Christiansensimonsen1132

Background/Purpose Globally, anaemia is a severe public health condition affecting over 24% of the world's population. Children under five years old and pregnant women are the most vulnerable to this disease. This scoping review aimed to evaluate studies that used classical statistical regression methods on nationally representative health survey data to identify the individual socioeconomic, demographic and contextual risk factors associated with developing anaemia among children under five years of age in sub-Saharan Africa (SSA). Methods/Design The reporting pattern followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The following databases were searched MEDLINE, EMBASE (OVID platform), Web of Science, PUBMED, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Scopus, Cochrane library, African Journal of online (AJOL), Google Scholar and Measure DHS. Results The review identified 20 relevant studies and the risk factors for anaemia were classified as child-related, parental/household-related and community- or area-related factors. The risk factors for anaemia identified included age, birth order, sex, comorbidities (such as fever, diarrhoea and acute respiratory infection), malnutrition or stunting, maternal education, maternal age, mother's anaemia status, household wealth and place of residence. Conclusion The outcome of this review is of significant value for health policy and planners to enable them to make informed decision that will correct any imbalances in anaemia across socioeconomic, demographic and contextual characteristics, with the view of making efficient distributions of health interventions.Background Endoscopic submucosal dissection (ESD) for gastric cancer is increasingly performed worldwide due to its efficacy and safety. This study aimed to assess the evidence of the impact of early vs. delayed feeding after ESD on quality of care, which remains to be fully determined. Methods Electronic databases (PubMed, the Cochrane Central Register of Controlled Trials, EMBASE) and the trial registries (the World Health Organization International Clinical Trials Platform Search Portal and ClinicalTrials.gov) were searched for studies performed prior to September 2020. Study selection, data abstraction, and quality assessment were independently performed using the Grading of Recommendations Assessment, Development, and Evaluation approach. Self-rated satisfaction and hospital stay were chiefly analyzed. Results Two randomized controlled trials (239 patients) were included. The early and delayed post-ESD feeding groups had similar rates of post-ESD bleeding (risk ratio 1.90, 95% CI 0.42 to 8.63; I2 = 0%). Early post-ESD feeding resulted in increased patients' satisfaction in comparison to delayed post-ESD feeding (standard mean difference (MD) 0.54, 95% CI 0.27 to 0.81; I2 = 0%) and reduced the length of hospital stay (MD -0.83, 95% CI -1.01 to -0.65; I2 = 0%). Conclusion Early post-ESD feeding was associated with increased patients' satisfaction and reduced hospital stay in comparison to delayed feeding, while the rate of complications did not differ to a statistically significant extent. As we must acknowledge the limited number of reviewed studies, various trials regarding the quality of care are further needed to determine the benefits of early feeding after ESD.Metformin is the most commonly used glucose-lowering therapy (GLT) worldwide and remains the first-line therapy for newly diagnosed individuals with type 2 diabetes (T2D) in management algorithms and guidelines after the UK Prospective Diabetes Study (UKPDS) showed cardiovascular mortality benefits in the overweight population using metformin. However, the improved Major Adverse Cardiovascular Events (MACE) realised in some of the recent large cardiovascular outcomes trials (CVOTs) using sodium-glucose co-transporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) have challenged metformin's position as a first-line agent in the management of T2D. Many experts now advocate revising the existing treatment algorithms to target atherosclerotic cardiovascular disease (ASCVD) and improving glycaemic control as a secondary aim. In this review article, we will revisit the major cardiovascular outcome data for metformin and include a critique of the UKPDS data. We then review additional factors that might be pertinent to metformin's status as a first-line agent and finally answer key questions when considering metformin's role in the modern-day management of T2D.Nearly one-quarter of all cancer deaths worldwide are due to lung cancer, making this disease the leading cause of cancer death among both men and women. The most important determinant of survival in lung cancer is the disease stage at diagnosis, thus developing an effective screening method for early diagnosis has been a long-term goal in lung cancer care. In the last decade, and based on the results of large clinical trials, lung cancer screening programs using low-dose computer tomography (LDCT) in high-risk individuals have been implemented in some clinical settings, however, this method has various limitations, especially a high false-positive rate which eventually results in a number of unnecessary diagnostic and therapeutic interventions among the screened subjects. By using complex algorithms and software, artificial intelligence (AI) is capable to emulate human cognition in the analysis, interpretation, and comprehension of complicated data and currently, it is being successfully applied in various healthcare settings. Taking advantage of the ability of AI to quantify information from images, and its superior capability in recognizing complex patterns in images compared to humans, AI has the potential to aid clinicians in the interpretation of LDCT images obtained in the setting of lung cancer screening. In the last decade, several AI models aimed to improve lung cancer detection have been reported. Some algorithms performed equal or even outperformed experienced radiologists in distinguishing benign from malign lung nodules and some of those models improved diagnostic accuracy and decreased the false-positive rate. BGB 15025 purchase Here, we discuss recent publications in which AI algorithms are utilized to assess chest computer tomography (CT) scans imaging obtaining in the setting of lung cancer screening.