对于急性心肌梗塞急性心肌梗塞的手腕穿戴的透皮热素I传感器评估来说,这是一个新的突破
Shantanu Sengupta1, Siddharth Biswal2, Jitto Titus2
1Sengupta Hospital and Research Institute, Nagpur- 440033, Vidarbha (Dist), India.
European heart journal. Digital health
|June 2, 2023
概括
一种新型的手腕佩戴传感器提供了一种无血方法,可以快速预测心脏中高血水平,有助于诊断急性心肌梗塞 (MI) 并改善急性冠状动脉综合征 (ACS) 患者分组.
科学领域:
- 生物医学工程 生物医学工程
- 心脏病学 心脏病学
- 人工智能在医学中的应用
背景情况:
- 准确及时诊断急性心肌梗塞 (MI) 对于有效治疗急性冠状动脉综合征 (ACS) 至关重要.
- 目前的诊断方法依赖于抽血和实验室检测,导致治疗开始的延迟.
- 对于疑似ACS的非侵入性,快速诊断工具有需要.
研究的目的:
- 评估穿戴在手腕上的超皮肤红外光谱传感器 (超皮肤-ISS) 的临床可行性.
- 评估机器学习算法的性能,使用皮肤间ISS数据来识别心脏高灵敏度升的Troponin-I (hs-cTnI) 水平.
- 确定通过皮肤进行的ISS预测与已确定的诊断标志物和ACS患者的成像发现的相关性.
主要方法:
- 一项前性研究招募了238名在五个临床场所住院患有ACS的患者.
- 一个深度学习模型是使用来自三个站点的透皮ISS数据开发的,并通过内部和外部验证.
- 对模型的性能进行了评估,根据已定诊断,hs-cTnI水平,心声学和冠状动脉血管学进行了评估.
主要成果:
- 通过皮肤-ISS深度学习模型在预测高hs-cTnI水平方面表现出高准确性,ROC曲线下的面积为0.90的内部验证和0.92的外部验证.
- 该模型在内部队列中获得了0.86的灵敏度和0.82的特异性,在外部队列中获得了0.94的灵敏度和0.64的特异性.
- 模型预测与区域壁运动异常和冠状动脉狭窄症显著相关,表明临床相关性.
结论:
- 手腕穿戴的透皮ISS在临床上是可行的,用于在疑似ACS患者中快速,非侵入性地预测升高的hs-cTnI水平.
- 这项技术显示出对心肌梗塞的临床生物标志物诊断的潜力.
- 通过皮肤进行的ISS可能有助于改善对呈现有暗示ACS的症状的患者的分拣.
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