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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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

Received: 30 December 2021

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	TAN Yahang
	TIAN Tian
	SHAN Dongkai

Cite this article:

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[J]. Med. J. Chin. Peop. Armed Poli. Forc., 2022, 33(8): 681-685.

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http://journal08.magtechjournal.com/Jwk_wjyx/EN/ OR http://journal08.magtechjournal.com/Jwk_wjyx/EN/Y2022/V33/I8/681

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