• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>JMIR Medical Informatics >Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation
【24h】

Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation

机译：急性ST段升高患者中医院出血的诊断模型心肌梗死：算法开发与验证

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences. Objective The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding. Methods We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). Results In-hospital bleeding occurred in 112 of 4262 participants (2.6%) in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital bleeding in age (odds ratio [OR] 1.047, 95% CI 1.029-1.066; P .001), Killip III (OR 3.265, 95% CI 2.008-5.31; P .001), and Killip IV (OR 5.133, 95% CI 3.196-8.242; P .001). We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was 0.777 (SD 0.021, 95% CI 0.73576-0.81823). We constructed a nomogram based on age and Killip classification. In-hospital bleeding occurred in 117 of 6015 participants (1.9%) in the validation data set. The AUC was 0.7234 (SD 0.0252, 95% CI 0.67392-0.77289). Conclusions We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory.
机译：背景技术急性ST段升高患者心肌梗死（Stemi）的出血并发症与随后的不良后果的风险增加有关。目的是我们研究的目的是开发和外部验证医院出血的诊断模型。方法对大学医院急诊部门的急性症患者进行多元逻辑回归。参与者：从2002年1月到2013年1月到2013年12月的4262名急性STEMI患者获得了模型开发数据集。2014年1月至2019年1月至2019年8月的一套6015名急性STEMI患者用于外部验证。我们使用了Logistic回归分析来分析开发数据集中医院出血的风险因素。我们开发了一个诊断模型的入住医院出血并构建了一个探测图。通过检查鉴别，校准和决策曲线分析（DCA）的测量，我们评估了验证数据集中诊断模型的预测性能。结果在4262名参与者（2.6％）中出现的医院出血，在开发数据集中。住院内出血的最强预测因子是高龄和高杀手分类。 Logistic回归分析显示，在年龄（odaber比率[或] 1.047,95％CI 1.029-1.066; p <.001），Killip III（或3.265,95％CI 2.008-5.31 ; p <.001）和Killip IV（或5.133,95％CI 3.196-8.242; P <.001）。我们开发了一项诊断模型的住院内出血。接收器操作特性曲线（AUC）下的区域为0.777（SD 0.021,95％CI 0.73576-0.81823）。我们根据年龄和基金分类构建了一个墨迹图。在验证数据集中的6015名参与者中的117名中，入住的患者出血（1.9％）。 AUC为0.7234（SD 0.0252,95％CI 0.67392-0.77289）。结论我们开发和外部验证了急性症患者的住院内出血的诊断模型。模型的歧视，校准和DCA被发现令人满意。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号