A non-invasive, automated platform for hemodynamic assessment of patients at risk of heart failure or pulmonary hypertension

用于对有心力衰竭或肺动脉高压风险的患者进行血流动力学评估的无创自动化平台

• 批准号: 10699067
• 负责人: Anthony Arnold
• 金额: $ 60.55万
• 依托单位: SENSYDIA CORPORATION
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-05 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10699067
• 关键词: Acoustics; Activities of Daily Living; Adult; Affect; Agreement; Algorithms; Breakthrough device; Cardiac; Cardiac Catheterization Procedures; Cardiac Output; Cardiology; Cardiovascular system; Caring; Catheterization; Cause of Death; Cessation of life; Chest; Clinic; Clinical; Clinical Research; Collaborations; Computer software; Data; Data Set; Development; Devices; Diagnosis; Disease; EFRAC; Early Diagnosis; Early Intervention; Early treatment; Echocardiography; Effectiveness; Electrocardiogram; Family; Feedback; Freezing; Frequencies; Goals; Gold; Grant; Guidelines; Health Personnel; Healthcare; Healthcare Systems; Heart Abnormalities; Heart failure; Intervention; Left Ventricular Function; Machine Learning; Measurement; Measures; Medical; Medical center; Monitor; Morbidity - disease rate; Operative Surgical Procedures; Participant; Patient Care; Patient Recruitments; Patients; Performance; Perioperative Care; Persons; Phase; Physicians; Procedures; Process; Prospective Studies; Pulmonary Capillary Wedge Pressure; Pulmonary Hypertension; Reporting; Resources; Risk; Risk Factors; Safety; Signal Transduction; Skin; Small Business Technology Transfer Research; Symptoms; System; Techniques; Technology; Testing; Time; Training; Ultrasonography; United States Food and Drug Administration; Universities; Validation; Wedge Pressures; algorithm development; burden of illness; clinical decision support; clinical diagnosis; clinically relevant; commercialization; cost; electronic sensor; experience; heart function; hemodynamics; improved; intracardiac pressure; lung pressure; mortality; patient screening; programs; prospective; prototype; pulmonary arterial pressure; recruit; sensor; skills; software development; standard of care; tool; usability

PROJECT SUMMARY Heart failure (HF) and abnormal heart function directly affects 6 million people in the U.S. and is a leading cause of death. Early intervention is key to reducing mortality and morbidity, yet early diagnosis, particularly for those with asymptomatic disease, is challenging. Effective diagnosis and management of HF and accompanying pulmonary hypertension (PH) requires accurate measurement of four hemodynamic parameters, including ejection fraction (EF), cardiac output (CO), pulmonary artery pressure (PAP), and pulmonary capillary wedge pressure (PCWP). Currently obtained by a combination of echocardiography and cardiac catheterization these assessments can only be performed by skilled medical personnel with specialized training. In addition, cardiac catheterization is highly invasive, requires significant expensive resources, and is associated with risks to the patient. There is an unmet need for an accurate, non-invasive, low cost hemodynamic measurement tool that can be operated without specialized training with accuracy equivalent to cardiac catheterization and sonography. Such a device would enable earlier, safer, and more affordable diagnosis, improved surveillance capabilities, more frequent monitoring of at-risk patients, and better clinical decision support for clinicians in guiding therapies. Non-invasive alternatives to catheterization are not currently available, and there are no technologies that currently exist for simultaneous measurement of EF, CO, PAP and PCWP. Sensydia Corporation is developing a low cost, non-invasive “Cardiac Performance System” (CPS) for hemodynamic measurement with the goal of achieving comparable accuracy to that of gold-standard techniques. CPS acquires and automatically analyzes acoustic and electrocardiogram signals from a set of easily applied sensors to accurately measure EF, CO, PAP, and PCWP. Sensydia has developed fully functioning hardware and prototype software for CPS that uses proprietary algorithms to analyze the acquired signals. Sensydia has been granted 510(k) clearance for measurement of EF; however, further algorithm development and testing are required to achieve a system that can also measure CO, PAP, and PCWP with similar accuracies. In Phase I of this Fast- Track STTR project, PAP and PCWP algorithms will be further refined and tested to meet desired thresholds of accuracy for clinical use using an existing training dataset of CPS and catheterization data obtained by the Sensydia/University of Pittsburgh Medical Center (UPMC) team and will be assessed based on Bland-Altman bias and limits of agreement. In collaboration with a team of experienced cardiologists and anesthesiologists at UPMC, the CO, PAP and PCWP algorithms will then be prospectively validated in a new, independent dataset from patients undergoing cardiac catheterization. Phase II will focus on demonstrating clinical utility and feasibility of routine use in a preoperative clinic setting. Finally, an integrated software application for reporting CPS data and diagnosis based on AHA/ACC guidelines will be developed and assessed in a useability study with UPMC physicians.

项目摘要心力衰竭（HF）和异常心脏功能直接影响美国600万人，是死亡的主要原因。早期干预是降低死亡率和发病率的关键，但早期诊断，尤其是对于那些不对称疾病的诊断是挑战。 HF和参与肺动脉高压（PH）的有效诊断和管理需要精确测量四个血液动力学参数，包括射血分数（EF），心脏输出（CO），肺动脉压力（PAP）和肺毛细管楔形压力（PCWP）。目前，通过超声心动图和心脏导管插入术的结合，这些评估只能由熟练的医务人员和专门的培训进行。此外，心脏导管插入术具有很高的侵入性，需要大量昂贵的资源，并且与患者的风险有关。不需要精确，无创，低成本的血液动力学测量工具，该工具可以在没有专门的训练的情况下进行操作，其精度等同于心脏导管插入术和超声检查。这种设备将使较早，更安全，更负担得起的诊断能力，改进的监视能力，更频繁地监测高危患者，并为临床医生提供更好的临床决策支持。目前尚不可用进行导管插入的非侵入性替代方法，目前尚无用于同时测量EF，CO，PAP和PCWP的技术。 Sensydia Corporation正在开发低成本的非侵入性“心脏性能系统”（CPS）进行血液动力学测量，目的是实现与金标准技术相当的精度。 CPS从一组易于应用的传感器中获取并自动分析了声学和心电图信号，以准确测量EF，CO，PAP和PCWP。 Sensydia已为CPS开发了功能齐全的硬件和原型软件，该软件使用专有算法来分析获得的信号。 Sensydia已获得510（k）的清除，以测量EF；但是，需要进一步的算法开发和测试才能实现可以以相似精度测量CO，PAP和PCWP的系统。在这个快速轨道STTR项目的第一阶段，PAP和PCWP算法将得到进一步完善和测试，以满足使用CPS/Pittsburgh Medical Center（UPMC）的Sensydia/Sensydia/Sensydia/Seensydia/Seensydia/Cath插入数据的临床使用的预期阈值，并将根据Bland-Alttman Biass and Limits和Limits和Limits和Limits和Limits和Limits和Limits和Limits和Limits和Limits and Limits and Limits和Limits评估。随后，将与CO，PAP和PCWP算法与经验丰富的心脏病专家和麻醉师团队合作，并在接受心脏导管插入术的患者的新独立数据集中得到预期的验证。第二阶段将着重于术前诊所环境中证明临床实用性和常规使用的可行性。最后，将在与UPMC医生的使用研究中开发和评估一项基于AHA/ACC指南的CPS数据和诊断的集成软件应用程序。