PROTECT: optima4BP 2.0: prediction of Optimal Treatment and Route to achieve and maintain BP Target

保护:optima4BP 2.0:预测最佳治疗和路线以实现和维持血压目标

基本信息

  • 批准号:
    10159301
  • 负责人:
  • 金额:
    $ 71.6万
  • 依托单位:
  • 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:
    2018-05-01 至 2022-04-30
  • 项目状态:
    已结题

项目摘要

Need. In the US, 40 million patients with hypertension (HTN) have their blood pressure (BP) uncontrolled. BP above clinical Target even for a few months increases the risk for stroke (35-40%), heart failure (HF) (up to 64%), myocardial infarction (MI) (15-25%). Physician-nurse-pharmacist resource-intensive demonstrations in achieving & maintaining BP Target have shown promising results, but their real-life deployment was found unsustainable long-term. As a result, a process-standardized and sustainable solution is acutely needed. Solution. In response to this need, Optima Integrated Health developed optima4BP 1.0. It is a first-in-class artificial intelligence (AI) that simulates the process of clinical reasoning undertaken by the treating physician in optimizing the anti-HTN treatment towards BP Target. Just like the physician, optima4BP 1.0 cannot determine upfront the needed Optimal Treatment (OT) to achieve & maintain BP Target for 1-2 years. PROTECT [optima4BP 2.0: prediction of Optimal Treatment and route to achieve and maintain BP Target] proposes to establish upfront the personalized OT. The OT can then be used to select the shortest and safest treatment modification route needed to achieve & maintain BP Target. Phase II Goal. Build optima4BP 2.0. Phase I. Phase I Prior Work demonstrated that k-Nearest Neighbor (kNN), an AI model, can predict with ≥ 80% confidence the correct anti-HTN treatment, when compared to physician decision. Phase II. optima4BP 2.0 will predict the Optimal Treatment and route to achieve & maintain BP Target. Optimal Treatment data-mining source. PROTECT will use the SPRINT (Systolic Blood Pressure Intervention Trial, 2015) and ACCORD (Action to Control Cardiovascular Risk in Diabetes, 2010) clinical trial data. They represent the foundation of the most current anti-HTN treatment management national guidelines. Aim 1. Build kNN. Hypothesis. kNN can predict the proximity (clinical relevance) of a patient to an Optimal Treatment (OT). Milestone. Achieve ≥ 90% accuracy of prediction to physician decision. Phase I Data Preparation protocol will be applied to the SPRINT & ACCORD data. Then, the kNN Ensemble Learning function will be built to select the Optimal Treatment with the highest demonstrated efficacy by comparing the choice from 3 computational approaches developed and tested during Phase I. Aim 2. Build the Optimal Treatment Route (OTR). Hypothesis. Knowing the Current and Optimal Treatment (OT), an OTR can be built. Milestone. Safest Route: Achieve 100% exclusion of treatments that led to an adverse event in similar patient populations. Shortest Route: Achieve ≥30% reduction in number of treatment changes compared to physician route. The OTR will be built by comparing at each Step on the Route how similar each Candidate Treatment is to the OT through a computed similarity assessment. optima4BP 2.0 aims to establish a process-standardized & sustainable solution with the goal of reducing the incidence of stroke, HF, MI and death resulting from uncontrolled hypertension.
所需要的。在美国,4000万高血压患者(HTN)的血压(BP)没有得到控制。

项目成果

期刊论文数量(0)
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Gabriela Voskerician其他文献

Gabriela Voskerician的其他文献

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{{ truncateString('Gabriela Voskerician', 18)}}的其他基金

PERSEVERE-PEF: optimizing medical therapy saves lives in heart failure with preserved ejection fraction
PERSEVERE-PEF:优化药物治疗可挽救射血分数保留的心力衰竭患者的生命
  • 批准号:
    10641684
  • 财政年份:
    2022
  • 资助金额:
    $ 71.6万
  • 项目类别:
PERSEVERE-PEF: optimizing medical therapy saves lives in heart failure with preserved ejection fraction
PERSEVERE-PEF:优化药物治疗可挽救射血分数保留的心力衰竭患者的生命
  • 批准号:
    10381898
  • 财政年份:
    2022
  • 资助金额:
    $ 71.6万
  • 项目类别:
ARTERY Outcomes: tAilored dRug Titration through artificial intElligence: an inteRventional studY
动脉结果:通过人工智能定制药物滴定:一项干预性研究
  • 批准号:
    10001603
  • 财政年份:
    2019
  • 资助金额:
    $ 71.6万
  • 项目类别:
optima4heart: pharmacological intervention and transition of care in cardiovascular disease management
optima4heart:心血管疾病管理中的药物干预和护理转变
  • 批准号:
    9770702
  • 财政年份:
    2019
  • 资助金额:
    $ 71.6万
  • 项目类别:
PROTECT: optima4BP 2.0: prediction of Optimal Treatment and Route to achieve and maintain BP Target
保护:optima4BP 2.0:预测最佳治疗和路线以实现和维持血压目标
  • 批准号:
    9901106
  • 财政年份:
    2018
  • 资助金额:
    $ 71.6万
  • 项目类别:
Tailored Drug Titration through Artificial Intelligence
通过人工智能定制药物滴定
  • 批准号:
    9341533
  • 财政年份:
    2017
  • 资助金额:
    $ 71.6万
  • 项目类别:
Personal Mobile Diabetes Management System(PMDMS): IN-TRACK
个人移动糖尿病管理系统(PMDMS):IN-TRACK
  • 批准号:
    8311248
  • 财政年份:
    2012
  • 资助金额:
    $ 71.6万
  • 项目类别:

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