SEMdag: Fast learning of Directed Acyclic Graphs via node or layer ordering.

A Directed Acyclic Graph (DAG) offers an easy approach to define causal structures among gathered nodes: causal linkages are represented by arrows between the variables, leading from cause to effect. Recently, industry and academics have paid close attention to DAG structure learning from observable data, and many techniques have been put out to address the problem. We provide a two-step approach, named SEMdag(), that can be used to quickly learn high-dimensional linear SEMs.

SEMbap: Bow-free covariance search and data de-correlation.

Large-scale studies of gene expression are commonly influenced by biological and technical sources of expression variation, including batch effects, sample characteristics, and environmental impacts. Learning the causal relationships between observable variables may be challenging in the presence of unobserved confounders. Furthermore, many high-dimensional regression techniques may perform worse.

Predictors of Care Home Admission and Survival Rate in Patients With Syndromes Associated With Frontotemporal Lobar Degeneration in Europe.

Background And Objectives: Data on care home admission and survival rates of patients with syndromes associated with frontotemporal lobar degeneration (FTLD) are limited. However, their estimation is essential to plan trials and assess the efficacy of intervention. Population-based registers provide unique samples for this estimate.

Statin use and long-term risk of recurrent intracerebral haemorrhage: the MUCH-Italy.

Background: Whether statin use after spontaneous intracerebral haemorrhage (ICH) increases the risk of recurrent ICH is uncertain.

Methods: In the setting of the Multicentric Study on Cerebral Haemorrhage in Italy we followed up a cohort of 30-day ICH survivors, consecutively admitted from January 2002 to July 2014, to assess whether the use of statins after the acute event is associated with recurrent cerebral bleeding.

Results: 1623 patients (mean age, 73.

Does pre-injury anticoagulation make chest tubes any less safe? A nationwide retrospective analysis.

Background: Oral anticoagulation is becoming more common with the aging population, which raises concern for the risk of invasive procedures that can cause bleeding, such as chest tube placement (thoracostomy). With the increase in CT imaging, more pneumothoraces and hemothoraces are being identified. The relative risk of thoracostomy in the presence of anticoagulation is not well-established.

Early seizures and risk of epilepsy and death after intracerebral haemorrhage: The MUCH Italy.

Introduction: It is unclear which patients with non-traumatic (spontaneous) intracerebral haemorrhage (ICH) are at risk of developing acute symptomatic seizures (provoked seizures occurring within the first week after stroke onset; early seizures, ES) and whether ES predispose to the occurrence of remote symptomatic seizures (unprovoked seizures occurring more than 1 week after stroke; post-stroke epilepsy, PSE) and long-term mortality.

Patients And Methods: In the setting of the Multicenter Study on Cerebral Haemorrhage in Italy (MUCH-Italy) we examined the risk of ES and whether they predict the occurrence of PSE and all-cause mortality in a cohort of patients with first-ever spontaneous ICH and no previous history of epilepsy, consecutively hospitalized in 12 Italian neurological centers from 2002 to 2014.

Results: Among 2570 patients (mean age, 73.

Long-Term Risk of Arterial Thrombosis After Intracerebral Hemorrhage: MUCH-Italy.

Background: The identification of patients surviving an acute intracerebral hemorrhage who are at a long-term risk of arterial thrombosis is a poorly defined, crucial issue for clinicians.

Methods: In the setting of the MUCH-Italy (Multicenter Study on Cerebral Haemorrhage in Italy) prospective observational cohort, we enrolled and followed up consecutive 30-day intracerebral hemorrhage survivors to assess the long-term incidence of arterial thrombotic events, to assess the impact of clinical and radiological variables on the risk of these events, and to develop a tool for estimating such a risk at the individual level. Primary end point was a composite of ischemic stroke, myocardial infarction, or other arterial thrombotic events.

Cortico-spinal tDCS in amyotrophic lateral sclerosis: A randomized, double-blind, sham-controlled trial followed by an open-label phase.

Background: Amyotrophic lateral sclerosis (ALS) is a progressive disease for which no curative treatment is currently available.

Objective: This study aimed to investigate whether cortico-spinal transcranial direct current stimulation (tDCS) could mitigate symptoms in ALS patients via a randomized, double-blind, sham-controlled trial, followed by an open-label phase.

Methods: Thirty-one participants were randomized into two groups for the initial controlled phase.

Survival in Incident Cases with Frontotemporal Lobar Degeneration: A Registry-Based Study.

Population-based registries represent a unique sample to estimate survival. The aim of the present study was to assess survival rates and predictors of outcome in incidental frontotemporal lobar degeneration (FTLD). Incident cases with FTLD, included between January 1, 2017 to December 31, 2017, have been followed for five years.

SEMtree: tree-based structure learning methods with structural equation models.

Motivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the identification of functional modules in PPI networks that show striking changes in molecular activity or phenotypic signatures becomes of particular interest to reveal process-specific information that is correlated with cellular or disease states. This requires both the identification of network nodes with reliability scores and the availability of an efficient technique to locate the network regions with the highest scores. In the literature, a number of heuristic methods have been suggested.

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations.

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.

Differential impact of the COVID-19 pandemic on primary care utilization related to common mental disorders in four European countries: A retrospective observational study.

Background: The COVID-19 pandemic is commonly believed to have increased common mental disorders (CMD, i.e., depression and anxiety), either directly due to COVID-19 contractions (death of near ones or residual conditions), or indirectly by increasing stress, economic uncertainty, and disruptions in daily life resulting from containment measure.

SEMgraph: an R package for causal network inference of high-throughput data with structural equation models.

Motivation: With the advent of high-throughput sequencing in molecular biology and medicine, the need for scalable statistical solutions for modeling complex biological systems has become of critical importance. The increasing number of platforms and possible experimental scenarios raised the problem of integrating large amounts of new heterogeneous data and current knowledge, to test novel hypotheses and improve our comprehension of physiological processes and diseases.

Results: Combining network analysis and causal inference within the framework of structural equation modeling (SEM), we developed the R package SEMgraph.

SEMgsa: topology-based pathway enrichment analysis with structural equation models.

Background: Pathway enrichment analysis is extensively used in high-throughput experimental studies to gain insight into the functional roles of pre-defined subsets of genes, proteins and metabolites. Methods that leverages information on the topology of the underlying pathways outperform simpler methods that only consider pathway membership, leading to improved performance. Among all the proposed software tools, there's the need to combine high statistical power together with a user-friendly framework, making it difficult to choose the best method for a particular experimental environment.

Bayesian time-varying autoregressive models of COVID-19 epidemics.

The COVID-19 pandemic has highlighted the importance of reliable statistical models which, based on the available data, can provide accurate forecasts and impact analysis of alternative policy measures. Here we propose Bayesian time-dependent Poisson autoregressive models that include time-varying coefficients to estimate the effect of policy covariates on disease counts. The model is applied to the observed series of new positive cases in Italy and in the United States.

Implementation of an integrative coping and resiliency program for nurses.

Purpose: To improve resiliency and reduce burnout in nurses through implementation of the Healing Pathways program (University of Maryland School of Medicine, Baltimore). Aims of this study include assessment of feasibility and acceptability and to explore changes in stress, coping, burnout, and mindfulness.

Design: A single-group, pre-, posttest design of an 8-week program in which participants attended weekly sessions that included Reiki, yoga, and meditation.

Qualitative and quantitative evaluation of a pilot integrative coping and resiliency program for healthcare professionals.

Stress, fatigue, and burnout are common maladies among healthcare employees. To address this problem, a holistic integrative self-care program for healthcare practitioners was designed, implemented, and evaluated. A total of 84 participants, recruited via presentations, flyers, and word of mouth, completed the 8-week program.

VAC (Vacuum Assisted Closure) treatment in Fournier's gangrene: personal experience and literature review.

Introduction: Fournier's gangrene (FG) is a rapidly developing necrotizing fasciitis that originates in genital and perineal region. The mortality rate is high and requires prompt diagnosis, antibiotic treatment and extensive necrosectomy with derivative colostomy. Vacuum Assisted Closure (VAC) is a wound care system of paramount importance in the treatment of complex wounds, including the perineum.