Wearable alert system for detecting postoperative hypotension

用于检测术后低血压的可穿戴警报系统

基本信息

  • 批准号:
    10760370
  • 负责人:
  • 金额:
    $ 29.59万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-08-11 至 2025-02-10
  • 项目状态:
    未结题

项目摘要

Project Summary This project aims to develop a low-cost, comfortable, and easy-to-use wearable alert system that tracks continuous BP non-invasively in patients to notify caregivers of hypotensive events in the postoperative setting. Postoperative hypotension (POH), when a patient’s mean arterial pressure (MAP) falls to unsafe levels, commonly <70 mmHg, can occur frequently in the time span between leaving the operating room and prior to discharge from the hospital. POH is a serious and common condition that has been shown to be independently associated with poor patient outcomes such as acute kidney injury, stroke, hospital re-admission, myocardial injury, and death.1–9 During surgery and recovery in the post anesthesia care unit (PACU) or the intensive care unit (ICU), a patient’s hemodynamics are closely monitored to support timely interventions and treatment. However, once the patient is transferred to a lower ward for recovery, patient monitoring is dramatically reduced. The current method to monitor a patient’s BP in the general ward, which relies on intermittent spot-checks performed manually every 4-6 hours by the nurse using an oscillometric BP cuff, is insufficient for detecting POH events. A recent study showed that almost 50% of hypotensive events went undetected by routine vital assessments. There is an unmet need for a technology that comfortably monitors a patient’s BP in the postoperative setting. Our core technology is able to non-invasively measure rapid BP changes at any location with a palpable pulse. The proposed project aims build upon the core technology to create a wearable alert system that informs caregivers of postoperative hypotensive episodes. To do so, a machine learning (ML) classifier for detection of hypotensive episodes will be developed through monitoring in the ICU. This ML classifier will undergo feasibility testing in the PACU and then a pilot study in the general ward. Successful completion of the proposed aims will result in a proof- of-concept wearable alert system that continuously monitors BP in the postoperative environment in a low-profile, wireless, and comfortable manner. Such a technology has huge potential to change clinical practice through earlier detection of patient deterioration, allowing more timely intervention and ultimately improved patient outcomes.
项目摘要 该项目旨在开发一种低成本,舒适,易于使用的可穿戴警报系统, 非侵入性地跟踪患者的连续BP, 术后设置。术后低血压(POH),当患者的平均动脉压 (MAP)福尔斯下降到不安全的水平,通常<70 mmHg,可能经常发生在 离开手术室和出院前。POH是一种严重而常见的 已被证明与不良患者结局独立相关的疾病, 急性肾损伤、中风、再次入院、心肌损伤和死亡。1 -9 在麻醉后监护室(PACU)或重症监护室(ICU)进行手术和恢复, 密切监测患者的血流动力学,以支持及时的干预和治疗。 然而,一旦患者被转移到较低的病房进行恢复, 急剧减少。目前在普通病房监测病人血压的方法, 依赖于护士每4-6小时手动进行的间歇性抽查, 血压计袖带不足以检测POH事件。最近的一项研究表明, 50%的过敏事件未被常规生命体征评估检测到。存在未满足的 需要一种在术后环境中舒适地监测患者血压的技术。我们 核心技术能够在任何位置非侵入性地测量快速BP变化, 可触知的脉搏拟议项目旨在建立在核心技术的基础上, 警报系统,告知护理人员术后的痉挛发作。为此,一台机器 将通过以下方式开发用于检测癫痫发作的ML分类器: ICU中的监控。该ML分类器将在PACU中进行可行性测试,然后进行 在普通病房进行试点研究。成功完成拟议目标将证明- 概念可穿戴警报系统,可在术后环境中持续监测BP 以一种低调、无线和舒适的方式。这种技术具有巨大的潜力, 通过更早地检测患者病情恶化来改变临床实践, 干预,最终改善患者的预后。

项目成果

期刊论文数量(0)
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Joshua Kim其他文献

Joshua Kim的其他文献

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{{ truncateString('Joshua Kim', 18)}}的其他基金

Beat-to-Beat Blood Pressure Monitoring During Sleep
睡眠期间逐次血压监测
  • 批准号:
    10449027
  • 财政年份:
    2022
  • 资助金额:
    $ 29.59万
  • 项目类别:
Beat-to-Beat Blood Pressure Monitoring During Sleep
睡眠期间逐次血压监测
  • 批准号:
    10629436
  • 财政年份:
    2022
  • 资助金额:
    $ 29.59万
  • 项目类别:

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