Yang Li, Cong Hongliang, Lu Yali, Chen Xiaolin, Liu Yin
Department of Cardiology, Tianjin Chest Hospital, Tianjin, China.
Department of Epidemiology and Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China.
Ann Transl Med. 2021 Jan;9(2):126. doi: 10.21037/atm-20-8003.
The purpose of this study was to screen the predictive factors of no-reflow after a percutaneous coronary intervention (PCI) in elderly patients with ST-segment elevation myocardial infarction (STEMI), and to construct a nomogram model, to guide clinical treatment.
A total of 551 elderly STEMI patients (age >65) underwent direct PCI were randomly classified into training group (n=386, 70%) and validation group (n=165, 30%). All patients in the two groups were divided into a no-reflow group and a normal blood flow group according to whether there was a no-reflow phenomenon. Univariable and multivariable logistic regression analysis was used to analyze the relevant data, including demographic characteristics, clinical characteristics, coronary angiography results, electrocardiogram (ECG) results, and biochemical indicators. Then, a nomogram model was constructed on the screened risk factors. The performance of the nomogram was evaluated in terms of discrimination and calibration. The nomogram was further confirmed in the internal validation group. Additionally, decision curve analysis (DCA) was applied to assess the clinical usefulness of the nomogram.
Five remarkable risk factors were determined: preoperative TIMI blood flow, the diameter of the target lesion, collateral circulation, pulse pressure, and the number of leads for ST-segment elevation. The nomogram involving these five risk factors showed full calibration and discrimination in the training group, with an AUC of 0.71 (95% CI: 0.66-0.77). It was confirmed in the validation group, and the entire cohort and the AUC were 0.64 (95% CI: 0.56-0.73) and 0.69 (95% CI: 0.65-0.74), respectively. Whether in the training group or the verification group, the calibration curve for the probability of no-reflow phenomenon all showed considerable consistency between prediction by nomogram and actual observation. The decision curve revealed a specific role in our nomogram in clinical practice.
We set up a nomogram that showed absolute accuracy for the prediction of the risk of no-reflow after primary PCI in elderly STEMI patients.
本研究旨在筛选老年ST段抬高型心肌梗死(STEMI)患者经皮冠状动脉介入治疗(PCI)后无复流的预测因素,并构建列线图模型,以指导临床治疗。
将551例接受直接PCI的老年STEMI患者(年龄>65岁)随机分为训练组(n = 386,70%)和验证组(n = 165,30%)。根据是否存在无复流现象,将两组所有患者分为无复流组和正常血流组。采用单因素和多因素逻辑回归分析相关数据,包括人口统计学特征、临床特征、冠状动脉造影结果、心电图(ECG)结果和生化指标。然后,根据筛选出的危险因素构建列线图模型。从区分度和校准度方面评估列线图的性能。在内部验证组中进一步验证列线图。此外,应用决策曲线分析(DCA)评估列线图的临床实用性。
确定了五个显著的危险因素:术前心肌梗死溶栓治疗(TIMI)血流、靶病变直径、侧支循环、脉压和ST段抬高导联数。包含这五个危险因素的列线图在训练组中显示出完全校准和区分度,曲线下面积(AUC)为0.71(95%可信区间:0.66 - 0.77)。在验证组中得到证实,整个队列的AUC分别为0.64(95%可信区间:0.56 - 0.73)和0.69(95%可信区间:0.65 - 0.74)。无论是在训练组还是验证组,无复流现象概率的校准曲线在列线图预测和实际观察之间均显示出相当的一致性。决策曲线显示了我们的列线图在临床实践中的特定作用。
我们建立了一个列线图,其对老年STEMI患者直接PCI后无复流风险的预测具有绝对准确性。