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Creation and Validation of an EMR-based Algorithm for Identifying Major Adverse Cardiac Events while on Statins

机译:基于EMR的他汀类药物识别主要不良心脏事件的算法的创建和验证

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摘要

Statin medications are often prescribed to ameliorate a patient’s risk of cardiovascular events due in part to cholesterol reduction. We developed and evaluated an algorithm that can accurately identify subjects with major adverse cardiac events (MACE) while on statins using electronic medical record (EMR) data. The algorithm also identifies subjects experiencing their first MACE while on statins for primary prevention. The algorithm achieved 90% to 97% PPVs in identification of MACE cases as compared against physician review. By applying the algorithm to EMR data in BioVU, cases and controls were identified and used subsequently to replicate known associations with eight genetic variants. We replicated 6/8 previously reported genetic associations with cardiovascular diseases or lipid metabolism disorders. Our results demonstrated that the algorithm can be used to accurately identify subjects with MACE and MACE while on statins. Consequently, future e studies can be conducted to investigate and validate the relationship between statins and MACE using real-world clinical data.
机译:通常开处方他汀类药物以减轻部分降低胆固醇导致患者发生心血管事件的风险。我们开发并评估了一种算法,该算法可以使用电子病历(EMR)数据在他汀类药物上准确识别出具有严重不良心脏事件(MACE)的受试者。该算法还可以识别使用他汀类药物进行一级预防时经历其首次MACE的受试者。与医师审查相比,该算法在识别MACE病例中实现了90%至97%的PPV。通过将该算法应用于BioVU中的EMR数据,可以识别病例和对照,随后将其用于复制具有八个遗传变异的已知关联。我们复制了先前报道的6/8与心血管疾病或脂质代谢紊乱的遗传关联。我们的结果表明,该算法可用于在他汀类药物上准确识别具有MACE和MACE的受试者。因此,可以使用现实的临床数据进行进一步的电子研究,以调查和验证他汀类药物与MACE之间的关系。

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