Zuo Wenjie, Zhang Rui, Yang Mingming, Ji Zhenjun, He Yanru, Su Yamin, Qu Yangyang, Tao Zaixiao, Ma Genshan
Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
Quant Imaging Med Surg. 2021 Jun;11(6):2642-2657. doi: 10.21037/qims-20-1274.
Invasive fractional flow reserve (FFR) is a standard indicator of coronary stenoses' hemodynamic severity. Clinical prediction models (CPMs) may help differentiate ischemic from non-ischemic lesions without using a pressure wire but by integrating related variables. This approach differs from that of physics-based models. However, it is not yet known which CPMs are the most reliable at detecting hemodynamic significance.
A systematic review was performed of relevant publications that developed or validated any FFR CPMs from inception to April 2019 in the PubMed, EMBASE, and Cochrane Library databases by two independent authors. The risk of bias and applicability were assessed using the prediction model risk of the bias assessment tool (PROBAST).
A total of 11 unique CPMs and 5 subsequent external validation studies were identified. The prevalence of hemodynamically significant lesions (FFR ≤0.80) across the studies had a median of 37.1% (range: 20.7-68.0%). Lesion length, percent diameter stenosis, and minimal lumen diameter were the three most frequently used variables in the CPMs. Of the 11 FFR CPMs, 9 (82%) exhibited strong discrimination [area under the curve (AUC) >0.75], and 5 (45%) had been subject to external validation; however, calibration was only available for 3 models (27%). There was a high degree of applicability; however, none of the studies was assessed as having a low risk of bias. A CPM was identified that had undergone rigorous validation and calibration: the DILEMMA score (three validations; median AUC, 0.83).
Almost half of the existing FFR CPMs had been externally validated. Due to their good discrimination abilities, these FFR CPMs are useful tools that could reduce the need for invasive hemodynamic measurements. Future research that adheres to methodological guidelines should be undertaken to develop high-quality models in this setting. (PROSPERO registration number: CRD42019125011).
有创血流储备分数（FFR）是冠状动脉狭窄血流动力学严重程度的标准指标。临床预测模型（CPM）可能有助于在不使用压力导丝的情况下，通过整合相关变量来区分缺血性病变和非缺血性病变。这种方法不同于基于物理学的模型。然而，目前尚不清楚哪些CPM在检测血流动力学意义方面最可靠。
由两名独立作者对PubMed、EMBASE和Cochrane图书馆数据库中从开始到2019年4月开发或验证任何FFR CPM的相关出版物进行系统评价。使用预测模型偏倚评估工具（PROBAST）评估偏倚风险和适用性。
共识别出11个独特的CPM和5项后续外部验证研究。各研究中血流动力学显著病变（FFR≤0.80）的患病率中位数为37.1%（范围：20.7%-68.0%）。病变长度、直径狭窄百分比和最小管腔直径是CPM中最常用的三个变量。在11个FFR CPM中，9个（82%）表现出较强的辨别力[曲线下面积（AUC）>0.75]，5个（45%）经过了外部验证；然而只有3个模型（27%）进行了校准。适用性较高；然而，没有一项研究被评估为偏倚风险低。识别出一个经过严格验证和校准的CPM：困境评分（三项验证；中位数AUC为0.83）。
几乎一半的现有FFR CPM经过了外部验证。由于其良好的辨别能力，这些FFR CPM是有用的工具，可以减少有创血流动力学测量的需求。应开展遵循方法学指南的未来研究，以在这种情况下开发高质量模型。（PROSPERO注册号：CRD42019125011）
