Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010
TL;DR: The results for 1990 and 2010 supersede all previously published Global Burden of Disease results and highlight the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account.
About: This article is published in The Lancet.The article was published on 2012-12-15. It has received 6861 citations till now. The article focuses on the topics: Disease burden & Disability-adjusted life year.
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TL;DR: In this paper, the authors introduce a new framework to guide potential evolution of the building stock in the next century, based on greenhouse gas emissions as the common thread to investigate the potential implications of new design paradigms, innovative operational strategies, and disruptive technologies.
65 citations
TL;DR: The mechanism study shows that the lowering of blood glucose level in diabetic rats by feeding RS is regulated through promoting glycogen synthesis and inhibiting gluconeogenesis, and the increased lipid metabolism is modulated through promoting lipid oxidation and cholesterol homeostasis.
65 citations
TL;DR: A large R‐fMRI dataset with 1434 participants from five centers in China is included to highlight reproducible patterns of functional alterations in MDD and relevant influencing factors, which provides crucial guidance for future neuroimaging studies of this disorder.
65 citations
TL;DR: This review focuses on unsupervised aspects of machine learning, and how these aspects could be applied to precision neurology to improve patient outcomes.
Abstract: Artificial intelligence (AI) has influenced all aspects of human life and neurology is no exception to this growing trend. The aim of this paper is to guide medical practitioners on the relevant aspects of artificial intelligence, i.e., machine learning, and deep learning, to review the development of technological advancement equipped with AI, and to elucidate how machine learning can revolutionize the management of neurological diseases. This review focuses on unsupervised aspects of machine learning, and how these aspects could be applied to precision neurology to improve patient outcomes. We have mentioned various forms of available AI, prior research, outcomes, benefits and limitations of AI, effective accessibility and future of AI, keeping the current burden of neurological disorders in mind. The smart device system to monitor tremors and to recognize its phenotypes for better outcomes of deep brain stimulation, applications evaluating fine motor functions, AI integrated electroencephalogram learning to diagnose epilepsy and psychological non-epileptic seizure, predict outcome of seizure surgeries, recognize patterns of autonomic instability to prevent sudden unexpected death in epilepsy (SUDEP), identify the pattern of complex algorithm in neuroimaging classifying cognitive impairment, differentiating and classifying concussion phenotypes, smartwatches monitoring atrial fibrillation to prevent strokes, and prediction of prognosis in dementia are unique examples of experimental utilizations of AI in the field of neurology. Though there are obvious limitations of AI, the general consensus among several nationwide studies is that this new technology has the ability to improve the prognosis of neurological disorders and as a result should become a staple in the medical community. AI not only helps to analyze medical data in disease prevention, diagnosis, patient monitoring, and development of new protocols, but can also assist clinicians in dealing with voluminous data in a more accurate and efficient manner.
65 citations
TL;DR: The identified evidence suggests that combined physical and psychological treatments, medical yoga, information and education programmes, spinal manipulation and acupuncture are likely to be cost-effective options for LBP.
Abstract: Low back pain (LBP) is a major health problem, having a substantial effect on peoples’ quality of life and placing a significant economic burden on healthcare systems and, more broadly, societies. Many interventions to alleviate LBP are available but their cost effectiveness is unclear. To identify, document and appraise studies reporting on the cost effectiveness of non-invasive and non-pharmacological treatment options for LBP. Relevant studies were identified through systematic searches in bibliographic databases (EMBASE, MEDLINE, PsycINFO, Cochrane Library, CINAHL and the National Health Service Economic Evaluation Database), ‘similar article’ searches and reference list scanning. Study selection was carried out by three assessors, independently. Study quality was assessed using the Consensus on Health Economic Criteria checklist. Data were extracted using customized extraction forms. Thirty-three studies were identified. Study interventions were categorised as: (1) combined physical exercise and psychological therapy, (2) physical exercise therapy only, (3) information and education, and (4) manual therapy. Interventions assessed within each category varied in terms of their components and delivery. In general, combined physical and psychological treatments, information and education interventions, and manual therapies appeared to be cost effective when compared with the study-specific comparators. There is inconsistent evidence around the cost effectiveness of physical exercise programmes as a whole, with yoga, but not group exercise, being cost effective. The identified evidence suggests that combined physical and psychological treatments, medical yoga, information and education programmes, spinal manipulation and acupuncture are likely to be cost-effective options for LBP.
65 citations
References
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TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.
11,809 citations
Book•
01 Jan 1996
TL;DR: This is the first in a planned series of 10 volumes that will attempt to "summarize epidemiological knowledge about all major conditions and most risk factors" and use historical trends in main determinants to project mortality and disease burden forward to 2020.
Abstract: This is the first in a planned series of 10 volumes that will attempt to "summarize epidemiological knowledge about all major conditions and most risk factors;...generate assessments of numbers of deaths by cause that are consistent with the total numbers of deaths by age sex and region provided by demographers;...provide methodologies for and assessments of aggregate disease burden that combine--into the Disability-Adjusted Life Year or DALY measure--burden from premature mortality with that from living with disability; and...use historical trends in main determinants to project mortality and disease burden forward to 2020." This first volume includes chapters summarizing results from the project as a whole. (EXCERPT)
7,154 citations
TL;DR: Prevalence and severity of health loss were weakly correlated and age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010, but population growth and ageing have increased YLD numbers and crude rates over the past two decades.
7,021 citations
TL;DR: The three leading contributors to the burden of disease are communicable and perinatal disorders affecting children, and the substantial burdens of neuropsychiatric disorders and injuries are under-recognised.
4,425 citations