9 research outputs found

    Determinants and Time Trends for Ischaemic and Haemorrhagic Stroke in a Large Chinese Population

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    <div><p>Background</p><p>The clinical epidemiology of stroke has been widely investigated in Caucasian populations, but the changes over time in the proportion of ischaemic to haemorrhagic strokes is less clear, especially in the Chinese population.</p><p>Aims</p><p>Our objective was to study the determinants and time trends for ischaemic and haemorrhagic stroke, in relation to age, in a large Chinese population cohort.</p><p>Methods</p><p>Using a medical insurance database in the southwest of China from 2001 to 2012, time trends in age-adjusted ischaemic and haemorrhagic stroke incidence and the contributing risk factors associated with age were investigated.</p><p>Results</p><p>Among 425,901 individuals without prior stroke (52.4% male, median age 54), the rate of ischaemic stroke (per 1000 patient-years) decreased between 2002–2007, then remained broadly similar between 2008–2012. The rate of haemorrhagic stroke showed a similar trend, being approximately 1.3–1.9 from 2008–2012. Compared to patients age<65, ischaemic and haemorrhagic stroke incidences (rate, 95% confidential interval, CI) were higher in the elderly population (age <65 versus age ≥65: ischaemic: 3.64, 3.33–4.00, vs 14.33, 14.01–14.60; haemorrhagic: 1.09, 1.00–1.10 vs 2.52,2.40–2.70, respectively, both p<0.001). There were no significant differences in haemorrhagic stroke rates between the elderly and the very elderly population. Ischaemic and haemorrhagic stroke shared similar risk factors (age, hypertension, coronary artery disease (CAD), vascular disease, and diabetes mellitus) (all p<0.05). In subjects age<75 years, CAD (7.17, 4.14–12.37) and diabetes mellitus (3.27, 2.42–4.42) contributed most to the developing of haemorrhagic stroke (all p<0.001). Amongst the very elderly, vascular disease (2.24, 1.49–3.37) was an additional major risk factor for haemorrhagic stroke, together with CAD and diabetes mellitus (all p<0.001).</p><p>Conclusion</p><p>In this large Chinese cohort, there was an increased risk of ischaemic stroke compared to haemorrhagic stroke with ageing. CAD, vascular disease, diabetes mellitus, and hypertension were major contributors to the development of hemorrhagic stroke in the very elderly Chinese population.</p></div

    Multivariate analysis of risk factors for ischaemic and haemorrhagic stroke associated with age strata amongst 425,901 Chinese subjects.

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    <p>Multivariate analysis of risk factors for ischaemic and haemorrhagic stroke associated with age strata amongst 425,901 Chinese subjects.</p

    Leveraging domain expertise in architectural exploration

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    Domain experience is a key driver behind design quality, especially during the early design phases of a product or service. Currently, the only practical way to bring such experience into a project is to directly engage subject matter experts, which means there is the potential for a resource availability bottleneck because the experts are not available when required. Whilst many domain specific tools have attempted to capture expert knowledge in embedded analytics thus allowing less experienced engineers to perform complex tasks, this is certainly not the case for highly complex systems of systems where their architectures can go far beyond what a single human being can comprehend. This paper proposes a new approach to leveraging design expertise in a manner that facilitates architectural exploration and architecture optimization by using pre-defined architecture patterns. In addition, we propose a means to streamline such a process by delineating the knowledge creation process and architectural exploration analytics with the means to facilitate information flow from the former to the latter through a carefuly designed integration framework