB) has been proposed in order to provide anesthesia/analgesia during S-ICD implantation. Objective We performed a case-control analysis in which a standardized SAPB approach was compared with the typical local anesthesia and sedation approach. Methods 91 consecutive patients underwent implantation of an S-ICD with the SAPB approach for anesthesia/analgesia at 10 centers. The control group consisted of 55 consecutive patients who underwent S-ICD implantation with standard local approach. Results The mean procedure duration was 59 ± 15min in the SAPB group and 76 ± 23min in the control group (p Conclusions SAPB is feasible and effective in providing anesthesia/analgesia during S-ICD implantation. The procedures were successfully accomplished and no complications occurred in either group. However, SAPB was associated with lower pain levels, enabling the need for sedation to be reduced and more patients to remain awake. Moreover, it resulted in shorter procedure durations.

The method of Semantic Background Subtraction (SBS), which combines semantic segmentation and background subtraction, has recently emerged for the task of segmenting moving objects in video sequences. While SBS has been shown to improve background subtraction, a major difficulty is that it combines two streams generated at different frame rates. This results in SBS operating at the slowest frame rate of the two streams, usually being the one of the semantic segmentation algorithm. We present a method, referred to as &ldquo, Asynchronous Semantic Background Subtraction&ldquo, (ASBS), able to combine a semantic segmentation algorithm with any background subtraction algorithm asynchronously. It achieves performances close to that of SBS while operating at the fastest possible frame rate, being the one of the background subtraction algorithm. Our method consists in analyzing the temporal evolution of pixel features to possibly replicate the decisions previously enforced by semantics when no semantic information is computed. We showcase ASBS with several background subtraction algorithms and also add a feedback mechanism that feeds the background model of the background subtraction algorithm to upgrade its updating strategy and, consequently, enhance the decision. Experiments show that we systematically improve the performance, even when the semantic stream has a much slower frame rate than the frame rate of the background subtraction algorithm. In addition, we establish that, with the help of ASBS, a real-time background subtraction algorithm, such as ViBe, stays real time and competes with some of the best non-real-time unsupervised background subtraction algorithms such as SuBSENSE.

Women living with HIV (WLWH) are over-represented in corrections in Canada, yet little is known about women’s experiences post-release. We used CHIWOS cross-sectional data from WLWH to estimate associations between social determinants of health and HIV-related care outcomes among WLWH with recent (within past year) or ever (before past year) incarceration experience. Lifetime incarceration prevalence was 36.9% (6.5% recent; 30.4% ever), with significant differences by province of residence (British Columbia: 10% recent; 52% ever; Ontario: 5%; 24%; Quebec: 6%; 22%; p < 0.001). In adjusted multinomial logistic regression analyses, compared with never incarcerated, recent incarceration was associated with Indigenous ancestry, lower annual income (< $20,000 CAD), unstable housing, current sex work, injection drug use (IDU), and sub-optimal antiretroviral therapy (ART) adherence, while ever incarceration was associated with current sex work, IDU, and experiencing adulthood violence. Our findings have implications regarding supports needed by WLWH in the post-release period, including ART adherence and achieving health and social goals.

The aim of this study is to assess the morbidity and mortality related to cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) in patients with colo-rectal carcinomatosis. A retrospective multi-institutional study from seven Italian Centers was performed. One hundred and seventy-two patients, submitted to cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) to treat carcinomatosis of colorectal origin, were recorded. Postoperative morbidity was evaluated in accordance with the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) v4.03. Post-operative mortality was evaluated as patients’ death within 60 days from surgical procedures. Predictors of morbidity were evaluated with univariate and multivariate analyses. Post-operative morbidity occurred in 83 patients (48.3%): grades 1–2 in 29 cases (16.9%), and grades 3–4 in 54 (31.4%). Mortality occurred in four cases (2.3%). Number of anastomoses (OR 1.45; 95% CI 1.05–2.00; p = 0.024), number of blood transfusions (OR 1.31; 95% CI 1.11–1.54; p = 0.001) and chemotherapy regimen [Oxaliplatin (OX): OR 2.87; 95% CI 1.22–6.75; p = 0.015] remained, in multivariate analysis, in a statistically significant correlation with overall morbidity. The only variable that was proven to have statistically significant correlation with 3–4 morbidity was the number of blood transfusions (OR 1.25; 95% CI 1.07–1.46; p = 0.005). Morbidity and mortality do not preclude the use of CRS plus HIPEC in the treatment of peritoneal carcinomatosis of colorectal origin.

Time-optimal control of robotic manipulators along specified paths is a well-known problem in robotics. It concerns the minimization of the trajectory-tracking time subject to a constrained path and actuator torque limits. Calculus of variations reveals that time-optimal control is of bang-bang type, meaning that at least one actuator is in saturation for every point on the path. Unfortunately, this rule is broken at singular points, where the enforcement of the maximal and/or minimal torque at the bounding actuator would cause the violation of the path constraint. At these particular points, and, sometimes, at critical ones too, the selection of the torques is cumbersome and may introduce jitters in the control references. In this paper, the time-optimal control is addressed in the phase plane with a genetic approach. Results of calculus of variations are ignored and bang-bang control is re-found for the most of the trajectory, while in the neighborhoods of singular points, torques are automatically selected in order to minimize the trajectory-tracking time. Compared to other techniques, the problem is solved directly, without intermediate steps requiring, for example, the explicit computation of the switching points and the management of torques at critical points. The algorithm is validated in simulation on a canonical 2R planar robot in order to ease the comparison with previous works.

Machine Learning (ML) approaches are vastly used for supporting humans in decision-making processes. However, the poor explainability associated to their behavior hampers their application in fields were the impact of the decision is critical, as it is the case for medical application, since physicians cannot simply use the predictions of the model but they must trust the results it provides. This work focuses on the automatic detection of Parkinson’s disease (PD), whose impact on both the individual’s quality of life and social well-being is constantly increasing with the aging of the population. To this end, we propose an explainable approach based on Genetic Programming, called Grammar Evolution (GE). This technique uses context-free grammar to describe the language of the programs to be generated and evolved. In this case, the generated programs are the explicit classification rules for the diagnosis of the subjects. The results of the experiments obtained on the publicly available HandPD data set show GE’s high expressive power and performance comparable to those of several ML models that have been proposed in the literature.

Custode, L. L., Tecce, C. L., Bakurov, I., Castelli, M., Cioppa, A. D., & Vanneschi, L. (2020). A Greedy Iterative Layered Framework for Training Feed Forward Neural Networks. In P. A. Castillo, J. L. Jiménez Laredo, & F. Fernández de Vega (Eds.), Applications of Evolutionary Computation - 23rd European Conference, EvoApplications 2020, Held as Part of EvoStar 2020, Proceedings (pp. 513-529). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12104 LNCS). Springer. https://doi.org/10.1007/978-3-030-43722-0_33 In recent years neuroevolution has become a dynamic and rapidly growing research field. Interest in this discipline is motivated by the need to create ad-hoc networks, the topology and parameters of which are optimized, according to the particular problem at hand. Although neuroevolution-based techniques can contribute fundamentally to improving the performance of artificial neural networks (ANNs), they present a drawback, related to the massive amount of computational resources needed. This paper proposes a novel population-based framework, aimed at finding the optimal set of synaptic weights for ANNs. The proposed method partitions the weights of a given network and, using an optimization heuristic, trains one layer at each step while “freezing” the remaining weights. In the experimental study, particle swarm optimization (PSO) was used as the underlying optimizer within the framework and its performance was compared against the standard training (i.e., training that considers the whole set of weights) of the network with PSO and the backward propagation of the errors (backpropagation). Results show that the subsequent training of sub-spaces reduces training time, achieves better generalizability, and leads to the exhibition of smaller variance in the architectural aspects of the network. authorsversion published

Background: Associations between HIV-related stigma and reduced antiretroviral therapy (ART) adherence are widely established, yet the mechanisms accounting for this relationship are underexplored. There has been less attention to HIV-related stigma and its associations with ART initiation and current ART use. We examined pathways from HIV-related stigma to ART initiation, current ART use, and ART adherence among women living with HIV in Canada. Methods: We used baseline survey data from a national cohort of women living with HIV in Canada (n = 1425). Structural equation modeling using weighted least squares estimation methods was conducted to test the direct effects of HIV-related stigma dimensions (personalized, negative self-image, and public attitudes) on ART initiation, current ART use, and 90% ART adherence, and indirect effects through depression and HIV disclosure concerns, adjusting for sociodemographic factors. Results: In the final model, the direct paths from personalized stigma to ART initiation (β = −0.104, P < 0.05) and current ART use (β = −0.142, P < 0.01), and negative self-image to ART initiation (β = −0.113, P < 0.01) were significant, accounting for the mediation effects of depression and HIV disclosure concerns. Depression mediated the pathways from personalized stigma to ART adherence, and negative self-image to current ART use and ART adherence. Final model fit indices suggest that the model fit the data well [χ2(25) = 90.251, P < 0.001; comparative fit index = 0.945; root-mean-square error of approximation = 0.044]. Conclusions: HIV-related stigma is associated with reduced likelihood of ART initiation and current ART use, and suboptimal ART adherence. To optimize the benefit of ART among women living with HIV, interventions should reduce HIV-related stigma and address depression.

Background Women comprise nearly one-quarter of people living with human immunodeficiency virus (HIV) in Canada. Compared with men, women living with HIV experience inequities in HIV care and health outcomes, prompting a need for gendered and tailored approaches to HIV care. Method Peer and academic researchers from the Canadian HIV Women's Sexual and Reproductive Health Cohort Study conducted focus groups to understand women's experience of seeking care, with the purpose of identifying key characteristics that define a women-centered approach to HIV care. Eleven focus groups were conducted with 77 women living with HIV across Quebec, Ontario, and British Columbia, Canada. Results Women envisioned three central characteristics of women-centered HIV care, including i) coordinated and integrated services that address both HIV and women's health care priorities, and protect against exclusion from care due to HIV-related stigma, ii) care that recognizes and responds to structural barriers that limit women's access to care, such as violence, poverty, motherhood, HIV-related stigma, and challenges to safe disclosure, and iii) care that fosters peer support and peer leadership in its design and delivery to honor the diversity of women's experiences, overcome women's isolation, and prioritize women's ownership over the decisions that affect their lives. Conclusion Despite advances in HIV treatment and care, the current care landscape is inadequate to meet women's comprehensive care needs. A women-centered approach to HIV care, as envisioned by women living with HIV, is central to guiding policy and practice to improve care and outcomes for women living with HIV in Canada.

The roofs are a complex part of the architectural constructive system: they represent the attack on the sky, which has the role to mitigate the effects of weathering and to crown the building. However, they are also an unusual landscape that look from above, cover and protect their city. This paper presents an analysis of some interesting technological design works, conducted with methodological needs-performance approach. It is a part of wider research on energy and environmentally responsible retrofits of constructive characters of the architectural heritage in the Mediterranean area, conducted as member of the Inter-University Centre of Bio-ecological Architecture and Technological Innovation for the Environment (ABITA) and addressed to knowledge the local constructive traditions and bio-ecological potentiality of this existing building heritage.

AIMS Many studies have analysed the occurrence of acute kidney injury (AKI) after percutaneous coronary intervention (PCI) but there are limited data relating to AKI risk in patients undergoing carotid artery stenting (CAS). The aim of this study was to determine the incidence and predictors of AKI in patients undergoing proximal protected CAS. METHODS AND RESULTS We analysed 456 patients undergoing proximal protected CAS. A binomial multivariate logistic model was developed including patients' clinical and angiographic/procedural characteristics. AKI (defined as an sCr increase ≥0.3 mg/dl or ≥1.5-fold sCr increase from baseline or more than 50% increase from baseline, within 48 hours post procedure) occurred in 155 patients (34%). AKI patients were more frequently affected by hypertension, diabetes, dyslipidaemia and anaemia, and presented lower renal function at baseline. Higher contrast volume to creatinine clearance ratio (2.40±1.44 vs. 2.08±1.15; p=0.01), lower post-procedural mean arterial pressure (MAP) (94.3±17.7 vs. 99.6±18.5 mmHg; p=0.003) and a more frequent post-procedural systolic pressure drop (∆SBP >50 mmHg) (23.9% vs. 14.3%, p=0.01) were observed in the AKI group of patients. At multivariate analysis, independent predictors of AKI were ∆SBP >50 mmHg, diabetes mellitus and dyslipidaemia. CONCLUSIONS AKI can occur quite frequently after proximal protected CAS and is related to clinical and procedural features. These data should be confirmed in larger registries or randomised trials.

The femoropopliteal artery is one of the commonest sites of involvement in peripheral artery disease (PAD) leading to intermittent claudication and/or critical limb ischemia. Endovascular therapy for superficial femoral artery (SFA) disease has been recognized as a safe and efficient therapy and is recommended by current guidelines as the first-line approach. Although the widespread use of new-generation, self-expanding, nitinol stents in SFA stenosis has reduced the shortcomings associated with plain old balloon angioplasty (POBA), lumen renarrowing at the stented (in-stent restenosis - ISR) level still represents a relevant clinical problem, because of higher risk of recurrent ISR, occlusion and surgical revascularization compared to de-novo lesions. In this setting, different treatment options are available and drug-coated balloons (DCBs) have shown good results in terms of safety and effectiveness. In this review we examine the results of different trials exploring the outcome of using DCBs for the treatment of SFA ISR. The available data demonstrate that SFA ISR can be safely treated with percutaneous transluminal angioplasty with a DCB, with a reduction in recurrent restenosis and target lesion revascularization (TLR) at least at 1 year after POBA. The consistent and positive results of different registries and randomized trials support the use of DCB to reduce SFA ISR recurrence.

Semantic segmentation can be regarded as a useful tool for global scene understanding in many areas, including sports, but has inherent difficulties, such as the need for pixel-wise annotated training data and the absence of well-performing real-time universal algorithms. To alleviate these issues, we sacrifice universality by developing a general method, named ARTHuS, that produces adaptive real-time match-specific networks for human segmentation in sports videos, without requiring any manual annotation. This is done by an online knowledge distillation process, in which a fast student network is trained to mimic the output of an existing slow but effective universal teacher network, while being periodically updated to adjust to the latest play conditions. As a result, ARTHuS allows to build highly effective real-time human segmentation networks that evolve through the match and that sometimes outperform their teacher. The usefulness of producing adaptive match-specific networks and their excellent performances are demonstrated quantitatively and qualitatively for soccer and basketball matches.

Early disease identification through non-invasive and automatic techniques has gathered increasing interest by the scientific community in the last decades. In this context, Parkinsons Disease (PD) has received particular attention in that it is a severe and progressive neurodegenerative disease and, therefore, early diagnosis would provide more prompt and effective intervention strategies. This, in turn, would successfully influence the life expectancy of the patients. However, the acceptance of computer-based diagnosis by doctors is hampered by the black-box approach implemented by the most performing systems, such as Artificial Neural Networks and Support Vector Machines, which do not explicit the rules adopted by the system. In this context, we propose a Cartesian Genetic Programming, aimed at automatically identify PD through the analysis of handwriting performed by PD patients and healthy controls. The use of such approach is particularly interesting in that it allows to infer explicit models of classification and, at same time, to automatically identify a suitable subset of features relevant for a correct diagnosis. The approach has been evaluated on the features extracted from the handwriting samples contained in the publicly available PaHaW dataset. Experimental results show that our approach compares favorably with state-of-the-art methods and, more importantly, provides an explicit model of the classification criteria.

Deep Neural Networks (DNNs) may be very effective for the classification over highly-sized data sets, especially in the medical domain, where the recognition of the occurrence of a specific event related to a disease is of high importance. Unfortunately, DNNs suffer from the drawback that a good set of values for their configuration hyper-parameters must be found. Currently, this is done through the use of either trial-and-error methods or sampling-based ones. In this paper we propose a new approach to find the most suitable structure for a DNN used for a classification problem in terms of achievement of the highest classification accuracy. This approach is based on a distributed version of Differential Evolution (DE), a variety of an Evolutionary Algorithm. To evaluate the approach, in this paper we investigate this issue with reference to Obstructive Sleep Apnea (OSA). OSA is an important medical problem consisting of episodes taking place during night in which a subject stops breathing due to a constriction of the upper airways. This deteriorates the quality of life and may have dangerous, and even lethal, consequences on both short and long term. An accurate classification is a very crucial step for the OSA treatment, because understanding automatically that a subject is experiencing such an episode may be decisive if prompt medical action is needed. In our experiments, classification takes place on a data set in which each item contains the values of 17 Heart Rate Variability parameters, extracted from ElectroCardiography signals, and the annotation of OSA events. We have extracted this data set from the real-world Sleep Heart Health Study database. The results obtained by the distributed DE are compared against those of the Grid Search as well as against those achieved by 13 well-known classification tools. The use of a distributed DE version turns out to be very effective in automatically obtaining DNN structures with higher classification accuracy with respect to Grid Search (72.95% versus 72.61%), and allows saving a high amount of time (three hours as opposed to 65 h and 40 min). Moreover, the proposed method outperforms in terms of higher accuracy all the other classifiers investigated, as it is evidenced also by statistical analysis. Numerically, the runner-up, i.e., JRip, achieves as its best value 72.01% and 71.50% on average over 25 runs, both values being lower than 72.95% and 72.74% obtained by our dDE.

We address the problem of designing a machine learning tool for the automatic diagnosis of Parkinson’s disease that is capable of providing an explanation of its behavior in terms that are easy to understand by clinicians. For this purpose, we consider as machine learning tool the decision tree, because it provides the decision criteria in terms of both the features which are actually useful for the purpose among the available ones and how their values are used to reach the final decision, thus favouring its acceptance by clinicians. On the other side, we consider the random forest and the support vector machine, which are among the top performing machine learning tool that have been proposed in the literature, but whose decision criteria are hidden into their internal structures. We have evaluated the effectiveness of different approaches on a public dataset, and the results show that the system based on the decision tree achieves comparable or better results that state-of-the-art solutions, being the only one able to provide a plain description of the decision criteria it adopts in terms of the observed features and their values.

In video understanding, action spotting consists in temporally localizing human-induced events annotated with single timestamps. In this paper, we propose a novel loss function that specifically considers the temporal context naturally present around each action, rather than focusing on the single annotated frame to spot. We benchmark our loss on a large dataset of soccer videos, SoccerNet, and achieve an improvement of 12.8% over the baseline. We show the generalization capability of our loss for generic activity proposals and detection on ActivityNet, by spotting the beginning and the end of each activity. Furthermore, we provide an extended ablation study and display challenging cases for action spotting in soccer videos. Finally, we qualitatively illustrate how our loss induces a precise temporal understanding of actions and show how such semantic knowledge can be used for automatic highlights generation., Comment: Accepted for CVPR2020 main conference. This document contains 8 pages + references + supplementary material

Background Through contemporary literature, the optimal strategy to manage coronary chronic total occlusions (CTOs) remains under debate. Objectives The aim of the Italian Registry of Chronic Total Occlusions (IRCTO) was to provide data on prevalence, characteristics, and outcome of CTO patients according to the management strategy. Methods The IRCTO is a prospective real world multicentre registry enrolling patients showing at least one CTO. Clinical and angiographic data were collected independently from the therapeutic strategy [optimal medical therapy (MT), percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG)]; a comparative 1-year clinical followup was performed. Results A total of 1777 patients were enrolled for an overall CTO prevalence of 13.3%. The adopted therapeutic strategies were as follows: MT in 826 patients (46.5%), PCI in 776 patients (43.7%), and CABG in the remaining 175 patients (9.8%). At 1-year follow-up, patients undergoing PCI showed lower rate of major adverse cardiac and cerebrovascular events (MACCE) (2.6% vs. 8.2% and vs. 6.9%; P < 0.001 and P < 0.01) and cardiac death (1.4% vs. 4.7% and vs. 6.3%; P < 0.001 and P < 0.001) in comparison with those treated with MT and CABG, respectively. After propensity scorematching analysis, patients treated with PCI showed lower incidence of cardiac death (1.5 vs. 4.4%; P < 0.001), acute myocardial infarction (1.1 vs. 2.9%; P = 0.03), and re-hospitalization (2.3 vs. 4.4% P = 0.04) in comparison with those managed by MT. Conclusions Our data showed how CTO PCI might significantly improve the survival and decrease MACCE occurrence at 1 year follow-up in comparison with MT and/or CABG.

In the last decades, early disease identification through non-invasive and automatic methodologies has gathered increasing interest from the scientific community. Among others, Parkinson's disease (PD) has received special attention in that it is a severe and progressive neuro-degenerative disease. As a consequence, early diagnosis would provide more effective and prompt care strategies, that cloud successfully influence patients’ life expectancy. However, the most performing systems implement the so called black-box approach, which do not provide explicit rules to reach a decision. This lack of interpretability, has hampered the acceptance of those systems by clinicians and their deployment on the field. In this context, we perform a thorough comparison of different machine learning (ML) techniques, whose classification results are characterized by different levels of interpretability. Such techniques were applied for automatically identify PD patients through the analysis of handwriting and drawing samples. Results analysis shows that white-box approaches, such as Cartesian Genetic Programming and Decision Tree, allow to reach a twofold goal: support the diagnosis of PD and obtain explicit classification models, on which only a subset of features (related to specific tasks) were identified and exploited for classification. Obtained classification models provide important insights for the design of non-invasive, inexpensive and easy to administer diagnostic protocols. Comparison of different ML approaches (in terms of both accuracy and interpretability) has been performed on the features extracted from the handwriting and drawing samples included in the publicly available PaHaW and NewHandPD datasets. The experimental findings show that the Cartesian Genetic Programming outperforms the white-box methods in accuracy and the black-box ones in interpretability.

Background: Several studies have compared the use of phosphodiesterase-5 (PDE5) inhibitors sildenafil or udenafil with the placebo in patients suffering from pulmonary hypertension (PH) due to left chronic heart failure (CHF), corresponding to group 2 (PH due to left heart disease) of the PH classification (according to 2015 ESC/ERS guidelines for the diagnosis and treatment of PH). The results of the use of PDE5 inhibitors in the PH due to left heart disease were inconsistent and heterogeneous. Therefore, we carried out a meta-analysis to assess the effect of PDE5 inhibitors in this clinical setting, i.e., patients with left CHF. Methods: A systematic search was conducted using the PubMed and Embase electronic archives. Studies had to be prospective randomized controlled trials (RCTs). In each of the RCTs admitted to meta-analysis, a comparison was made between a group of CHF patients taking a PDE5 inhibitor and a second group assigned a placebo. Studies were incorporated in the meta-analysis provided that they had sufficient information about two or more of the following clinical, ergospirometric or hemodynamic outcomes: the composite of all-cause death and hospitalization, adverse events, peak VO 2 , 6-min walking distance (6MWD), left ventricular ejection fraction (LVEF), E/e’ ratio, mean pulmonary arterial pressure (mPAP), pulmonary arterial systolic pressure (PASP), and pulmonary vascular resistance (PVR). Results: Fourteen studies enrolling a total of 928 patients were incorporated in the meta-analysis. Among them,13 were RCTs and one was a subgroup analysis. Among patients with CHF with reduced left ventricular ejection fraction (HFREF, n = 555), a significant benefit was conferred by PDE5 inhibitors against the risk of the composite endpoint of death and hospitalizations (odds ratio (OR): 0.28; 95% confidence interval (CI): 0.10 - 0.74; P = 0.03). Furthermore, among HFREF patients, PDE5 inhibitors were associated with a significant improvement in peak VO 2 (difference in means (MD): 3.76 mL/min/kg; 95% CI: 3.27 - 4.25) as well as in 6MWD (MD: 22.7 m; 95% CI: 8.19 - 37.21) and LVEF (MD: 4.30%; 95% CI: 2.18% to 6.42%). For patients with HFREF, PDE5 inhibitors caused a non-significant reduction in mPAP, while PASP was significantly reduced (MD: -11.52 mm Hg; 95% CI: -15.56 to -7.49; P < 0.001). By contrast, in the RCTs of patients with CHF with preserved left ventricular ejection fraction (HFpEF, n = 373), no benefit ensued from PDE5 inhibitor use regarding all of the investigated clinical, ergospirometric or hemodynamic endpoints. Conclusions: PDE5 inhibitors improved clinical outcomes, exercise capacity and pulmonary hemodynamics in patients with HFREF, but not in HFpEF. However, considering the relatively small size of the HFpEF subset enrolled so far in the RCTs that explored the PDE5 inhibitor effects, further research in this field is undoubtedly warranted. J Clin Med Res. 2017;9(6):488-498 doi: https://doi.org/10.14740/jocmr3008w

Platypnea-orthodeoxia syndrome (POS) is a rare disorder characterized by the emergence of a right-to-left shunt at the intracardiac or intrapulmonary level. The clinical picture is distinguished by shortness of breath that worsens on standing due to an accentuation of oxygen desaturation, and instead improves, at least partly, in the recumbent position. In this article we present a brief review of the pathophysiology of POS, as well as its clinical picture, diagnostic assessment, and preferential therapeutic options. Pathophysiological issues that are still not completely understood or much debated are outlined. The currently accepted pathophysiological concepts are presented and a summary of the main diagnostic and therapeutic tools is provided.

Knowledge of the right atrial pressure (RAP) values is critical to ascertain the existence of a state of hemodynamic congestion, irrespective of the possible presence of signs and symptoms of clinical congestion and cardiac overload that can be lacking in some conditions of concealed or clinically misleading cardiac decompensation. In addition, a more reliable estimate of RAP would make it possible to determine more accurately also the systolic pulmonary arterial pressure with the only echocardiographic methods. The authors briefly illustrate some of the criteria that have been implemented to obtain a non-invasive RAP estimate, some of which have been approved by current guidelines and others are still awaiting official endorsement from the Scientific Societies of Cardiology. There is a representation of the sometimes opposing views of researchers who have studied the problem, and the prospects for development of new diagnostic criteria are outlined, in particular those derived from the matched use of two- and three-dimensional echocardiographic parameters.

Automatic interpretation of sports games is a major challenge, especially when these sports feature complex players organizations and game phases. This paper describes a bottom-up approach based on the extraction of semantic features from the video stream of the main camera in the particular case of soccer using scene-specific techniques. In our approach, all the features, ranging from the pixel level to the game event level, have a semantic meaning. First, we design our own scene-specific deep learning semantic segmentation network and hue histogram analysis to extract pixel-level semantics for the field, players, and lines. These pixel-level semantics are then processed to compute interpretative semantic features which represent characteristics of the game in the video stream that are exploited to interpret soccer. For example, they correspond to how players are distributed in the image or the part of the field that is filmed. Finally, we show how these interpretative semantic features can be used to set up and train a semantic-based decision tree classifier for major game events with a restricted amount of training data. The main advantages of our semantic approach are that it only requires the video feed of the main camera to extract the semantic features, with no need for camera calibration, field homography, player tracking, or ball position estimation. While the automatic interpretation of sports games remains challenging, our approach allows us to achieve promising results for the semantic feature extraction and for the classification between major soccer game events such as attack, goal or goal opportunity, defense, and middle game.

INTRODUCTION Recent evidence from relatively small randomized controlled trials would seem to support a useful role of ranolazine for the prevention and treatment of atrial fibrillation (AF). The present study is aimed at providing information about the possible beneficial anti-arrhythmic properties of ranolazine. In particular, the meta-analysis carried out in this study focuses on the application of ranolazine to prophylaxis and treatment of atrial fibrillation. EVIDENCE ACQUISITION Both methods randomized controlled trials (RCTs) and non-randomized observational studies concerning the effects of ranolazine on AF were included in the meta-analysis. In each of the considered studies, a comparison was made between a group of patients taking ranolazine and a second group treated instead with another antiarrhythmic therapy, or assigned to placebo. Efficacy outcomes were the risk of new-onset AF, the probability of conversion to sinus rhythm of patients with recent occurrence (≤48 h) of AF and the time to conversion to sinus rhythm. Safety endpoints were death, adverse events, QTc prolongation and hypotension. EVIDENCE SYNTHESIS Ten studies (8 RCTs and 2 nonrandomized observational studies) were gathered on the whole. Ranolazine was effective in preventing the occurrence of AF when compared to controls (RR=0.60; 95% CI: 0.43-0.83; P=0.002). Subgroup analysis showed a more pronounced preventive effect of ranolazine against AF in the postoperative setting of coronary artery bypass grafting (CABG) surgery (RR=0.39; 95% CI: 0.18-0.83; P=0.02) when compared to non-postoperative AF (RR=0.76; 95% CI: 0.63-0.92; P=0.04). Ranolazine enhanced the chances of successful cardioversion when added to intravenous amiodarone compared to amiodarone alone (RR 1.18; 95% CI: 1.05-1.33; P=0.004) and significantly decreased the time to cardioversion (SMD= -10.35 h; 95% CI: -18.13 hours to -2.57 hours; P

Background The most common clinical presentation of peripheral artery disease (PAD) comprises intermittent claudication (IC), but about one third of patients will progress to critical limb ischemia (CLI), characterized by rest pain and/or tissue loss, which is the most severe limb manifestation of PAD. Paclitaxel-coated balloons are well established for the endovascular treatment of femoropopliteal lesions in patients with IC and CLI. This ongoing multicenter registry study is exploring the role of the Lutonix® 014 drug-coated balloon (DCB) in the treatment of below-the-knee (BTK) arteries and CLI. Methods Three hundred fourteen (314) patients were enrolled from 26 sites and 12 countries. The real-world patients represent those undergoing intervention for BTK arteries with the Lutonix® 014 DCB. The study had both, primary safety and primary efficacy endpoints. The primary safety endpoint was freedom at 30 days from BTK major adverse limb event (MALE) + perioperative death (POD). Primary efficacy was freedom from clinically driven target lesion reintervention (fTLR) at 6 months. Additional secondary endpoints related to safety were reported. Results The interim 6 months' results showed freedom from MALE and POD at 30 days of 98.6% and at 6 months (180 days) of 96.0%. Primary efficacy of fTLR at 6 months (180 days) was 87.9%. Safety related secondary endpoints at 6 months (180 days) showed freedom from all of the following: all cause death of 91.2%, above ankle amputation 97.1%, reintervention for thrombosis 95.2%, reintervention for distal embolization 100.0%, and target vessel revascularization of 88.0%. There were no unexpected device or drug related events reported. Conclusions The interim 6-month outcomes demonstrate the safety and efficacy of the Lutonix® 014 DCB for the treatment of BTK arteries.

Deep Neural Networks are being more and more widely used to perform several tasks over highly-sized datasets, one of them being classification. Finding good configurations for Deep Neural Network structures is a very important problem in general, and particularly in the medical domain. Currently, either trial-and-error methodologies or sampling-based ones are considered. This paper describes some preliminary steps towards effectively facing this task. The first step consists in the use of Differential Evolution, a kind of an Evolutionary Algorithm. The second lies in using a parallelized version in order to reduce the turnaround time. The preliminary results obtained here show that this approach can be useful in easily obtaining structures that allow increases in the network accuracy with respect to those provided by humans.