Just a few months after the official U.S. launch of its Sensora platform, Eko Health has published a study detailing the real-world performance of the platform’s first artificial intelligence-powered heart disease detection tool.

就在美国正式推出Sensora平台几个月后，Eko Health发布了一项研究，详细介绍了该平台第一个人工智能驱动的心脏病检测工具的真实性能。

Sensora combines Eko’s digital stethoscopes with an AI algorithm trained to identify structural heart murmurs that may be linked to valvular heart disease, or VHD. The AI was cleared by the FDA last year and goes beyond just spotting signs of murmurs, also analyzing their timing and severity to distinguish between innocent and absent, and systolic and diastolic murmurs..

Sensora将Eko的数字听诊器与人工智能算法相结合，人工智能算法经过训练可以识别可能与瓣膜性心脏病（VHD）有关的结构性心脏杂音。人工智能去年被美国食品和药物管理局（FDA）批准，它不仅仅是发现杂音的迹象，还分析了它们的时间和严重程度，以区分无辜和缺席，以及收缩期和舒张期杂音。。

The platform also includes Eko’s Care Pathway Analytics software, which clinicians can use to track their patients’ progress through the healthcare system.

该平台还包括Eko的护理路径分析软件，临床医生可以使用该软件通过医疗保健系统跟踪患者的进展。

In study data published in the journal Circulation and presented at the American Heart Association’s scientific sessions this week, Eko found that the AI tool could significantly improve murmur detection—and, therefore, the rate of valvular heart disease diagnoses.

Eko在《循环》杂志上发表的研究数据中发现，人工智能工具可以显着改善杂音检测，从而提高瓣膜性心脏病的诊断率。

The study spanned a total of 369 patients who were at least 50 years old and had never been diagnosed with VHD or a heart murmur. Each patient was examined using both a standard analog stethoscope and one of Eko’s digital stethoscopes, equipped with the AI algorithm.

这项研究共涉及369名至少50岁且从未被诊断出患有VHD或心脏杂音的患者。每位患者均使用标准模拟听诊器和配备AI算法的Eko数字听诊器进行检查。

After comparing the results of each examination to echocardiogram data, the AI-equipped stethoscope was found to be able to spot signs of VHD with about 94% sensitivity, compared to just over 41% for the standard stethoscopes. In total, the AI was able to identify 22 patients with “moderate-or-greater” cases of the disease that had gone previously overlooked, while the analog method uncovered only eight new cases..

在将每次检查的结果与超声心动图数据进行比较后，发现配备AI的听诊器能够以约94%的灵敏度发现VHD的迹象，而标准听诊器的灵敏度略高于41%。总的来说，人工智能能够识别出22例先前被忽视的“中度或更大”病例，而类似方法仅发现了8例新病例。。

The results were much less stark when it came to specificity—that is, classifying negative cases of VHD. On that metric, Eko’s digital device scored just under 85%, while the non-AI device topped 95%.

当涉及特异性时，即对VHD阴性病例进行分类时，结果就不那么明显了。根据这一指标，Eko的数字设备得分略低于85%，而非人工智能设备得分则高达95%。

The study’s authors concluded that Eko’s method “showed meaningful impact on new discovery of VHD as compared to conventional practice,” and they suggested that implementing the technology into regular point-of-care exams could improve the diagnosis rate, patient treatment paths and overall outcomes..

该研究的作者得出结论，Eko的方法“与传统实践相比，对VHD的新发现产生了有意义的影响”，他们建议将该技术应用于常规的即时检查可以提高诊断率，患者治疗途径和总体结果。。

Those improvements are much needed, according to Eko, which cited data in a release this week showing that around half of all adults over the age of 65 have some form of VHD.

据Eko称，这些改进是非常必要的，Eko在本周发布的一份报告中引用了数据，显示65岁以上的成年人中约有一半患有某种形式的VHD。

Though most of those instances are mild, with only about 10% of the age group bearing a clinically significant case of the disease, VHD can progress quickly if left undiagnosed and untreated—a common occurrence, since many patients are asymptomatic, and many symptoms that do crop up are nonspecific—and can ultimately lead to heart failure, stroke and even death..

尽管这些病例大多数是轻微的，只有约10%的年龄组患有临床上显着的VHD病例，但如果不及时诊断和治疗，VHD可以迅速进展-这是一种常见的情况，因为许多患者无症状，许多症状确实是非特异性的，最终可能导致心力衰竭，中风甚至死亡。。

“The implications of undiagnosed or late diagnosis of valvular heart disease are dire, as well as costly to our health system,” Moshe Rancier, M.D., lead author and principal investigator of the study, said in Eko’s release. “This study demonstrates that patients can be more effectively evaluated for VHD in primary care by augmenting the standard cardiac exam with AI-enabled technology.”.

该研究的主要作者兼首席研究员MosheRancier医学博士在Eko的新闻稿中说：“未确诊或迟发性心脏瓣膜病的影响是可怕的，对我们的健康系统来说也是昂贵的。”。“这项研究表明，通过使用人工智能技术增强标准心脏检查，可以更有效地评估患者在初级保健中的VHD。”。

Next up, the researchers plan to continue enrolling participants in the study to gather more evidence, and they’ll also follow the patients for 12 months after the initial exams to assess their clinical outcomes.

接下来，研究人员计划继续招募研究参与者以收集更多证据，并在初次检查后对患者进行12个月的随访，以评估其临床结果。