全球首创心肌肌球蛋白抑制剂玛伐凯泰，是全球首个针对HCM核心病理生理机制的创新药物。近年来，百时美施贵宝（BMS）通过不断深入玛伐凯泰在 全球和中国的研发，持续验证疗效，中国研究者也深度参与其中。例如，玛伐凯泰用于中国患者的关键III期临床研究——EXPLORER-CN，与多项全球研 究结果共同推动了玛伐凯泰在中国获批。与此同时，BMS还与中国本土科研力量合作，共同推动全球创新更好地"落地中国"。 *仅供医学专业人士阅读参考 肥厚型心肌病（HCM）是临床上最常见的单基因遗传性心脏病，主要表现为心肌非对称性肥厚[1]。根据是否存在左心室流出道梗阻，HCM又分为梗阻性 与非梗阻性两类，梗阻性HCM患者生存率更低。 呼吸困难、乏力、胸痛、甚至晕厥，几乎是所有梗阻性HCM患者所经历的。疾病不仅限制了他们的活动能力，还带来长期的精神压力——许多患者不得 不告别工作、运动和旅行，甚至连日常生活都被迫"放慢节奏"。 据估算，HCM的全球患病率为0.2%至0.5%，中国约有200万HCM患者[2]。由于公众认知不足、基层诊断能力有限，有大量患者未被确诊或未能获得规范 治疗。多年来，梗阻性HCM患者亟需一种能够针对疾病根源的治 ...

Core Viewpoint - Sudden Cardiac Death (SCD) is a major global health issue, particularly in patients with Hypertrophic Cardiomyopathy (HCM), where current clinical guidelines show low performance and inconsistent accuracy in risk assessment [1][2]. Group 1 - SCD has an annual incidence of 50-100 cases per 100,000 people in North America and Europe, with ventricular arrhythmias being the primary mechanism [1]. - Implantable Cardioverter Defibrillators (ICDs) can effectively terminate arrhythmias and reduce mortality in high-risk patients when implanted preventively [1]. - The current risk stratification paradigm, based on Left Ventricular Ejection Fraction (LVEF) below 30%-35%, is primarily applicable to ischemic and dilated cardiomyopathy patients but fails to provide comprehensive risk assessment [2]. Group 2 - A recent study published by researchers from Johns Hopkins University introduced a multimodal AI model named MAARS (Multimodal Artificial intelligence for Ventricular Arrhythmia Risk Stratification) to predict arrhythmic death in HCM patients [3][4]. - MAARS utilizes a Transformer-based neural network that learns from electronic health records, echocardiograms, radiology reports, and contrast-enhanced cardiac MRI, which is a unique aspect of the model [8]. Group 3 - MAARS demonstrated an Area Under the Curve (AUC) of 0.89 in internal cohorts and 0.81 in external cohorts, significantly outperforming current clinical guidelines which have AUCs ranging from 0.27-0.35 (internal) and 0.22-0.30 (external) [10]. - Unlike clinical guidelines, MAARS shows fairness across different population subgroups, enhancing the transparency of AI predictions and identifying risk factors for further investigation [10]. - Overall, MAARS is a powerful and reliable clinical decision support tool for risk stratification of SCD in HCM patients, with potential to significantly improve clinical decision-making and patient care through integration with automated data extraction systems or as a concept validation for personalized patient care [10].