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Poisson cluster analysis of cardiac arrest incidence in columbus, ohio

机译：俄亥俄州哥伦布的心脏骤停发生率的泊松聚类分析

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Background. Scarce resources in disease prevention and emergency medical services (EMS) need to be focused on high-risk areas of out-of-hospital cardiac arrest (OHCA). Objective. Cluster analysis using geographic information systems (GISs) was used to find these high-risk areas and test potential predictive variables. Methods. This was a retrospective cohort analysis of EMS-treated adults with OHCAs occurring in Columbus, Ohio, from April 1, 2004, through March 31, 2009. The OHCAs were aggregated to census tracts and incidence rates were calculated based on their adult populations. Poisson cluster analysis determined significant clusters of high-risk census tracts. Both census tract-level and case-level characteristics were tested for association with high-risk areas by multivariate logistic regression. Results. A total of 2,037 eligible OHCAs occurred within the city limits during the study period. The mean incidence rate was 0.85 OHCAs/1,000 population/year. There were five significant geographic clusters with 76 high-risk census tracts out of the total of 245 census tracts. In the case-level analysis, being in a high-risk cluster was associated with a slightly younger age (3 years, adjusted odds ratio OR 0.99, 95 confidence interval CI 0.99-1.00), not being white, non-Hispanic (OR 0.54, 95 CI 0.45-0.64), cardiac arrest occurring at home (OR 1.53, 95 CI 1.231.71), and not receiving bystander cardiopulmonary resuscitation (CPR) (OR 0.77, 95 CI 0.62-0.96), but with higher survival to hospital discharge (OR 1.78, 95 CI 1.30-2.46). In the census tract-level analysis, high-risk census tracts were also associated with a slightly lower average age (0.1 years, OR 1.14, 95 CI 1.06-1.22) and a lower proportion of white, non-Hispanic patients (0.298, OR 0.04, 95 CI 0.01-0.19), but also a lower proportion of high-school graduates (0.184, OR 0.00, 95 CI 0.00-0.00). Conclusions. This analysis identified high-risk census tracts and associated census tract-level and case-level characteristics that can be used to target public education efforts to prevent OHCA and to mitigate its occurrence with CPR and automated external defibrillator training. In addition, EMS resources can be redeployed to minimize response times to these census tracts.
机译：背景。疾病预防和紧急医疗服务（EMS）中的稀缺资源需要集中在院外心脏骤停（OHCA）的高风险领域。目的。使用地理信息系统（GIS）进行的聚类分析可发现这些高风险区域并测试潜在的预测变量。方法。这是一项对从2004年4月1日至2009年3月31日在俄亥俄州哥伦布市发生的OHCA进行EMS治疗的成年人的回顾性队列分析。将OHCA汇总到人口普查区域，并根据成年人群计算发病率。泊松聚类分析确定了高风险普查区的重要聚类。通过多元逻辑回归分析检验了人口普查区级和病例级特征是否与高风险地区相关。结果。在研究期间，总共2037个符合条件的OHCA发生在城市范围内。平均发病率为0.85 OHCA / 1000人口/年。在245个人口普查区中，有五个重要的地理区域，其中有76个高风险人口普查区。在病例水平分析中，处于高风险人群中与年龄稍小（3岁，调整后的优势比OR 0.99，95置信区间CI 0.99-1.00）相关，不是白人，非西班牙裔（OR 0.54） ，95 CI 0.45-0.64），在家中发生心脏骤停（OR 1.53、95 CI 1.231.71）并且未接受旁观者心肺复苏术（OR 0.77、95 CI 0.62-0.96），但住院率更高放电（OR 1.78，95 CI 1.30-2.46）。在人口普查区级分析中，高风险人口普查区还与平均年龄略低（0.1岁，或1.14，95 CI 1.06-1.22）和白人非西班牙裔患者的比例较低（0.298，或OR）相关。 0.04，95 CI 0.01-0.19），但高中毕业生的比例也较低（0.184，OR 0.00，95 CI 0.00-0.00）。结论。该分析确定了高风险普查区以及相关的普查区级和病例级特征，这些特征可用于针对公共教育工作，以预防OHCA并通过心肺复苏术和自动体外除颤器培训减轻其发生。此外，可以重新部署EMS资源，以最大程度地缩短对这些普查区域的响应时间。

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