Sittichanbuncha Yuwares, Sanpha-Asa Patchaya, Thongkrau Theerayut, Keeratikasikorn Chaiyapon, Aekphachaisawat Noppadol, Sawanyawisuth Kittisak
Emergency Medicine Department, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand.
Department of Computer Sciences, Faculty of Sciences, Khon Kaen University, Khon Kaen 40002, Thailand.
Emerg Med Int. 2015;2015:413047. doi: 10.1155/2015/413047. Epub 2015 Apr 2.
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.
背景。在急诊科（ED）对胸痛患者鉴别急性冠状动脉综合征（ACS）与其他病因至关重要，且可由护士分诊完成。我们评估了三级医院急诊科护士对ACS的分诊效果。方法。我们回顾性纳入了经急诊科护士分诊确定为ACS风险患者的连续患者。根据最终诊断将患者分为ACS组和非ACS组。采用多因素逻辑分析预测与ACS相关的因素。构建了一个用于急诊科护士分诊的ACS在线预测模型。结果。有175例患者符合研究标准。其中，28例（16.0%）被诊断为ACS。多因素逻辑回归显示，糖尿病患者、既往有CAD病史的患者以及具有至少一种ACS胸痛特征的患者独立与患有ACS相关。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）。结论。急诊科护士对ACS的分诊有效率为16%。该在线工具可供急诊科分诊护士评估个体发生ACS的风险。
