Exploratory Development of a Prognostic Model for Coronary Artery Disease Utilizing CT-FFR Derived Functional Duke Jeopardy Score.

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology Pub Date : 2024-12-05 DOI:10.1016/j.acra.2024.11.038

Li-Na Ouyang, Rui Wang, Qian Wu, Pei Wang, Huai-Rong Zhang, Yuan Li, Li Zhu

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引用次数: 0

Abstract

Rationale and objectives: To explore the prognostic value of the functional Duke Jeopardy Score based on CT-FFR(fDJS_CTA) in assessing major adverse cardiovascular events (MACE) in patients with coronary artery disease (CAD).

Materials and methods: A total of 894 patients with stable CAD with stenosis ranging from 30% to 90%, who underwent CCTA were included in the study. Follow-up was performed to record MACE. The patients were randomly divided into training and validation sets in a 7:3 ratio. In the training set, prognostic analysis was performed and predictive model was constructed using univariable and multivariable Cox regressions and compared the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) of different indicators. The receiver operating characteristic curve, calibration curve and clinical decision curve were used to evaluate the model's discrimination, calibration and clinical efficacy.

Results: The median follow-up period was 33 (16-36) months, during which 167 cases (18.68%) of MACE occurred. Males accounted for 61.52% (550/894) of the cohort, with a median age of 61.92 years. The multivariate Cox regression analysis indicated that DJS_CTA (HR: 2.07, 95% CI: 1.17 ∼ 3.68) and fDJS_CTA (HR: 4.68, 95% CI: 2.97 ∼ 7.38) were independent predictors of MACE. Using MACE as a standard, fDJS_CTA improved the risk re-stratification ability of CT-FFR (NRI:0.993, P < 0.001) and the predictive ability of CT-FFR (IDI:0.101, P < 0.001) and DJS_CTA (IDI:0.079, P < 0.001). The prediction model demonstrated high discrimination (training AUC: 0.84 [0.80-0.89]; validation AUC: 0.82 [0.75-0.89]), good calibration and clinical efficacy.

Conclusion: The fDJS_CTA was the strongest predictor of MACE. The model constructed based on fDJS_CTA has certain clinical utility in prognostic evaluation for CAD.

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来源期刊

Academic Radiology 医学-核医学

CiteScore

7.60

自引率

10.40%

发文量

432

审稿时长

18 days

期刊介绍： Academic Radiology publishes original reports of clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, image-guided interventions and related techniques. It also includes brief technical reports describing original observations, techniques, and instrumental developments; state-of-the-art reports on clinical issues, new technology and other topics of current medical importance; meta-analyses; scientific studies and opinions on radiologic education; and letters to the Editor.