ABSTRACT
Attention deficit hyperactivity disorder (ADHD) is a neurobiological condition that appears during an individual's childhood and may follow her/him for life. The research objective was to understand better how and which computer technologies have been applied to support ADHD diagnosis and treatment. The research used the systematic literature review method: a rigorous, verifiable, and repeatable approach that follows well-defined steps. Six well-known academic data sources have been consulted, including search engines and bibliographic databases, from technology and health care areas. After a rigorous research protocol, 1,239 articles were analyzed. For the diagnosis, the use of machine learning techniques was verified in 61 percent of the articles. Neurofeedback was ranked second with 9.3 percent participation, followed by serious games and eye tracking with 5.6 percent each. For the treatment, neurofeedback was present in 50 percent of the articles, whereas some studies combined both approaches, accounting for 31 percent of the total. Nine percent of the articles reported remote assistance technology, whereas another 9 percent have used virtual reality. By highlighting the leading computer technologies used, their applications, results, and challenges, this literature review breaks ground for further investigations. Moreover, the study highlighted the lack of consensus on ADHD biomarkers. The approaches using machine learning call attention to the probable occurrence of overfitting in several studies, thus demonstrating limitations of this technology on small-sized bases. This research also presented the convergence of evidence from different studies on the persistence of long-term effects of using neurofeedback in treating ADHD.
Subject(s)
Attention Deficit Disorder with Hyperactivity , Neurofeedback , Virtual Reality , Attention Deficit Disorder with Hyperactivity/diagnosis , Attention Deficit Disorder with Hyperactivity/therapy , Child , Computers , Female , Humans , MaleABSTRACT
Este e-book tem como objetivo trazer um compêndio de relatos de experiência relacionados à gestão de saúde do Estado de Goiás. Cada capítulo traz a descrição dos projetos desenvolvidos no âmbito da Secretaria de Estado da Saúde de Goiás, que são vinculados aos objetivos estratégicos do órgão. Estes projetos têm como objetivo fortalecer as ações estratégicas para otimizar o planejamento do Sistema Único de Saúde
This e-book aims to bring a compendium of experience reports related to health management in the State of Goiás. Each chapter brings a description of the projects developed within the scope of the State Department of Health of Goiás, which are linked to the strategic objectives of the agency. These projects aim to strengthen strategic actions to optimize the planning of the Unified Health System
Subject(s)
Health Management , Public Health Administration , State Health Plans , Health Programs and Plans , Social Control Policies , Health Services Administration , Crew Resource Management, Healthcare , Health PolicyABSTRACT
BACKGROUND: Patients with Coronavirus Disease 2019 (COVID-19) may present high risk features during hospitalization, including cardiovascular manifestations. However, less is known about the factors that may further increase the risk of death in these patients. METHODS: We included patients with COVID-19 and high risk features according to clinical and/or laboratory criteria at 21 sites in Brazil from June 10th to October 23rd of 2020. All variables were collected until hospital discharge or in-hospital death. RESULTS: A total of 2546 participants were included (mean age 65 years; 60.3% male). Overall, 70.8% were admitted to intensive care units and 54.2% had elevated troponin levels. In-hospital mortality was 41.7%. An interaction among sex, age and mortality was found (p = 0.007). Younger women presented higher rates of death than men (30.0% vs 22.9%), while older men presented higher rates of death than women (57.6% vs 49.2%). The strongest factors associated with in-hospital mortality were need for mechanical ventilation (odds ratio [OR] 8.2, 95% confidence interval [CI] 5.412.7), elevated C-reactive protein (OR 2.3, 95% CI 1.72.9), cancer (OR 1.8, 95 %CI 1.22.9), and elevated troponin levels (OR 1.8, 95% CI 1.42.3). A risk score was developed for risk assessment of in-hospital mortality. CONCLUSIONS: This cohort showed that patients with COVID-19 and high risk features have an elevated rate of in-hospital mortality with differences according to age and sex. These results highlight unique aspects of this population and might help identifying patients who may benefit from more careful initial surveillance and potential subsequent interventional therapies
Subject(s)
Hospital Mortality , Coronavirus , Risk AssessmentSubject(s)
Hyperlipidemias , Metabolic Diseases , Xanthomatosis , Humans , Hyperlipidemias/complicationsABSTRACT
BACKGROUND: Patients with Coronavirus Disease 2019 (COVID-19) may present high risk features during hospitalization, including cardiovascular manifestations. However, less is known about the factors that may further increase the risk of death in these patients. METHODS: We included patients with COVID-19 and high risk features according to clinical and/or laboratory criteria at 21 sites in Brazil from June 10th to October 23rd of 2020. All variables were collected until hospital discharge or in-hospital death. RESULTS: A total of 2546 participants were included (mean age 65 years; 60.3% male). Overall, 70.8% were admitted to intensive care units and 54.2% had elevated troponin levels. In-hospital mortality was 41.7%. An interaction among sex, age and mortality was found (p = 0.007). Younger women presented higher rates of death than men (30.0% vs 22.9%), while older men presented higher rates of death than women (57.6% vs 49.2%). The strongest factors associated with in-hospital mortality were need for mechanical ventilation (odds ratio [OR] 8.2, 95% confidence interval [CI] 5.4-12.7), elevated C-reactive protein (OR 2.3, 95% CI 1.7-2.9), cancer (OR 1.8, 95 %CI 1.2-2.9), and elevated troponin levels (OR 1.8, 95% CI 1.4-2.3). A risk score was developed for risk assessment of in-hospital mortality. CONCLUSIONS: This cohort showed that patients with COVID-19 and high risk features have an elevated rate of in-hospital mortality with differences according to age and sex. These results highlight unique aspects of this population and might help identifying patients who may benefit from more careful initial surveillance and potential subsequent interventional therapies.
ABSTRACT
BACKGROUND AND AIMS: GPIHBP1 is an accessory protein of lipoprotein lipase (LPL) essential for its functioning. Mutations in the GPIHBP1 gene cause a deficit in the action of LPL, leading to severe hypertriglyceridemia and increased risk for acute pancreatitis. METHODS: We describe twelve patients (nine women) with a novel homozygous mutation in intron 2 of the GPIHBP1 gene. RESULTS: All patients were from the Northeastern region of Brazil and presented the same homozygous variant located in a highly conserved 3' splicing acceptor site of the GPIHBP1 gene. This new variant was named c.182-1G > T, according to HGVS recommendations. We verified this new GPIHBP1 variant's effect by using the Human Splicing Finder (HSF) tool. This mutation changes the GPIHBP1 pre-mRNA processing and possibly causes the skipping of the exon 3 of the GPIHBP1 gene, affecting almost 50% of the cysteine-rich Lys6 GPIHBP1 domain. Patients presented with severe hypertriglyceridemia (2351 mg/dl [885-20600]) and low HDL (18 mg/dl [5-41). Four patients (33%) had a previous history of acute pancreatitis. CONCLUSIONS: We describe a novel GPIHBP1 pathogenic intronic mutation of patients from the Northeast region of Brazil, suggesting the occurrence of a founder effect.