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Wearable alert system for detecting postoperative hypotension

Wearable alert system for detecting postoperative hypotension
用于检测术后低血压的可穿戴警报系统
批准号:
10760370
负责人:
Joshua Kim
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
项目状态:
未结题
起止时间:
2023-08-11 至 2025-02-10

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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.
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Beat-to-Beat Blood Pressure Monitoring During Sleep
  • 批准号:
    10449027
  • 项目类别:
  • 资助金额:
    $41.56万
  • 财政年份:
    2022
  • 负责人:
    Joshua Kim
  • 依托单位:
Beat-to-Beat Blood Pressure Monitoring During Sleep
  • 批准号:
    10629436
  • 项目类别:
  • 资助金额:
    $42.72万
  • 财政年份:
    2022
  • 负责人:
    Joshua Kim
  • 依托单位:
海外基金