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：
Gabriela Voskerician
金额：
$ 71.6万
依托单位：
OPTIMA INTEGRATED HEALTH, INC.
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

来源：
https://reporter.nih.gov/project-details/10159301
关键词：
Acute Adverse drug event Adverse event Antihypertensive Agents Artificial Intelligence Blood Pressure California Cessation of life Clinical Clinical Trials Confidential Information Data Development Diabetes Mellitus Diagnosis Drug Combinations Enrollment Euclidean Space Exclusion Foundations Gender Generations Goals Guidelines Health Heart failure Hypertension Incidence Individual Intervention Intervention Trial Learning Life Lipids Logic Medical center Mind Modeling Modification Myocardial Infarction Names Nature Nurses Outcome Patients Performance Pharmaceutical Preparations Pharmacists Pharmacological Treatment Pharmacotherapy Phase Physicians Preparation Process Protocols documentation Resources Route Safety San Francisco Seminal Source Standardization Stroke Testing Time Training Universities Visit Women&apos s Health Women&apos s Role Work base blood pressure intervention cardiovascular risk factor clinical care clinically relevant commercial application comparative efficacy data mining data quality hypertension treatment innovation optimal treatments patient population prevent processing speed response stroke incidence stroke risk success

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.

需要。关于临床目标的BP即使几个月来增加中风的风险（35-40％），心力衰竭（HF） 64％），心肌梗塞（MI）（15-25％）。实现和维护BP目标已显示出令人鼓舞的结果，但发现了他们的现实部署结果，不可持续的是，急需过程标准化和可持续的解决方案。解决方案。人工智能（AI）模拟了治疗医师在像医师一样，优化针对BP目标的抗HTN处理。前期需要最佳治疗（OT），以实现和维护1-2个Youars的BP目标 [Optima4bp 2.0：预测最佳治疗和实现和维护BP目标的途径] 预先建立个性化的OT。修改路线需要实现和维护II阶段目标。第一阶段I Priork证明了k-nearest邻居（KNN），AI模型，可以预测≥ 80％的信心正确的抗HTN治疗，同时决定。 II阶段。最佳处理数据挖掘源将使用Sprint（系统血液压力干预试验，2015年）和协议（糖尿病中控制心血管风险的行动，2010年）临床试验数据。 AIM 1。构建KNN。治疗（OT）然后将其应用于Sprint＆Accord数据。通过比较从第1阶段开发和测试的3种计算方法中的选择。 AIM 2。建立最佳治疗途径（OTR）。治疗（OT），可以建立一个最安全的路线。在类似的患者中发生不良事件。与医师路线相比，将通过比较路线路线与同样的相似性评估与OT相似。 Optima4bp 2.0旨在建立一个流程标准化和可持续的解决方案，目的是减少了由不受控制的高血压导致的中风，HF，MI和死亡的发生率。