基于CT-FFR联合临床指标对疑似冠心病胸痛患者18个月MACE的预测价值研究

Predictive Value of CT‑FFR Combined with Clinical Indicators for 18‑Month MACE in Patients with Chest Pain Suspected of Coronary Artery Disease

摘要: 目的：评估基于冠状动脉CT血管成像的血流储备分数(Computed Tomography-Derived Fractional Flow Reserve, CT-FFR)对疑似冠心病胸痛患者18个月主要不良心血管事件(Major Adverse Cardiovascular Event, MACE)的预测价值，并探索其与临床指标联合的增量效能。方法：连续纳入196例因胸痛就诊并完成CCTA的疑似冠心病患者，根据CT-FFR值分为阳性组(≤0.80, n = 93)和阴性组(>0.80, n = 103)。收集基线临床资料、实验室指标及诊疗路径信息。主要终点为18个月MACE事件。采用Kaplan-Meier生存分析、多因素Logistic回归及受试者工作特征(ROC)曲线评估CT-FFR的预测价值。结果：随访期间，CT-FFR阳性组MACE发生率显著高于阴性组(31.18% vs. 8.74%, P < 0.001)。多因素Logistic回归显示，CT-FFR阳性是MACE的独立预测因子(OR = 5.461, 95% CI: 2.253~13.236, P < 0.001)。单独CT-FFR预测MACE的AUC为0.679，联合年龄、BNP、血肌酐(Cr)的模型B的AUC提升至0.752 (P = 0.035)。结论：CT-FFR ≤ 0.80是疑似冠心病患者18个月MACE的强独立预测因子。联合CT-FFR与BNP、Cr等临床指标可显著提高风险分层效能。

Abstract: Objective: This study aimed to evaluate the predictive value of computed tomography-derived fractional flow reserve (CT‑FFR) for 18‑month major adverse cardiovascular events (MACE) in patients with chest pain suspected of coronary artery disease (CAD), and to explore the incremental efficacy when combined with clinical indicators. Methods: A total of 196 consecutive patients with suspected CAD who presented with chest pain and underwent coronary computed tomography angiography (CCTA) were enrolled. They were divided into a positive group (CT‑FFR ≤ 0.80, n = 93) and a negative group (CT‑FFR > 0.80, n = 103) based on CT‑FFR values. Baseline clinical data, laboratory indicators, and diagnostic/therapeutic pathways were collected. The primary endpoint was MACE at 18 months. Kaplan‑Meier survival analysis, multivariate logistic regression, and receiver operating characteristic (ROC) curves were used to assess the predictive value of CT‑FFR. Results: During follow‑up, the MACE rate in the CT‑FFR positive group was significantly higher than that in the negative group (31.18% vs. 8.74%, P < 0.001). Multivariate logistic regression showed that positive CT‑FFR was an independent predictor of MACE (OR = 5.461, 95% CI: 2.253~13.236, P < 0.001). The area under the ROC curve (AUC) for CT‑FFR alone in predicting MACE was 0.679, while the AUC of Model B, which combined CT‑FFR with age, BNP, and serum creatinine (Cr), increased to 0.752 (P = 0.035). Conclusion: CT‑FFR ≤ 0.80 is a strong independent predictor of 18‑month MACE in patients with suspected CAD. Combining CT‑FFR with clinical indicators such as BNP and Cr significantly improves risk stratification performance.