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除胸痛外:其他变量的附加价值可用于识别需要早期进行心电图检查的患者。

Beyond chest pain: Incremental value of other variables to identify patients for an early ECG.

机构信息

Department of Emergency Medicine, Stanford University, Palo Alto, CA, United States of America.

Quantitative Sciences Unit, Stanford University, Palo Alto, CA, United States of America.

出版信息

Am J Emerg Med. 2023 May;67:70-78. doi: 10.1016/j.ajem.2023.01.054. Epub 2023 Feb 8.

DOI:10.1016/j.ajem.2023.01.054
PMID:36806978
Abstract

BACKGROUND

Chest pain (CP) is the hallmark symptom for acute coronary syndrome (ACS) but is not reported in 20-30% of patients, especially women, elderly, non-white patients, presenting to the emergency department (ED) with an ST-segment elevation myocardial infarction (STEMI).

METHODS

We used a retrospective 5-year adult ED sample of 279,132 patients to explore using CP alone to predict ACS, then we incrementally added other ACS chief complaints, age, and sex in a series of multivariable logistic regression models. We evaluated each model's identification of ACS and STEMI.

RESULTS

Using CP alone would recommend ECGs for 8% of patients (sensitivity, 61%; specificity, 92%) but missed 28.4% of STEMIs. The model with all variables identified ECGs for 22% of patients (sensitivity, 82%; specificity, 78%) but missed 14.7% of STEMIs. The model with CP and other ACS chief complaints had the highest sensitivity (93%) and specificity (55%), identified 45.1% of patients for ECG, and only missed 4.4% of STEMIs.

CONCLUSION

CP alone had highest specificity but lacked sensitivity. Adding other ACS chief complaints increased sensitivity but identified 2.2-fold more patients for ECGs. Achieving an ECG in 10 min for patients with ACS to identify all STEMIs will be challenging without introducing more complex risk calculation into clinical care.

摘要

背景

胸痛(CP)是急性冠状动脉综合征(ACS)的标志性症状,但在 20-30%的患者中并未报告,尤其是女性、老年人、非白人患者,他们在急诊科(ED)就诊时表现为 ST 段抬高型心肌梗死(STEMI)。

方法

我们使用了一项回顾性的 5 年成人 ED 样本,共 279132 例患者,旨在探讨仅使用 CP 来预测 ACS,然后在一系列多变量逻辑回归模型中逐步加入其他 ACS 主要症状、年龄和性别。我们评估了每个模型对 ACS 和 STEMI 的识别能力。

结果

仅使用 CP 会建议对 8%的患者进行心电图检查(敏感性为 61%;特异性为 92%),但会遗漏 28.4%的 STEMI。包含所有变量的模型可识别 22%的患者需要进行心电图检查(敏感性为 82%;特异性为 78%),但会遗漏 14.7%的 STEMI。包含 CP 和其他 ACS 主要症状的模型具有最高的敏感性(93%)和特异性(55%),可识别 45.1%的患者需要进行心电图检查,仅遗漏 4.4%的 STEMI。

结论

CP 单独使用具有最高的特异性,但敏感性不足。增加其他 ACS 主要症状会提高敏感性,但会导致 2.2 倍的患者需要进行心电图检查。在不引入更复杂的风险计算到临床护理的情况下,要在 10 分钟内为 ACS 患者进行心电图检查以识别所有 STEMI,将极具挑战性。

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