5 research outputs found

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

    Get PDF
    BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

    Komparasi Fitur Seleksi pada Algoritma Support Vector Machine untuk Analisis Sentimen Review

    Full text link
    The main problem in the process sentiment analysis review is how to choose and use the best feature selection to get the maximal result. The accuracy of the use of algorithm in analysis sentiment review also have been an important role in the determination results of the analysis. Analysis of the sentiment is a study computing on an opinion, behavior and emotion of a person to an entity. This research also discussed comparative studies, technique classification and combining method of the feature selection to comparsion result of the people opinion about tourist destination. The classifications technique to analyze sentiment review of the tourist destinations, using support vector machine algorithm (svm) and a model of the features selection will be compared between a particle swarm optimization and genetic algorithm to increase the accuracy classifications of support vector machines algorithm. The measurement of were based on accuracy support vector machines before and after the addition of features. The evaluation uses 10 cross fold validation. While the measurement of accuracy measured by confusion the matrix and a curve roc. The result showed an increase in accuracy support vector machines of 75.33 % to 88.67 %

    Pengolahan Data Pengawai Menggunakan Metode FAST pada PT. Asia Berjaya Mobilindo

    Full text link
    PT. Asia Berjaya Mobilindo merupakan salah satu Perusahaan di Indonesia yang bergerak di bidang penjualan, perawatan serta penjualan suku cadang mobil bermerk Mazda. Pengolahan data pegawai pada PT. Asia Berjaya Mobilindo masih dilakukan secara konvensional dan menimbulkan beberapa kendala bagi pegawai terutama pada saat pengajuan cuti dan penerimaan gaji. Pengajuan cuti yang ditujukan ke manajer HRD dilakukan dengan menggunakan surat cuti dan harus diserahkan secara langsung, adanya keterlambatan dalam pendistribusian slip gaji dan adanya kesalahan dalam perhitungan gaji yang menyebabkan pegawai menerima gaji tidak sesuai dengan yang seharusnya diterima oleh pegawai. Oleh karena itu, diperlukan sistem informasi pengajuan cuti, slip gaji dan rekap absen karyawan yang sesuai dengan PT. Asia Berjaya Mobilindo dengan menggunakan metode Framework for The Application of System Thinking (FAST) dengan diagram Unified Model Language (UML) sehingga sistem yang dibangun mampu menyelesaikan permasalahan pada pengolahan data pegawai pada PT. Asia Berjaya Mobilindo dan memudahkan pegawai dalam mengajukan cuti, melihat slip gaji dan melihat absen

    Implementasi Monitoring Perkembangan Proyek Konstruksi pada Perum Perumnas Jakarta Berbasis Web

    Full text link
    One factor of success in a housing construction project is the monitoring of each division that is interrelated and connected with each other. It would be very inefficient if from each party there was no clear and uncontrolled communication. As with the Jakarta Housing Corporation, currently monitoring the project has not been well integrated. Where information that is intertwined with regional offices is still limited to communication information by telephone, as well as data that is used using documents or archives that can sometimes be lost or forgotten in the storage. Of course this will slow down the project development process, because it is constrained by each of the relevant parties, plus the report must be presented or needed at any time by the director. For this reason, a system that can support the monitoring process is needed so that data can be stored properly and the control of the progress of each project is monitored from the center. One of them is the creation of a web-based system application, with this system all can be done in real time
    corecore