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Sun Y.,National Healthcare Services | Lee S.H.,National Neuroscience Institute NNI | Heng B.H.,National Healthcare Services | Chin V.S.,National Healthcare Services
BMC Neurology | Year: 2013

Background: Stroke is the 4th leading cause of death and 1st leading cause of disability in Singapore. However the information on long-term post stroke outcomes for Singaporean patients was limited. This study aimed to investigate the post stroke outcomes of 5-year survival and rehospitalization due to stroke recurrence for hemorrhagic and ischemic stroke patients in Singapore. The outcomes were stratified by age, ethnic group, gender and stroke types. The causes of death and stroke recurrence were also explored in the study.Methods: A multi-site retrospective cohort study. Patients admitted for stroke at any of the three hospitals in the National Healthcare Group of Singapore were included in the study. All study patients were followed up to 5 years. Kaplan-Meier was applied to study the time to first event, death or rehospitalization due to stroke recurrence. Cox proportional hazard model was applied to study the time to death with adjustment for stroke type, age, sex, ethnic group, and admission year. Cumulative incidence model with competing risk was applied for comparing the risks of rehospitalization due to stroke recurrence with death as the competing risk.Results: Totally 12,559 stroke patients were included in the study. Among them, 59.3% survived for 5 years; 18.4% were rehospitalized due to stroke recurrence in 5 years. The risk of stroke recurrence and mortality increased with age in all stroke types. Gender, ethnic group and admitting year were not significantly associated with the risk of mortality or stroke recurrence in hemorrhagic stroke. Male or Malay patient had higher risk of stroke recurrence and mortality in ischemic stroke. Hemorrhagic stroke had higher early mortality while ischemic stroke had higher recurrence and late mortality. The top cause of death among died stroke patients was cerebrovascular diseases, followed by pneumonia and ischemic heart diseases. The recurrent stroke was most likely to be the same type as the initial stroke among rehospitalized stroke patients.Conclusions: Five year post-stroke survival and rehospitalization due to stroke recurrence as well as their associations with patient demographics were studied for different stroke types in Singapore. Specific preventive strategies are needed to target the high risk groups to improve their long-term outcomes after acute stroke. © 2013 Sun et al.; licensee BioMed Central Ltd. Source

Feng M.,Institute for Infocomm Research | Zhang Z.,Institute for Infocomm Research | Zhang F.,Institute for Infocomm Research | Ge Y.,Institute for Infocomm Research | And 7 more authors.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2011

Close monitoring and timely treatment are extremely crucial in Neuro Intensive/Critical Care Units (NICUs) to prevent patients from secondary brain damages. However, the current clinical practice is labor-intensive, prone to human errors and ineffective. To address this, we developed an integrated and intelligent system, namely iSyNCC, to enhance the effectiveness of patient monitoring and clinical decision makings in NICUs. The requirements of the system were investigated through interviews and discussions with neurosurgeons, neuroclinicians and nurses. Based on the summarized requirements, a modular 2-tier system is developed. iSyNCC integrates and stores crucial patient information ranging from demographic details, clinical & treatment records to continuous physiological monitoring data. iSyNCC enables remote and centralized patient monitoring and provides computational intelligence to facilitate clinical decision makings. © 2011 IEEE. Source

Zhang F.,Institute for Infocomm Research | Feng M.,Institute for Infocomm Research | Pan S.J.,Institute for Infocomm Research | Loy L.Y.,Institute for Infocomm Research | And 6 more authors.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2011

Although the future mean of intracranial pressure (ICP) is of critical concern of many clinicians for timely medical treatment, the problem of forecasting the future ICP mean has not been addressed yet. In this paper, we present a nonlinear autoregressive with exogenous input artificial neural network based mean forecast algorithm (ANN NARX-MFA) to predict the ICP mean of the future windows based on features extracted from past windows and segmented sub-windows. We compare its performance with nonlinear autoregressive artificial neural network algorithm (ANN NAR) without features extracted from window segmentation. Experimental results showed that, ANN NARX-MFA algorithm outperforms ANN NAR algorithm in prediction accuracy, because additional features extracted from finer segmented sub-windows help to catch the subtle changes of ICP trends. This verifies the effectiveness of decomposing the whole window into sub-windows to obtain features in making predictions on future windows. Based on the forecast of ICP mean, medical treatments can be planned in advance to control ICP elevation, in order to maximize recovery and optimize outcome. © 2011 IEEE. Source

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