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Identifying pre-sepsis opportunities for early, targeted intervention

确定败血症前早期、有针对性的干预的机会

基本信息

批准号：
10624036
负责人：
Vincent Liu
金额：
$ 46.18万
依托单位：
KAISER FOUNDATION RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2028-07-31
项目状态：
未结题

项目摘要

PROJECT SUMMARY Sepsis kills an estimated 11 million people worldwide every year. Sepsis also contributes to as many as 50% of US hospital deaths. Early treatment is the only universally recognized modifiable factor for improving sepsis mortality. Thus, current treatment guidelines focus heavily on early sepsis care immediately following hospital presentation. However, today, little is known about even earlier, pre-hospital, opportunities to predict, recognize, or treat sepsis. Our research program uses innovative translational informatics approaches to elucidate the presentation, pace, and profile of infection in pre-sepsis patients that could enable novel pre- hospital approaches designed to mitigate, or even prevent, sepsis. These pre-sepsis opportunities are now being recognized as a key new frontier of sepsis research and care. In this renewal, we will extend successful research that has begun to identify and characterize pre-sepsis opportunities for early, targeted intervention. To achieve this goal, we will leverage granular electronic health record (EHR) data, advanced informatics and artificial intelligence/machine learning methods, and the design of novel pre-sepsis care programs. Through this proposal, we will rigorously test sepsis prediction models in key clinical subgroups, prospectively validate the performance of pre-sepsis prediction models in real-time EHR platforms, and assess the value of additional screening and diagnostic modalities for pre-sepsis risk stratification. Our findings will have broad and immediate implications for patients, clinicians, and health systems to address this devastating condition. These results will also inform the design of sepsis public health programs and future prospective interventional studies aimed at improving outcomes for a condition that remains common, deadly, and costly.

项目摘要脓毒症每年在全世界造成约1100万人死亡。败血症也有助于多达50% 美国医院死亡早期治疗是唯一公认的改善脓毒症的可变因素 mortality.因此，目前的治疗指南主要集中在医院后立即进行的早期脓毒症护理演示文稿.然而，今天，人们对更早的、院前的、预测的机会知之甚少，识别或治疗败血症。我们的研究计划使用创新的翻译信息学方法，阐明脓毒症前患者感染的表现、速度和特征，旨在减轻甚至预防脓毒症的医院方法。这些脓毒症前的机会现在被认为是脓毒症研究和护理的关键新前沿。在这次更新中，我们将成功地研究已经开始识别和描述脓毒症前的早期有针对性的干预机会。为了实现这一目标，我们将利用精细的电子健康记录（EHR）数据、先进的信息学和人工智能/机器学习方法，以及新型脓毒症前护理计划的设计。通过根据这项提议，我们将在关键临床亚组中严格测试脓毒症预测模型，脓毒症前预测模型在实时EHR平台中的性能，并评估额外的脓毒症前风险分层的筛查和诊断模式。我们的发现将有广泛的，这对患者、临床医生和卫生系统解决这一毁灭性疾病的直接影响。这些研究结果也将为脓毒症公共卫生项目的设计和未来的前瞻性干预提供信息。旨在改善一种仍然常见、致命和昂贵的疾病的结果的研究。

项目成果

期刊论文数量（42）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Evaluation of an intervention targeted with predictive analytics to prevent readmissions in an integrated health system: observational study.

DOI：
10.1136/bmj.n1747
发表时间：
2021-08-11
期刊：
BMJ (Clinical research ed.)
影响因子：
0
作者：
Marafino BJ;Escobar GJ;Baiocchi MT;Liu VX;Plimier CC;Schuler A
通讯作者：
Schuler A

Development and Validation of an Obstetric Comorbidity Risk Score for Clinical Use.

DOI：
10.1089/whr.2021.0046
发表时间：
2021
期刊：
Women's health reports (New Rochelle, N.Y.)
影响因子：
0
作者：
Ruppel H;Liu VX;Kipnis P;Hedderson MM;Greenberg M;Forquer H;Lawson B;Escobar GJ
通讯作者：
Escobar GJ

Hospital Strain and Variation in Sepsis ICU Admission Practices and Associated Outcomes.