首页> 外文期刊>European journal of emergency medicine: Official journal of the European Society for Emergency Medicine >Could a computer-based system including a prevalence function support emergency medical systems and improve the allocation of life support level?
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Could a computer-based system including a prevalence function support emergency medical systems and improve the allocation of life support level?

机译:包含患病率功能的基于计算机的系统能否支持紧急医疗系统并改善生命支持水平的分配?

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OBJECTIVES: To evaluate whether a computer-based decision support system could be useful for the emergency medical system when identifying patients with acute myocardial infarction (AMI) or life-threatening conditions and thereby improve the allocation of life support level. METHODS: Patients in the Municipality of Goteborg who dialled the dispatch centre due to chest pain during a period of 3 months. To analyse the relationship between patient characteristics (according to a case record form used during an interview) and the response variables (AMI or life-threatening condition), multivariate logistic regression was used. For each patient, the probability of AMI/life-threatening condition was estimated by the model. We used these probabilities retrospectively to allocate advanced life support or basic life support. This model allocation was then compared with the true allocation made by the dispatchers. RESULTS: The sensitivity, that is, the percentage of AMI patients allocated to advanced life support, was 85.7% in relation to the true allocation made by the dispatchers. The corresponding sensitivity regarding allocation made by the model was 92.4% (P=0.17). The specificity was also slightly higher for the model allocation than the dispatcher allocation. Among the 15 patients with AMI who were allocated to basic life support by the dispatchers, nine died (eight during and one after hospitalization). Among the eight patients with AMI allocated to basic life support by the model, only one patient died (in hospital) (P=0.02). CONCLUSION: A computer-based decision support system including a prevalence function could be a valuable tool for allocating the level of life support. The case record form, however, used for the interview can be refined and a model based on a larger sample and confirmed in a prospective study is recommended.
机译:目的:评估基于计算机的决策支持系统在识别急性心肌梗塞(AMI)或危及生命的疾病患者时是否对紧急医疗系统有用,从而改善生命支持水平的分配。方法:哥德堡市因胸痛在三个月内拨打调度中心电话的患者。为了分析患者特征(根据访谈中使用的病例记录表)与响应变量(AMI或危及生命的状况)之间的关系,使用了多元逻辑回归。对于每个患者,通过模型评估AMI /危及生命状况的可能性。我们追溯使用这些概率来分配高级生命支持或基本生命支持。然后将该模型分配与调度员进行的实际分配进行比较。结果:相对于调度员的真实分配,敏感性,即分配给高级生命支持的AMI患者百分比为85.7%。该模型对分配的相应敏感性为92.4%(P = 0.17)。与分配器分配相比,模型分配的特异性也略高。在由调度员分配用于基本生活支持的15例AMI患者中,有9例死亡(住院期间8例,住院后1例)。该模型分配给基本生活支持的8例AMI患者中,只有1例死亡(住院)(P = 0.02)。结论:包括患病率功能的基于计算机的决策支持系统可能是分配生命支持水平的有价值的工具。但是,可以对用于访谈的案例记录表进行完善,并建议基于较大样本的模型并在前瞻性研究中进行确认。

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