ESC 2022:新的人工智能使用常规超声心动图中识别中高死亡风险主动脉瓣狭窄人群(AI-ENHANCED AS研究)

2022-08-29 MedSci原创 MedSci原创

2022年8月28日,一种新的人工智能 (AI) 算法使用常规超声心动图来识别可能从治疗中受益的高死亡风险主动脉瓣狭窄患者。 今天在 2022 年 ESC 大会的热线会议上介绍了最新的研究。

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2022年8月28日,一种新的人工智能 (AI) 算法使用常规超声心动图来识别可能从治疗中受益的高死亡风险主动脉瓣狭窄患者。 今天在 2022 年 ESC 大会的热线会议上介绍了最新的研究。

主动脉瓣狭窄是欧洲和北美最常见的需要手术或经导管干预的原发性瓣膜病变。由于人口老龄化,患病率正在迅速增加。 由于预后不佳,指南强烈建议对所有有症状的严重主动脉瓣狭窄患者进行早期干预。 大约 50% 未经治疗的主动脉瓣狭窄患者在症状出现后的头两年内死亡。3 超声心动图用于评估严重程度,即峰值流速、平均压力梯度和主动脉瓣面积。 然而,越来越多的证据表明,死亡率升高的风险超出了当前的诊断定义,应该考虑更多的患者进行主动脉瓣置换术。

AI-ENHANCED AS 检查了从临床实践中常规使用的超声心动图参数开发的 AI 算法是否可以识别与五年死亡率增加相关的中度至重度和重度主动脉瓣狭窄表型。 使用的专有 AI 决策支持算法 (AI-DSA) 使用来自澳大利亚国家回声数据库 (NEDA) 的数据进行训练,该数据库包含来自超过 630,000 名患者的超过 1,000,000 份超声心动图,并与死亡率信息相关联。 该算法还经过训练,以确保检测到所有指南定义的严重主动脉瓣狭窄。 使用随机选择的 70% 的 NEDA 数据进行训练。

利用剩余的 30% 的 NEDA 数据,研究人员比较了中度至重度和重度主动脉瓣狭窄表型患者的五年死亡率与无严重主动脉瓣狭窄风险的患者的五年死亡率。 在 179,054 人中,AI-DSA 确定了 2,606 人(1.4%)具有中度至重度表型,4,622 人(2.5%)具有重度表型。 在具有严重表型的患者中,3,566 人 (77.2%) 符合严重主动脉瓣狭窄的指南标准。

中重度表型患者的五年死亡率为56.2%,重度表型患者为67.9%。 没有这两种表型的人(参考组)的五年死亡率为 22.9%。 与对照组相比,校正年龄和性别后,中度至重度和重度表型的全因死亡率的调整优势比 (OR) 为 1.82(95% 置信区间 [CI] 1.63–2.02)和 2.80(95% CI 2.57–3.06)。

在 AI-DSA 确定的严重主动脉瓣狭窄表型(4,622;2.5%)中,符合现行指南的患者(77%)的五年死亡率为 69.1%。 AI-DSA 确定的具有严重表型但不符合当前指南的其他人群的死亡率为 64.4%。

澳大利亚圣母大学的首席研究员 Geoffrey Strange 教授说:“这种专有的 AI 算法可以挑选出五年内死亡风险高的患者(以及当前指南内的所有患者),而传统定义可能会忽略这些患者。 研究结果表明,人工智能算法可用于临床实践,以提醒医生应该接受进一步调查以确定他们是否有资格进行主动脉瓣置换术的患者。”

他总结道:“鉴于主动脉瓣狭窄患病率的上升及其对死亡率的影响,是时候重新审视观察等待的做法,并考虑更积极地尝试识别处于危险中的人。 需要更多的研究来确定主动脉瓣置换术是否可以提高被 AI-DSA 确定为具有高死亡风险但不符合当前指南定义的患者的生存率和生活质量。”

参考资料:

https://www.escardio.org/The-ESC/Press-Office/Press-releases/Artificial-intelligence-identifies-severe-aortic-stenosis-from-routine-echocardiograms

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    2022-08-29 循证小兵

    这一届#ESC#年会上#人工智能#十分活跃,有很大的突破,在多种#图像识别#方面,都不亚于医生了

    0

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