Suppr超能文献

基于直接经皮冠状动脉介入治疗的 ST 段抬高型心肌梗死患者中预测冠状动脉微血管阻塞的风险列线图模型的建立与验证。

Development and Validation of Risk Nomogram Model Predicting Coronary Microvascular Obstruction in Patients with ST-Segment Elevation Myocardial Infarction (STEMI) Undergoing Primary Percutaneous Catheterization.

机构信息

Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China (mainland).

出版信息

Med Sci Monit. 2019 Aug 7;25:5864-5877. doi: 10.12659/MSM.915960.

Abstract

BACKGROUND Coronary microvascular functional and structural obstruction (CMVO) remains a major complication in patients with ST-segment elevation myocardial infarction (STEMI). This study was designed to develop and validate a nomogram model to predict CMVO risk during primary percutaneous catheterization procedure. MATERIAL AND METHODS Starting January 2014 to December 2016, a cohort of eligible candidates were enrolled and divided into a training or a validation database. Each database was divided into MO or NMO subgroups based on TIMI myocardial perfusion grade results after recanalization. Independent factors were identified by multivariate logistic regression, from which the nomogram was plotted. The echocardiography measurement of the left ventricular ejection fraction (LVEF) was arranged within 7 days after the procedure. RESULTS A nomogram was built for CMVO risk prediction for the first time. There were 446 participants in the training database with 319 cases in the NMO subgroup and 127 participants in the MO subgroup. The validation database included 99 participants with 25 cases in the NMO subgroup and 74 in the MO subgroup. The risk model was developed by 6 independently significant factors: age, symptom onset to balloon time, Killip classification, admission activated clotting time, neutrophil/lymphocyte ratio, and glucose value. Internal receiver operating characteristic displayed favorable performance with concordance index of 0.925, while external validation area under curve was 0.939. There were significant differences in LVEF values during hospitalization between the subgroups of each database (both P<0.001). CONCLUSIONS The nomogram model consisting of 6 factors could predict CMVO risk accurately for STEMI patients undergoing primary percutaneous catheterization.

摘要

背景

冠状动脉微血管功能和结构阻塞(CMVO)仍然是 ST 段抬高型心肌梗死(STEMI)患者的主要并发症。本研究旨在开发和验证一种列线图模型,以预测直接经皮冠状动脉介入治疗过程中 CMVO 的风险。

材料和方法

从 2014 年 1 月至 2016 年 12 月,入选了一组符合条件的候选者,并将其分为训练或验证数据库。根据再通后 TIMI 心肌灌注分级结果,每个数据库分为 MO 或 NMO 亚组。通过多变量逻辑回归确定独立因素,并绘制列线图。术后 7 天内安排左心室射血分数(LVEF)的超声心动图测量。

结果

首次建立了 CMVO 风险预测的列线图。训练数据库中有 446 名参与者,其中 NMO 亚组 319 例,MO 亚组 127 例。验证数据库包括 99 名参与者,其中 NMO 亚组 25 例,MO 亚组 74 例。该风险模型由 6 个独立的显著因素开发而成:年龄、症状发作至球囊时间、Killip 分级、入院激活凝血时间、中性粒细胞/淋巴细胞比值和血糖值。内部接收者操作特征显示出良好的性能,一致性指数为 0.925,而外部验证曲线下面积为 0.939。两个数据库的每个亚组在住院期间的 LVEF 值均存在显著差异(均 P<0.001)。

结论

由 6 个因素组成的列线图模型可以准确预测接受直接经皮冠状动脉介入治疗的 STEMI 患者的 CMVO 风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2176/6693363/1014e7509ccb/medscimonit-25-5864-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验