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：
9901106
负责人：
Gabriela Voskerician
金额：
$ 75.02万
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/9901106
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。在美国，有4000万例高血压患者（HTN）无法控制其血压（BP）。即使在几个月内，BP即使在临床目标上都增加了中风的风险（35-40％），心力衰竭（HF）（直到 64％），心肌梗塞（MI）（15-25％）。医师 - 武术主义者资源密集型演示实现和维护BP目标已显示出希望的结果，但发现了他们的现实部署长期不可持续的。结果，急需一个过程标准化和可持续的解决方案。解决方案。为了应对这种需求，Optima Integrated Health开发了Optima4bp 1.0。这是一流的人工智能（AI）模拟了治疗医师在优化针对BP靶标的抗HTN处理。就像物理一样，Optima4bp 1.0无法确定预先进行所需的最佳治疗（OT），以实现和维持BP目标1 - 2年。保护 [Optima4bp 2.0：预测最佳治疗和实现BP目标的途径] 建立个性化的OT。然后可以使用OT选择最短，最安全的治疗实现和维护BP目标所需的修改路线。第二阶段目标。构建Optima4bp 2.0。第一阶段I的先前工作证明了K-Nearest邻居（KNN）是AI模型，可以预测≥ 与身体决策相比，80％信心正确的抗HTN治疗方法。第二阶段。 Optima4bp 2.0将预测实现和维护BP目标的最佳处理和途径。最佳处理数据挖掘来源。保护将使用冲刺（收缩压）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。它们代表了最新的反HTN治疗管理国家准则的基础。目标1。建立KNN。假设。 KNN可以预测患者与最佳的邻近性（临床相关性）治疗（OT）。里程碑。实现预测物理决策的准确性≥90％。第一阶段数据准备协议将应用于Sprint＆Accord数据。然后，KNN合奏学习通过比较从第1阶段开发和测试的3种计算方法中选择。目标2。建立最佳治疗路线（OTR）。假设。了解当前和最佳治疗（OT），可以构建OTR。里程碑。最安全的路线：100％排除导致的治疗在类似的患者人群中发生不良事件。最短路线：减少≥30％与物理途径相比，治疗变化。 OTR将通过在每个步骤上进行比较路线通过计算的相似性评估，每种候选治疗与OT的相似程度相似。 Optima4bp 2.0旨在建立一个流程标准化和可持续的解决方案，目的是减少了不受控制的高血压导致中风，HF，MI和死亡的事件。