Publications by authors named "Sassi R"

Background: Electrical remodeling has been linked to the progression and recurrence of atrial fibrillation (AF) after catheter ablation (CA). Substrate mapping based solely on a voltage amplitude electrogram (EGM) does not provide a comprehensive understanding of the left atrial (LA) disease. The aim of this study is to assess left atrial spatial entropy (LASE) from voltage maps routinely obtained during AF ablation to further characterize the LA substrate.

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Article Synopsis
  • This systematic review investigates predictors of intradialytic hypotension (IDH) in critically ill patients receiving kidney replacement therapy (KRT) for acute kidney injury (AKI).
  • It analyzed data from 8 studies with 2873 patients, finding that machine learning models, particularly Extreme Gradient Boosting Machine (XGB) and deep neural networks (DNN), had the highest predictive accuracy compared to traditional indicators.
  • The study emphasizes the need for combining predictive models and clinical indicators to enhance prediction of IDH and highlights that further validation in different healthcare settings is necessary.
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Body composition is now recognized to have a major impact on health and disease. Imaging enables its analysis in an objective and quantitative way through diverse techniques such as dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging, and ultrasonography. This review article first surveys the methodological aspects underpinning the use of these modalities to assess body composition, highlighting their strengths and limitations as well as the set of parameters that they measure and their clinical relevance.

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Purpose: This scoping review synthesizes the characteristics and outcomes of recent evidence-based treatments and services for youth with nonmedical opioid use/opioid use disorder in the context of the ongoing opioid crisis in Canada and the United States.

Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Extension for Scoping Reviews guidelines, empirical health databases were searched for literature describing treatments or health-related services for nonmedical opioid use/opioid use disorder among youth (ages 12-25). Two independent reviewers conducted study screening, selection, and data extraction.

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Background: Depression, anxiety, and stress disorders have significant and widespread impacts worldwide, affecting millions of individuals and their communities. According to the World Health Organization, depression impacts the daily lives of more than 300 million people, making it one of the most important diseases globally. Treatment for these mental disorders (MD) typically involves medication and psychotherapies, but also incorporates technological resources like Artificial Intelligence (AI) to indicate personalized therapies and care.

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Sample entropy embeds time series into m-dimensional spaces and estimates entropy based on the distances between points in these spaces. However, when samples can be considered as missing or invalid, defining distance in the embedding space becomes problematic. Preprocessing techniques, such as deletion or interpolation, can be employed as a solution, producing time series without missing or invalid values.

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Article Synopsis
  • Conventional chemotherapy is still the main treatment for various cancers, despite advancements in the field, but it often leads to acute kidney injury (AKI), a serious side effect.
  • Nephrotoxic effects are commonly linked to platinum-based drugs, but other chemotherapy agents, including antimetabolites and alkylating agents, can also cause kidney damage.
  • The article reviews the causes, risks, and management strategies for AKI during chemotherapy, and discusses prevention methods, though avoiding kidney injury remains difficult due to multiple contributing factors.
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Connolly, DR, Stolp, S, Gualtieri, A, Ferrari Bravo, D, Sassi, R, Rampinini, E, and Coutts, AJ. How do young soccer players train? A 5-year analysis of weekly training load and its variability between age groups in an elite youth academy. J Strength Cond Res 38(8): e423-e429, 2024-The aim of this study was to quantify the session rating of perceived exertion (sRPE), duration, and training load accrued across typical training weeks undertaken by youth soccer players.

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Due to its potential use as a carbon-free energy resource with minimal environmental and climate impacts, natural hydrogen (H) produced by subsurface geochemical processes is today the target of intensive research. In H exploration practices, bacteria are thought to swiftly consume H and, therefore, small near-surface concentrations of H, even orders of 10 ppmv in soils, are considered a signal of active migration of geological gas, potentially revealing underground resources. Here, we document an extraordinary case of a widespread occurrence of H (up to 1 vol%), together with elevated concentrations of CH and CO (up to 51 and 27 vol%, respectively), in aerated meadow soils along Italian Alps valleys.

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Atrial fibrillation (AF), the most prevalent cardiac rhythm disorder, significantly increases hospitalization and health risks. Reverting from AF to sinus rhythm (SR) often requires intensive interventions. This study presents a deep-learning model capable of predicting the transition from SR to AF on average 30.

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Background: Nutrition exerts a fundamental role in the prevention of obesity (OB). The aim of this study was to assess the extent to which well recognized risk factors for early OB can be associated to overweight (OW) or OB under a standardized nutritional approach and surveillance in toddlers.

Methods: The eligible population was represented by 676 toddlers aged 24-36 months, assigned to 18 primary care pediatricians trained on nutritional issues who shared a standardized nutritional approach.

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The objective of the current study was to explore the correlation between repeated sprint sets (RSS) ability and several physical attributes, including maximum sprint speed, maximal aerobic speed, maximal anaerobic speed, aerobic capacity, and explosive strength. Moreover, the aim was to assess the suitability of RSS as a comprehensive evaluation tool for physical qualities and to determine which physical field tests most accurately predict RSS in elite young male soccer players. A total of thirty-two young elite male soccer players (mean age 14.

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Osteogenesis imperfecta (OI) is a rare phenotypically and genetically heterogeneous group of inherited skeletal dysplasias. The hallmark features of OI include bone fragility and susceptibility to fractures, bone deformity, and diminished growth, along with a plethora of associated secondary features (both skeletal and extraskeletal). The diagnosis of OI is currently made on clinical grounds and may be confirmed by genetic testing.

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Background: The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet mental health needs. Accurate ED revisit prediction could aid early intervention and ensure efficient healthcare resource allocation.

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Radon is a radioactive gas and a major source of ionizing radiation exposure for humans. Consequently, it can pose serious health threats when it accumulates in confined environments. In Europe, recent legislation has been adopted to address radon exposure in dwellings; this law establishes national reference levels and guidelines for defining Radon Priority Areas (RPAs).

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Numerous field and laboratory studies have been conducted to investigate the relationship between radon variation and seismic events, as well as the complex link between radon emission and rock deformation mechanisms. However, a clear understanding of this correspondence and systematic observations of these phenomena are still lacking, and recent experimental studies have yet to yield conclusive results. In this study, we investigate the possible relationships between radon migration dynamics and rock deformation at the micro-scale through laboratory experiments using the SHIVA apparatus under shear stress-controlled conditions and simultaneous high-resolution radon measurements.

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Dysregulation is a combination of emotion, behavior, and attention problems associated with lifelong psychiatric comorbidity. There is evidence for the stability of dysregulation from childhood to adulthood, which would be more fully characterized by determining the likely stability from infancy to childhood. Early origins of dysregulation can further be validated and contextualized in association with environmental and biological factors, such as prenatal stress and polygenic risk scores (PRS) for overlapping child psychiatric problems.

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In utero, the developing brain is highly susceptible to the environment. For example, adverse maternal experiences during the prenatal period are associated with outcomes such as altered neurodevelopment and emotion dysregulation. Yet, the underlying biological mechanisms remain unclear.

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AI techniques have recently been put under the spotlight for analyzing electrocardiograms (ECGs). However, the performance of AI-based models relies on the accumulation of large-scale labeled datasets, which is challenging. To increase the performance of AI-based models, data augmentation (DA) strategies have been developed recently.

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Introduction: Environmental perturbations during critical periods can have pervasive, organizational effects on neurodevelopment. To date, the literature examining the long-term impact of early life adversity has largely investigated structural and functional imaging data outcomes independently. However, emerging research points to a relationship between functional connectivity and the brain's underlying structural architecture.

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Background And Objective: Planning the optimal ablation strategy for the treatment of complex atrial tachycardia (CAT) is a time consuming task and is error-prone. Recently, directed network mapping, a technology based on graph theory, proved to efficiently identify CAT based solely on data of clinical interventions. Briefly, a directed network was used to model the atrial electrical propagation and reentrant activities were identified by looking for closed-loop paths in the network.

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Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ).

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