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- W2788409062 abstract "Out-of-hospital cardiac arrest (OHCA) incidence varies greatly between geographic areas. Since survival rates are dramatically lower for OHCAs that have a response time longer than several minutes, areas with a relatively high incidence of OHCA cases may be appropriate targets for community-based resuscitation training. In two large regions in the Netherlands, we (1) identify high- and low-risk districts for OHCA, (2) determine whether these districts remain high- or low-risk over time, (3) find underlying demographic, socio-economic and ethnicity associations that may explain spatial disparities, and (4) explore the current state of resuscitation efforts to identify the most beneficial opportunities for short-term improvement, by focusing on communities at greatest risk. The emphasis is on determining the underlying associations between OHCA incidence and demographic, socio-economic and ethnicity factors at a district level, through the use of machine learning algorithms: Logistic Regression, Support Vector Machine, Artificial Neural Networks, and Adaptive Boosting. We observe considerable spatial disparities across districts in terms of OHCA incidence. Public health campaigns should target districts with a high proportion of low income receivers, recipients of labour disability acts, elderly population, male inhabitants, and a low proportion of married inhabitants. However, districts do not necessarily report similar rates over time." @default.
- W2788409062 created "2018-03-06" @default.
- W2788409062 creator A5014847196 @default.
- W2788409062 date "2018-01-01" @default.
- W2788409062 modified "2023-09-27" @default.
- W2788409062 title "Spatial Analysis of Out-of-Hospital Cardiac Arrest Incidences" @default.
- W2788409062 hasPublicationYear "2018" @default.
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