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An Online Tool for Nurse Triage to Evaluate Risk for Acute Coronary Syndrome at Emergency Department

机译:急诊科护士分类的在线工具,以评估急性冠脉综合征的风险

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Background. To differentiate acute coronary syndrome (ACS) from other causes in patients presenting with chest pain at the emergency department (ED) is crucial and can be performed by the nurse triage. We evaluated the effectiveness of the ED nurse triage for ACS of the tertiary care hospital.Methods. We retrospectively enrolled consecutive patients who were identified as ACS at risk patients by the ED nurse triage. Patients were categorized as ACS and non-ACS group by the final diagnosis. Multivariate logistic analysis was used to predict factors associated with ACS. An online model predictive of ACS for the ED nurse triage was constructed.Results. There were 175 patients who met the study criteria. Of those, 28 patients (16.0%) were diagnosed with ACS. Patients with diabetes, patients with previous history of CAD, and those who had at least one character of ACS chest pain were independently associated with having ACS by multivariate logistic regression. The adjusted odds ratios (95% confidence interval) were 4.220 (1.445, 12.327), 3.333 (1.040, 10.684), and 12.539 (3.876, 40.567), respectively.Conclusions. The effectiveness of the ED nurse triage for ACS was 16%. The online tool is available for the ED triage nurse to evaluate risk of ACS in individuals.
机译:背景。区分急诊科(ED)出现胸痛的患者中的急性冠状动脉综合症(ACS)与其他原因非常重要,可以通过护士分流进行。我们评估了ED护士分诊对三级医院ACS的有效性。我们回顾性纳入了由ED护士分诊确定为ACS高危患者的连续患者。根据最终诊断将患者分为ACS组和非ACS组。多元逻辑分析用于预测与ACS相关的因素。建立了在线预测ED护士分诊ACS的模型。有175位符合研究标准的患者。其中,有28例(16.0%)被诊断患有ACS。糖尿病患者,具有CAD既往史的患者以及至少具有ACS胸痛的一种特征的患者通过多因素Logistic回归独立地患有ACS。调整后的优势比(95%置信区间)分别为4.220(1.445,12.327),3.333(1.040,10.684)和12.539(3.876,40.567)。 ED护士分类对ACS的有效性为16%。 ED分诊护士可以使用该在线工具评估个人发生ACS的风险。

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