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.

心力衰竭（HF）和心脏功能异常直接影响美国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，特别是对那些无症状疾病，是具有挑战性的。HF和伴随的肺动脉高压（PH）的有效诊断和管理需要准确测量四个血流动力学参数，包括射血分数（EF）、心输出量（CO）、肺动脉压（PAP）和肺毛细血管楔压（PCWP）。目前，通过超声心动图和心导管插入术的组合获得这些评估只能由经过专门培训的熟练医务人员进行。此外，心导管插入术是高度侵入性的，需要大量昂贵的资源，并且与患者的风险相关。存在对准确的、非侵入性的、低成本的血液动力学测量工具的未满足的需求，该血液动力学测量工具可以在没有专门培训的情况下操作，其准确性等同于心导管插入术和超声检查。这样的设备将能够实现更早、更安全、更经济的诊断，提高监测能力，更频繁地监测高危患者，并为临床医生指导治疗提供更好的临床决策支持。目前没有导管插入术的无创替代方法，目前也没有同时测量EF、CO、PAP和PCWP的技术。Sensydia公司正在开发一种用于血流动力学测量的低成本、非侵入性“心脏性能系统”（CPS），其目标是实现与金标准技术相当的准确性。CPS采集并自动分析来自一组易于应用的传感器的声学和心电图信号，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，使用专有算法来分析获取的信号。Sensydia已获得EF测量的510（k）许可;但是，需要进一步的算法开发和测试，以实现也可以测量CO、PAP和PCWP的系统，其精度相似。在该快速跟踪STTR项目的I期，将使用Sensydia/匹兹堡大学医学中心（UPMC）团队获得的CPS和导管插入数据的现有训练数据集进一步完善和测试PAP和PCWP算法，以满足临床使用的预期准确度阈值，并将基于Bland-Altman偏倚和一致性限值进行评估。与UPMC经验丰富的心脏病专家和麻醉师团队合作，CO、PAP和PCWP算法将在接受心导管插入术的患者的新的独立数据集中进行前瞻性验证。II期将重点展示术前临床环境中常规使用的临床效用和可行性。最后，将开发一个集成软件应用程序，用于报告CPS数据和基于AHA/ACC指南的诊断，并在UPMC医生的可用性研究中进行评估。