基于CT平扫的视觉钙化积分系统在稳定型胸痛患者传统验前概率模型中的临床应用

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摘要目的探讨联合视觉评估钙化积分系统对提高稳定型胸痛患者传统验前概率模型的准确性。方法回顾性选择门诊行冠脉CT检查的疑似稳定型冠心病患者。根据Update Diamond-Forrester模型(UDFM),计算患者验前概率。计算患者的Agatston和视觉评估钙化积分,记录患者是否存在阻塞性病变。采用重分类改善指数(NRI)对联合钙化积分系统验前概率模型进行验证。结果共有396例门诊患者符合入组标准。与UDFM模型相比,UDFM+Agatston,UDFM+视觉评估钙化模型能够提高对阻塞性病变的预测价值 [ AUC:0.876(0.830-0.918) vs. 0.749(0.691-0.805),P＜0.001;AUC:0.877(0.835-0.919) vs. 0.749 (0.691-0.805),P＜0.001 ]。与UDFM模型(NRI=27.8.%)比较,视觉评估钙化联合模型的NRI=25.4%(P＜0.05)。结论在稳定型胸痛人群中,基于CT获得钙化积分可以进一步优化传统验前概率模型,实现更为精准的预测。

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	檀亚航
	田天
	单冬凯

关键词 ：冠脉CT, 验前概率, 钙化积分, 冠心病

Abstract：Objective To investigate the accuracy of the traditional pretest probability model for stable chest pain patients by combining visual evaluation calcification score system.Methods Patients with suspected stable coronary artery disease (CAD) who underwent coronary CT examination in the outpatient department were retrospectively selected.According to the Update Diamond-Forrester model (UDFM), the patient pretest probability was calculated.Agatston and visual assessment calcification scores were calculated and the presence of obstructive lesions was recorded.Reclassification improvement Index (NRI) was used to verify the pretest probability model of combined calcification score system.Results A total of 396 outpatients met the inclusion criteria.Compared with UDFM model, UDFM+Agatston and UDFM+ visual evaluation of calcification model could improve the predictive value of obstructive lesions [AUC: 0.876 (0.830-0.918) vs. 0.749 (0.691-0.805), P<0.001;AUC:0.877 (0.835-0.919) vs. 0.749 (0.691-0.805), P<0.001].Compared with UDFM model (NRI=27.8.%), the NRI of visual assessment combined model of calcification was 25.4% (P<0.05).Conclusion For patients with stable chest pain, calcification score based on CT can further optimize the traditional pretest probability model to achieve more accurate prediction.

Key words： coronary computed tomography pretest probability calcification score coronary artery disease

收稿日期: 2021-12-30

ZTFLH:

R543.3

基金资助:国家自然科学基金(62106160)

通讯作者: 田天,E-mail:tanyahang@163.com

作者简介: 檀亚航,博士,医师。

引用本文:

檀亚航, 田天, 单冬凯. 基于CT平扫的视觉钙化积分系统在稳定型胸痛患者传统验前概率模型中的临床应用[J]. 武警医学, 2022, 33(8): 681-685. TAN Yahang, TIAN Tian, SHAN Dongkai. Clinical application of visual calcification score system based on PLAIN CT scan in traditional pretest probability model for patients with stable chest pain. Med. J. Chin. Peop. Armed Poli. Forc., 2022, 33(8): 681-685.

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http://journal08.magtechjournal.com/Jwk_wjyx/CN/ 或 http://journal08.magtechjournal.com/Jwk_wjyx/CN/Y2022/V33/I8/681

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