San Jose Medical Center, Kaiser Permanente, CA (J.J.J.).
Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (M.B., A.C., S.V., C.B.F., K.L.L., W.S.J., D.B.M., P.S.D., M.R.P.).
Circ Cardiovasc Imaging. 2019 Feb;12(2):e007940. doi: 10.1161/CIRCIMAGING.118.007940.
Patients with high-risk coronary artery disease (CAD) may be difficult to identify.
Using the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) cohort randomized to coronary computed tomographic angiography (n=4589), 2 predictive models were developed for high-risk CAD, defined as left main stenosis (≥50% stenosis) or either (1) ≥50% stenosis [50] or (2) ≥70% stenosis [70] of 3 vessels or 2-vessel CAD involving the proximal left anterior descending artery. Pretest predictors were examined using stepwise logistic regression and assessed for discrimination and calibration.
High-risk CAD was identified in 6.6% [50] and 2.4% [70] of patients. Models developed to predict high-risk CAD discriminated well: [50], bias-corrected C statistic=0.73 (95% CI, 0.71-0.76); [70], bias-corrected C statistic=0.73 (95% CI, 0.68-0.77). Variables predictive of CAD in both models included family history of premature CAD, age, male sex, lower glomerular filtration rate, diabetes mellitus, elevated systolic blood pressure, and angina. Additionally, smoking history was predictive of [50] CAD and sedentary lifestyle of [70] CAD. Both models characterized high-risk CAD better than the Pooled Cohort Equation (area under the curve=0.70 and 0.71 for [50] and [70], respectively) and Diamond-Forrester risk scores (area under the curve=0.68 and 0.71, respectively). Both [50] and [70] CAD was associated with more frequent invasive interventions and adverse events than non-high-risk CAD (all P<0.0001).
In contemporary practice, 2.4% to 6.6% of stable, symptomatic patients requiring noninvasive testing have high-risk CAD. A simple combination of pretest clinical variables improves prediction of high-risk CAD over traditional risk assessments.
URL: https://www.clinicaltrials.gov . Unique identifier: NCT01174550.
高危冠状动脉疾病（CAD）患者可能难以识别。
使用 PROMISE（前瞻性多中心成像研究评估胸痛）队列随机分配至冠状动脉计算机断层血管造影术（n=4589），为高危 CAD 制定了 2 种预测模型，定义为左主干狭窄（≥50%狭窄）或以下任何一种情况：（1）≥50%狭窄[50]或（2）≥70%狭窄[70]的 3 支血管或 2 支血管 CAD 累及左前降支近端。使用逐步逻辑回归检查术前预测指标，并评估其区分度和校准度。
高危 CAD 在 6.6%[50]和 2.4%[70]的患者中被识别。为预测高危 CAD 而制定的模型具有良好的区分度：[50]，校正后的 C 统计量=0.73（95%置信区间，0.71-0.76）；[70]，校正后的 C 统计量=0.73（95%置信区间，0.68-0.77）。两种模型中预测 CAD 的变量包括早发性 CAD 的家族史、年龄、男性、肾小球滤过率降低、糖尿病、收缩压升高和心绞痛。此外，吸烟史与[50]CAD 相关，而久坐的生活方式与[70]CAD 相关。两种模型对高危 CAD 的描述均优于 Pooled Cohort Equation（曲线下面积为 0.70 和 0.71，分别用于[50]和[70]）和 Diamond-Forrester 风险评分（曲线下面积为 0.68 和 0.71，分别用于[50]和[70]）。与非高危 CAD 相比，[50]和[70]CAD 更常进行有创介入和不良事件（均 P<0.0001）。
在当代实践中，2.4%至 6.6%的需要非侵入性检查的稳定、有症状的患者患有高危 CAD。术前临床变量的简单组合可提高对高危 CAD 的预测，优于传统风险评估。
