相关实验视频
Updated: Jan 29, 2026

05:37
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
2.6K
在PCI中开发和内部验证救助风险评分,使用涂有药物的气球
Luigi Alberto Iossa1, Marco Ferrone1, Luigi Salemme1
1Division of Interventional Cardiology, Montevergine Clinic, 83013 Mercogliano, Italy.
Journal of clinical medicine
|January 28, 2026
概括
一个新的床边救助风险评分有助于预测在冠状动脉干预的药物涂层气球手术期间需要紧急支架. 这种工具有助于临床医生管理经过皮肤冠状动脉干预的患者的程序风险.
科学领域:
- 干预心脏病学 干预心脏病学
- 医疗器械技术 医疗器械技术
- 临床风险预测预测
背景情况:
- 在使用药物涂层气球 (DCB) 进行皮肤通冠状动脉干预 (PCI) 时,救助支架是一个重大挑战.
- 目前,没有床头工具可以预测在DCB程序期间需要救助支架的可能性.
- 这种差距凸显了评估程序风险的实际方法的需要.
研究的目的:
- 开发和内部验证床边风险评分,用于预测DCB治疗病变的救助支架.
- 在接受DCB-only PCI的患者中确定救助支架的独立预测因素.
- 在复杂的PCI程序中提供实时风险评估工具.
主要方法:
- 在2021-2025年期间,对352名患者 (399个病变) 进行了DCB-only PCI治疗的分析.
- 多变量后勤回归确定了救助支付的预测因素,其中显著变量被转换为整数点.
- 模型性能使用AUC-ROC,校准和bootstrap内部验证进行评估.
主要成果:
- 在14.5%的病变中发生了救助支架.
- 独立预测因素包括先前的CABG,近端病变位置和扩散性疾病;先前的PCI和降脂疗法具有保护性.
- 开发的救助风险评分显示了中度的歧视 (AUC=0.734) 和优秀的校准,将患者分为低,中,高风险组.
结论:
- 救助风险评分是一个实用和可靠的床头工具,用于估计无支架的PCI中的程序风险.
- 该得分有助于临床医生预测和管理DCB程序期间的潜在并发症.
- 这种工具可以通过允许更好的程序规划和风险分层来改善患者的治疗结果.
相关概念视频
In Vitro Drug Release Testing: Overview, Development and Validation
327
In vitro dissolution and drug release tests assess how quickly and how much of a drug is released from its dosage form into an aqueous medium under standardized laboratory conditions. These tests are essential tools in pharmaceutical development and quality assurance, offering insight into the drug's performance before clinical use.During formulation development, dissolution testing identifies incomplete or inconsistent drug release issues. It also supports decisions on selecting the optimal...
327
Reliability and Validity
13.9K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.9K
Internal Energy
36.7K
The total of all possible kinds of energy present in a substance is called the internal energy (U), sometimes symbolized as E. Suppose a system with initial internal energy, Uinitial, undergoes a change in energy (transfer of work or heat), and the final internal energy of the system is Ufinal. Change in internal energy equals the difference between Ufinal and Uinitial.
36.7K
Introduction to z Scores
11.2K
A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
z scores...
11.2K
Introduction to z Scores
1.3K
A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
z scores...
1.3K
z Scores and Area Under the Curve
19.6K
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
19.6K

