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一种用于急性心肌炎与急性冠状动脉综合征鉴别诊断的新型临床评分——萨尔茨堡心肌炎(SAMY)评分。

A Novel Clinical Score for Differential Diagnosis Between Acute Myocarditis and Acute Coronary Syndrome - The SAlzburg MYocarditis (SAMY) Score.

作者信息

Mirna Moritz, Schmutzler Lukas, Topf Albert, Sipos Brigitte, Hehenwarter Lukas, Hoppe Uta C, Lichtenauer Michael

机构信息

Division of Cardiology, Department of Internal Medicine II, Paracelsus Medical University, Salzburg, Austria.

Department of Nuclear Medicine and Endocrinology, Paracelsus Medical University, Salzburg, Austria.

出版信息

Front Med (Lausanne). 2022 Jun 9;9:875682. doi: 10.3389/fmed.2022.875682. eCollection 2022.

Abstract

BACKGROUND

Acute myocarditis and acute coronary syndrome (ACS) are important differential diagnoses in patients with new-onset chest pain. To date, no clinical score exists to support the differentiation between these two diseases. The aim of this study was to develop such a score to aid the physician in scenarios where discrimination between myocarditis and ACS appears difficult.

MATERIALS AND METHODS

Patients with ACS ( = 233) and acute myocarditis ( = 123) were retrospectively enrolled. Least absolute shrinkage and selection operator (LASSO) regression was conducted to identify parameters associated with the highest or least probability for acute myocarditis. Logistic regression was conducted using the identified parameters and score points for each level of the predictors were calculated. Cutoffs for the prediction of myocarditis were calculated. Validation was conducted in a separate cohort of 90 patients.

RESULTS

A score for prediction of acute myocarditis was calculated using six parameters [age, previous infection, hyperlipidemia, hypertension, C-reactive protein (CRP), and leukocyte count]. Logistic regression analysis showed a significant association between total score points and the presence of myocarditis ( = 0.9078, < 0.0001). Cutoff #1 for the prediction of myocarditis was calculated at ≥ 4 (Sens.: 90.3%, Spec.: 93.1%; 46.3% predicted probability for acute myocarditis), cutoff #2 was calculated at ≥ 7 (Sens.: 73.1%, Spec.: > 99.9%; 92.9% pred. prob.). Validation showed good discrimination [area under the curve (AUC) = 0.935] and calibration of the score.

CONCLUSION

Our clinical score showed good discrimination and calibration for differentiating patients with acute myocarditis and ACS. Thus, it could support the differential diagnosis between these two disease entities and could facilitate clinical decisions in affected patients.

摘要

背景

急性心肌炎和急性冠状动脉综合征(ACS)是新发胸痛患者的重要鉴别诊断。迄今为止,尚无临床评分来支持这两种疾病的鉴别。本研究的目的是开发这样一种评分,以帮助医生在难以区分心肌炎和ACS的情况下进行判断。

材料与方法

回顾性纳入ACS患者(n = 233)和急性心肌炎患者(n = 123)。进行最小绝对收缩和选择算子(LASSO)回归以识别与急性心肌炎最高或最低概率相关的参数。使用识别出的参数进行逻辑回归,并计算每个预测变量水平的得分点。计算心肌炎预测的临界值。在另一组90例患者中进行验证。

结果

使用六个参数[年龄、既往感染、高脂血症、高血压、C反应蛋白(CRP)和白细胞计数]计算急性心肌炎的预测评分。逻辑回归分析显示总分与心肌炎的存在之间存在显著关联(OR = 0.9078,P < 0.0001)。心肌炎预测的临界值#1计算为≥4(敏感性:90.3%,特异性:93.1%;急性心肌炎预测概率为46.3%),临界值#2计算为≥7(敏感性:73.1%,特异性:> 99.9%;预测概率为92.9%)。验证显示该评分具有良好的区分度[曲线下面积(AUC)= 0.935]和校准度。

结论

我们的临床评分在区分急性心肌炎和ACS患者方面显示出良好的区分度和校准度。因此,它可以支持这两种疾病实体之间的鉴别诊断,并有助于受影响患者的临床决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbc7/9218572/29236ef40745/fmed-09-875682-g001.jpg

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