Department of Cardiology, Beijing Shijitan Hospital, Capital Medical University, No. 10 Tieyi Road, Haidian District, Beijing, 100038, China.
Sci Rep. 2023 Mar 28;13(1):5084. doi: 10.1038/s41598-023-32222-2.
Ischemia-reperfusion injury is a risk factor for poor clinical prognosis in patients with ST-segment elevation myocardial infarction (STEMI). However, due to the inability to predict the risk of its occurrence early, the effect of intervention measures is still being determined. This study intends to construct a nomogram prediction model and evaluate its value in predicting the risk of ischemia-reperfusion injury (IRI) after primary percutaneous coronary intervention (PCI). The clinical admission data of 386 STEMI patients who underwent primary PCI were retrospectively analyzed. According to the degree of ST-segment resolution (STR), the patients were divided into the STR < 70% group (n = 197) and the STR > 70 group (n = 187). The least absolute shrinkage and selection operator (LASSO) regression method was used to screen out IRI's admission-related clinical risk factors. The R language software was used to construct and verify the IRI nomogram prediction model based on the above indicators. The peak troponin level and the incidence of in-hospital death in the STR < 70% group were significantly higher than those in the STR > 70% group (p < 0.01), and the left ventricular ejection fraction was significantly lower than that in the STR > 70% group (p < 0.01). Combined with the results of LASSO regression and receiver operating characteristic curve comparison analysis, we constructed a six-dimensional nomogram predictive model: hypertension, anterior myocardial infarction, culprit vessel, proximal occlusion, C-reactive protein (CRP) > 3.85 mg/L, white blood cell count, neutrophil cell count, and lymphocyte count. The area under the nomogram's receiver operating characteristic (ROC) curve was 0.779. The clinical decision curve found that the nomogram had good clinical applicability when the occurrence probability of IRI was between 0.23 and 0.95. The nomogram prediction model constructed based on six clinical factors at admission has good prediction efficiency and clinical applicability regarding the risk of IRI after primary PCI in patients with acute myocardial infarction.
缺血再灌注损伤是 ST 段抬高型心肌梗死（STEMI）患者临床预后不良的危险因素。然而，由于无法早期预测其发生的风险，干预措施的效果仍在确定之中。本研究旨在构建列线图预测模型，并评估其预测急性心肌梗死患者直接经皮冠状动脉介入治疗（PCI）后缺血再灌注损伤（IRI）风险的价值。回顾性分析了 386 例接受直接 PCI 的 STEMI 患者的临床入院数据。根据 ST 段回落程度（STR），将患者分为 STR＜70%组（n＝197）和 STR＞70%组（n＝187）。采用最小绝对收缩和选择算子（LASSO）回归方法筛选出与 IRI 相关的入院临床危险因素。使用 R 语言软件构建并验证了基于上述指标的 IRI 列线图预测模型。STR＜70%组的峰值肌钙蛋白水平和院内死亡发生率明显高于 STR＞70%组（p＜0.01），左心室射血分数明显低于 STR＞70%组（p＜0.01）。结合 LASSO 回归和受试者工作特征曲线比较分析的结果，构建了一个六维列线图预测模型：高血压、前壁心肌梗死、罪犯血管、近端闭塞、C 反应蛋白（CRP）＞3.85mg/L、白细胞计数、中性粒细胞计数和淋巴细胞计数。列线图的受试者工作特征（ROC）曲线下面积为 0.779。临床决策曲线发现，当 IRI 发生概率在 0.23 至 0.95 之间时，列线图具有良好的临床适用性。基于入院时 6 个临床因素构建的列线图预测模型对急性心肌梗死患者直接 PCI 后 IRI 风险具有良好的预测效率和临床适用性。
