Remppis B A, Zellweger M J, Kelle S, Leber A, Weißer M, Heinl P V, Freudenberg L S, Rischpler C, Emrich T, Mildenberger P, Helms T
Klinik für Kardiologie, Herz- und Gefäßzentrum Bad Bevensen, Bad Bevensen, Deutschland.
Kardiologische Klinik, Universitätsspital, Universität Basel, Basel, Schweiz.
Herzschrittmacherther Elektrophysiol. 2025 Sep 1. doi: 10.1007/s00399-025-01094-6.
The German healthcare system is facing challenges in diagnosing coronary artery disease (CAD). These include high mortality rates, even when advanced medical technology is used, and an excessive number of coronary angiographies. A key issue is that current guideline models inaccurately estimate pretest probability (PTP). However, accurately determining PTP is crucial for efficiently guiding the diagnostic pathway and ensuring cost-effectiveness. Artificial intelligence (AI)-based systems offer a solution for precisely determining a personalized PTP. Approved medical AI devices calculate a personalized PTP using laboratory values and medical history. These systems achieve high accuracy (area under the curve 0.87), improve patient selection, avoid unnecessary diagnostics for low-risk patients, and demonstrate significant cost savings. AI-based PTP is essential for improving guideline-based CAD diagnostics and utilizing resources more efficiently.
德国医疗保健系统在冠状动脉疾病（CAD）的诊断上面临挑战。这些挑战包括即便使用了先进医疗技术仍有较高死亡率，以及冠状动脉造影检查数量过多。一个关键问题是当前的指南模型对预检概率（PTP）的估计不准确。然而，准确确定PTP对于有效指导诊断路径和确保成本效益至关重要。基于人工智能（AI）的系统为精确确定个性化PTP提供了一种解决方案。获批的医疗AI设备利用实验室检查值和病史来计算个性化PTP。这些系统具有很高的准确性（曲线下面积为0.87），改善了患者选择，避免了对低风险患者进行不必要的诊断，并显示出显著的成本节约。基于AI 的PTP对于改进基于指南的CAD诊断和更有效地利用资源至关重要。
