Cardialysis Core Laboratories and Clinical Trial Management, Rotterdam, the Netherlands; Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, Rotterdam, the Netherlands.
Cardialysis Core Laboratories and Clinical Trial Management, Rotterdam, the Netherlands.
JACC Cardiovasc Interv. 2017 Apr 10;10(7):658-666. doi: 10.1016/j.jcin.2016.12.016.
This study sought to investigate the differences in detecting (e.g., triggering) periprocedural myocardial infarction (PMI) among 3 current definitions.
PMI is a frequent component of primary endpoints in coronary device trials. Identification of all potential suspected events is critical for accurate event ascertainment. Automatic triggers based on study databases prevent underreporting of events.
We generated automated algorithms to trigger PMI based on each definition and compared results using data from the RESOLUTE all comers trial.
The operationalization of current PMI definitions was achieved by defining programmable algorithms used to interrogate the study database. From a total of 636 PMI triggers, we identified 234 for the World Health Organization extended definition, 382 for the Third Universal definition, and 216 for the Society for Cardiovascular Angiography and Interventions definition. Differences among the biomarkers used, different cutoff values, and in the hierarchy among biomarkers within definitions, yielded a different number of triggers, and identified unique triggers for each definition. Only 38 triggers were consistently identified by all definitions. Availability of ECG data, eCRF data on clinical presentation, and the reporting of >2 post-procedural values of the same biomarker influenced considerably the number of PMI triggers identified.
PMI definitions are not interchangeable. The number of triggers identified and consequently the potential number of events varies significantly, highlighting the importance of rigorous methodology when PMI is a component of a powered endpoint. Emphasis on collection of biomarkers, ECG data, and clinical status at baseline may improve the correct identification of PMI triggers.
本研究旨在探讨 3 种现行定义在检测（如触发）围术期心肌梗死（PMI）方面的差异。
PMI 是冠状动脉器械试验主要终点的常见组成部分。识别所有潜在疑似事件对于准确确定事件至关重要。基于研究数据库的自动触发可防止事件漏报。
我们生成了基于每个定义触发 PMI 的自动算法，并使用 RESOLUTE 所有患者试验的数据比较了结果。
通过定义用于查询研究数据库的可编程算法，实现了现行 PMI 定义的操作化。在总共 636 个 PMI 触发中，我们确定了 234 个符合世界卫生组织扩展定义，382 个符合第三次通用定义，216 个符合心血管造影和介入学会定义。用于识别 PMI 的不同生物标志物、不同截断值以及定义内生物标志物之间的分层差异导致了触发数量的不同，并为每个定义确定了独特的触发。只有 38 个触发被所有定义一致识别。心电图数据的可用性、临床症状电子病例数据和同一生物标志物的>2 个术后值的报告对 PMI 触发的识别数量有很大影响。
PMI 定义不可互换。识别出的触发数量以及潜在事件数量差异显著，这突出了在 PMI 是有力终点组成部分时采用严格方法的重要性。强调生物标志物、心电图数据和基线临床状态的收集可能会改善 PMI 触发的正确识别。
