Access to medicines among asylum seekers, refugees and undocumented migrants across the migratory cycle in Europe: a scoping review.

Introduction: Access to essential medicines is a critical element of health systems and an important measure of their performance. Migrants may face barriers in accessing healthcare, including essential medicines, throughout the migration cycle, which includes the stages of departure from home or residence countries, transit through non-European or European countries, reception and settlement in a country in Europe and deportation. We aim to provide an overview of research and grey literature concerning access to essential medicines for asylum seekers, refugees and undocumented migrants in or heading to Europe (European Union, European Economic Area, Switzerland and the UK).

Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis.

Background: IntraUterine Growth Restriction (IUGR) is a global public health concern and has major implications for neonatal health. The early diagnosis of this condition is crucial for obtaining positive outcomes for the newborn. In recent years Artificial intelligence (AI) and machine learning (ML) techniques are being used to identify risk factors and provide early prediction of IUGR.

Access to medicine among asylum seekers, refugees and undocumented migrants across the migratory cycle: a scoping review protocol.

Introduction: Migration creates new health vulnerabilities and exacerbates pre-existing medical conditions. Migrants often face legal, system-related, administrative, language and financial barriers to healthcare, but little is known about factors that specifically influence migrants' access to medicines and vaccines. This scoping review aims to map existing evidence on access to essential medicines and vaccines among asylum seekers, refugees and undocumented migrants who aim to reach Europe.

Effectiveness of Platform-Based Robot-Assisted Rehabilitation for Musculoskeletal or Neurologic Injuries: A Systematic Review.

During the last ten years the use of robotic-assisted rehabilitation has increased significantly. Compared with traditional care, robotic rehabilitation has several potential advantages. Platform-based robotic rehabilitation can help patients recover from musculoskeletal and neurological conditions.

Development of a Model Care Pathway for Myasthenia Gravis.

Myasthenia Gravis (MG) is a chronic, life-lasting condition that requires high coordination among different professionals and disciplines. The diagnosis of MG is often delayed and sometimes misdiagnosed. The goal of the care pathway (CP) is to add value to healthcare reducing unnecessary variations.

Physical exercise and fall prevention: A systematic review and meta-analysis of experimental studies included in Cochrane reviews.

The aim of this systematic review (SR) and meta-analysis was to assess what type of exercise is associated with fall risk reduction among apparently healthy adults aged 50 and older. We conducted a SR by searching for randomized controlled trials (RCTs) included in Cochrane SRs published until October 2019. Five SRs that compared exercise versus any type of control included 32 RCTs.

Effectiveness and feasibility of smoking counselling: a randomized controlled trial in an Italian emergency department.

Background: 5A's counselling is recommended for screening and treating patients with smoking addiction. The emergency department (ED) setting might be a suitable environment for conducting interventions for smoking cessation. The present study aims to determine the feasibility and effectiveness on smoking cessation of 5A's counselling administered to ED patients by nurses.

Overview on the target population and methods used in care pathway projects: A narrative review.

Background: There is evidence that the efficiency and effectiveness of care processes can be improved in all countries. Care pathways (CPs) are proposed as a method to improve the quality of care by reducing variation. During the last decades, CPs have been intensively used in practice.

Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review.

Artificial Intelligence (AI) and Machine Learning (ML) have expanded their utilization in different fields of medicine. During the SARS-CoV-2 outbreak, AI and ML were also applied for the evaluation and/or implementation of public health interventions aimed to flatten the epidemiological curve. This systematic review aims to evaluate the effectiveness of the use of AI and ML when applied to public health interventions to contain the spread of SARS-CoV-2.

Lymphocyte doubling time in chronic lymphocytic leukemia modern era: a real-life study in 848 unselected patients.

The prognostic significance of lymphocyte doubling time (LDT) in chronic lymphocytic leukemia (CLL) was identified when the biology of the disease was poorly understood and therapy was not effective. We assessed the clinical and biological significance of LDT in 848 CLL patients in a real-life setting and the context of new biomarkers and effective therapy. A short LDT (≤12 months) was enriched for adverse biomarkers.