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

基本信息

批准号：
10641684
负责人：
Gabriela Voskerician
金额：
$ 124.64万
依托单位：
OPTIMA INTEGRATED HEALTH, INC.
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-15 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10641684
关键词：
Address Affect Algorithms American Area Atrial Fibrillation Automobile Driving California Cardiology Caring Cessation of life Clinical Complex Confidential Information Consumption Coronary Arteriosclerosis Data Element Development Diagnosis Disease Disease Management Dissemination and Implementation EFRAC Electronic Health Record Environment Evidence based intervention Expert Systems Guidelines Health Personnel Health system Heart Diseases Heart failure Home Hospitalization Hospitals Hypertension Incidence Individual Intelligence Judgment Left Liquid substance Logic Managed Care Medical Methodist Church Monitor Needs Assessment Organ Patients Pharmacology Process Protocols documentation Randomized Recommendation Records Sampling San Francisco Services Site Software Validation Standardization Syndrome Testing Time Treatment Efficacy Universities Visualization Voting Work adjudication care coordination clinical care clinical research site cohort college community clinic comorbidity cost data cleaning digital experience health data hospitalization rates hypertension control improved improved outcome interoperability meetings mortality personalized care post-COVID-19 preservation regression algorithm response system architecture treatment optimization volume hypertension

项目摘要

Need. In the US, heart failure (HF) is the contributing cause of 1 in 8 deaths. HF with preserved ejection fraction (HFpEF) affects close to 50% of all HF patients. The 5-years mortality is 35%. HFpEF multi-organ syndrome clinical care management is complex and time consuming. In addressing HFpEF, the American College of Cardiology guidelines directed medical therapy (GDMT) references the medical therapy decision to the individual disease guidelines [hypertension (HTN), coronary artery disease (CAD), atrial fibrillation (AFib)]. Providing concerted multi-disease HFpEF management is a major unmet clinical need. Solution. In response to this need, we (OPTIMA) developed and demonstrated the feasibility of a clinical analytic intelligence (AI) for the management of HFpEF multi-organ syndrome, optima4PEF AI. The solution adds significant value to OPTIMA’s HF Management Service currently addressing the GDMT management of HTN (optima4BP AI) and HFrEF (optima4heart AI). optima4PEF deconstructs a complex set of disease- specific clinical guidelines and re-assembles them into a concerted multi-disease GDMT that is patient- personalized, explainable, and actionable. Objectives. PERSEVERE-PEF [optimizing medical therapy saves lives in heart failure with preserved ejection fraction] proposes to complete the AI development of optima4PEF product concept, and to validate its efficacy using contemporary, diverse, retrospective patient cohorts. Aim 1. Build optima4PEF AI to address the GDMT management of HFpEF multi-organ syndrome. Hypothesis. optima4PEF deconstructs a complex set of disease-specific clinical guidelines and re-assembles them into a concerted multi-disease GDMT that is patient-personalized, explainable, and actionable. The product concept work built the optima4PEF AI system architecture and developed the decision logic to address GDMT management for patients experiencing HFpEF + volume overload + HTN. optima4PEF product concept will be extended to include GDMT management of AFib and of CAD. An end-to-end algorithm regression test will be performed to verify that each decision logic step performs its intended function. Aim 2. Validate optima4PEF AI in recommending the most relevant GDMT. Hypothesis. In ≥ 90% of patient cases, optima4PEF case-specific treatment recommendation is ACCEPTED as the appropriate next step in the process of multi-disease GDMT treatment optimization of patients diagnosed with HFpEF. Unidentified patient records will be collected from 4 clinical partner sites. A randomization algorithm will select n=840 patient records. optima4PEF will generate a Treatment Action (TA) for each patient record. A simple majority rule of pharmacology and cardiology experts (n=5) will adjudicate the optima4PEF TA. optima4PEF averts loss of lives by assisting in the delivery of HFpEF multi-disease management. optima4PEF surveillance & personalized care support the emerging digital-first clinical care practices.

需要。分数（HFPEF）影响了所有HF患者的近50％。综合症临床护理管理很复杂且耗时。心脏病学指南指示医疗治疗（GDMT）的医疗治疗决定个体疾病指南[高血压（HTN），冠状动脉疾病（CAD），心房颤动（AFIB）]。提供一致的多疾病HFPEF管理是一项主要的未满足的临床需求。解决方案。 HFPEF多器官综合征的管理分析智能（AI），Optima4pef AI 为Optima的HF管理服务增加了重大价值，目前解决了GDMT管理 HTN（Optima4bp AI）和HFREF（Optima4heart AI）。具体的临床准则并将其重新组装为个性化，可以解释和可行。目标。分数]建议迫使Optima4Pef产品概念的AI开发，并验证ETS效率使用当代，多样化的回顾性患者队列。 AIM 1。构建Optima4pef AI，以解决HFPEF多器官综合征的GDMT管理。卫生术。它们成为一个协同的多疾病GDMT，该GDMT是患者个性化，可以解释且可操作的。产品概念工作构建了Optima4Pef AI系统体系结构，并将决策逻辑开发到解决患者的GDMT管理经历HFPEF +量超载 + HTN 概念将扩展到AFIB和CAD的GDMT管理回归测试将通过执行，以验证每个决策逻辑步骤是否执行其预期功能。目标2。患者案例，Optima4Pefic治疗补充治疗建议是可观的在诊断为HFPEF的患者的多疾病中GDMT治疗优化的过程中迈出了一步。身份不明的患者记录将从4个临床伴侣中收集。 n = 840个患者记录。药理学和心脏病专家的多数规则（n = 5）将裁定Optima4pef TA。 Optima4Pef通过提供HFPEF多疾病管理来避免丧生。 Optima4PEF监视和个性化护理支持新兴的数字临床护理实践。