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
- 来源:
- 关键词:Acute Renal Failure with Renal Papillary NecrosisAddressAnesthesia proceduresArterial LinesBlood PressureCardiacCaregiversCaringCessation of lifeCost efficiencyDataDetectionDeteriorationDevicesDropsEarly DiagnosisEnvironmentEventFollow-Up StudiesFrequenciesFundingGeneral WardHospitalsHourHypotensionHypotensivesHypoxemiaIntensive Care UnitsInterventionLocationManualsMeasuresMethodsModelingMonitorNotificationNursesOperating RoomsOperative Surgical ProceduresPalpablePatient MonitoringPatient-Focused OutcomesPatientsPersonal SatisfactionPhasePhysiologic pulsePilot ProjectsPostoperative PeriodRecoveryReportingResourcesRiskSensitivity and SpecificitySignal TransductionSmall Business Innovation Research GrantSpottingsStrokeSystemTechnologyTimeUnited States National Institutes of Healthcardiac intensive care unitcaregiver interventionscerebrovascularclinical careclinical practicecostdetection platformexperiencefallsfeasibility testinghemodynamicshigh riskhospital readmissionimprovedmachine learning classifiermachine learning modelmyocardial injurynon-invasive monitorpressurepreventrisk of major adverse eventsrisk stratificationstandard of carewardwearable devicewireless
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.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(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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