Department of Cardiology, Heart Centre, Alfred Health, Victoria, Australia.
Monash University, Faculty of Medicine, Nursing and Health Sciences, University in Clayton, Victoria, Australia.
Am J Cardiol. 2023 Oct 15;205:134-140. doi: 10.1016/j.amjcard.2023.07.168. Epub 2023 Aug 18.
Patients at a low risk of coronary artery disease (CAD) could be triaged to noninvasive coronary computed tomography angiogram instead of invasive coronary angiography, reducing health care costs and patient morbidity. Therefore, we aimed to develop a CAD risk prediction score to identify those who underwent transcatheter aortic valve implantation (TAVI) at a low risk of CAD. We enrolled 1,782 patients who underwent TAVI and randomized the patients to the derivation or validation cohort 2:1. The aortic stenosis-CAD (AS-CAD) score was developed using logistic regression, followed by separation into low- (score 0 to 5), intermediate- (6 to 10), or high-risk (>11) categories. The AS-CAD was validated initially through the k-fold cross-validation, followed by a separately held validation cohort. The average age of the cohort was 82 ± 7 years, and 41% (730 of 1,782) were female; 35% (630) had CAD. The male sex, previous percutaneous coronary intervention, stroke, peripheral arterial disease, diabetes, smoking status, left ventricular ejection fraction <50%, and right ventricular systolic pressure >35 mm Hg were all associated with an increased risk of CAD and were included in the final AS-CAD model (all p <0.03). Within the validation cohort, the AS-CAD score stratified those into low, intermediate, and high risk of CAD (p <0.001). Discrimination was good within the internal validation cohort, with a c-statistic of 0.79 (95% confidence interval 0.74 to 0.84), with similar power obtained using k-fold cross-validation (c-statistic 0.74 [95% confidence interval 0.70 to 0.77]). In conclusion, The AS-CAD score robustly identified those at a low risk of CAD in patients with severe AS. The use of AS-CAD in practice could avoid potential complications of invasive coronary angiogram by triaging low-risk patients to noninvasive coronary assessment using existing computed tomography data.
患有低危冠心病（CAD）的患者可以通过非侵入性冠状动脉计算机断层扫描血管造影（CCTA）而非有创冠状动脉造影（ICA）进行分诊，从而降低医疗保健成本和患者发病率。因此，我们旨在开发一种 CAD 风险预测评分，以识别那些接受经导管主动脉瓣置换术（TAVI）的低危 CAD 患者。我们纳入了 1782 名接受 TAVI 的患者，并将患者随机分为推导队列和验证队列，比例为 2:1。使用逻辑回归开发了主动脉瓣狭窄-CAD（AS-CAD）评分，然后将其分为低危（评分 0 至 5 分）、中危（6 至 10 分）或高危（>11 分）类别。首先通过 k 折交叉验证验证 AS-CAD，然后在单独的验证队列中进行验证。队列的平均年龄为 82±7 岁，41%（730 名/1782 名）为女性；35%（630 名）患有 CAD。男性、经皮冠状动脉介入治疗、中风、外周动脉疾病、糖尿病、吸烟状况、左心室射血分数<50%和右心室收缩压>35mmHg 均与 CAD 风险增加相关，并包含在最终的 AS-CAD 模型中（所有 p<0.03）。在验证队列中，AS-CAD 评分将患者分为 CAD 低危、中危和高危（p<0.001）。内部验证队列的区分度较好，C 统计量为 0.79（95%置信区间 0.74 至 0.84），使用 k 折交叉验证也获得了相似的效果（C 统计量 0.74[95%置信区间 0.70 至 0.77]）。总之，AS-CAD 评分可稳健地识别出严重主动脉瓣狭窄患者中 CAD 低危患者。在实践中，AS-CAD 的使用可以通过将低危患者分诊至现有的 CT 数据进行非侵入性冠状动脉评估，从而避免有创冠状动脉造影的潜在并发症。
