Early Diagnosis of Heart Failure: A Perioperative Data-Driven Approach

项目摘要/摘要 候选人：迈克尔·马西斯博士是一位拥有麻醉学委员会证书的心胸麻醉师 和密歇根大学先进的围手术期超声心动图。通过完成T32 研究培训补助金，马西斯博士在患者围手术期结果研究方面积累了专业知识 患有晚期心血管疾病。他的长期职业目标是改善对心脏病患者的护理 通过利用围手术期电子医疗记录(EHR)数据进行早期诊断和 管理层。这项建议建立在马西斯博士的专业知识基础上，为数据培训提供了受保护的时间 必要的科学方法，推动提出的分析技术，以提高心力衰竭的诊断。 环境：密歇根大学是多中心围术期的协调中心 结果集团(MPOG)，一个由50多个麻醉和外科部门组成的国际财团 围手术期信息系统。萨钦·克尔特帕尔博士，医学博士，MBA，是马西斯博士的主要导师， 他是MPOG的主任和NIH精密医学倡议顾问小组的成员。这个 拟议中的研究将在Kherpal博士和共同导师Milo Engoren的指导下完成， 丹尼尔·克劳医学博士和凯文·纳贾里安博士。由心力衰竭诊断和数据专家组成的咨询小组 科学方法论将为马西斯博士提供额外的指导。 背景：心力衰竭是最常见的需要住院治疗的慢性疾病之一，其发病率很高 死亡率。在围手术期，心衰是主要心脏并发症的危险因素。尽管 在医疗保健方面取得了进展，但在减轻心力衰竭医疗负担方面进展甚微，困难可归因于 缺乏廉价、可靠的诊断方法。因此，患有心力衰竭的患者可能在 在早期阶段，不接受治疗以降低死亡率。围手术期未得到充分利用 提高心力衰竭诊断水平的机会。除了丰富的术前数据外，术中 作为心脏应激测试，血流动力学对手术和麻醉剂的反应 刺激是以高分辨率记录的。然而，这些数据仍然是高频评估的未开发资源。 研究：拟议研究的目标是将围手术期作为一个机会 心衰的早期诊断。这两个具体目标是开发一种数据驱动的HF诊断算法，使用 术前EHR数据(目标1)以及术中EHR数据(目标2)。这两个目标都将使用自动 从围术期EHR中提取心衰特征的技术，在密歇根大学开发，可扩展到多个 中心通过MPOG基础设施。这项工作代表了围手术期评估的范式转变，使用 围手术期数据作为诊断工具而不是风险评估工具。拟议的研究和培训 将为马西斯博士提供必要的数据科学计算经验，使其成为独立的 医生-研究者致力于改善心衰患者的围手术期管理策略。

PROJECT SUMMARY / ABSTRACT Candidate: Dr. Michael Mathis is a cardiothoracic anesthesiologist with board certification in anesthesiology and advanced perioperative echocardiography at the University of Michigan. Through completion of a T32 Research Training Grant, Dr. Mathis has developed expertise in perioperative outcomes research for patients with advanced cardiovascular disease. His long-term career goal is to improve care for patients with heart failure (HF) through harnessing perioperative electronic healthcare record (EHR) data for early diagnosis and management. This proposal builds on Dr. Mathis's expertise, providing protected time for training in data science methods necessary to drive forward the analytic techniques proposed for improving HF diagnosis. Environment: The University of Michigan is the coordinating center for the Multicenter Perioperative Outcomes Group (MPOG), an international consortium of over 50 anesthesiology and surgical departments with perioperative information systems. Dr. Sachin Kheterpal, MD, MBA is the primary mentor for Dr. Mathis, and is the Director for MPOG and member of the NIH Precision Medicine Initiative Advisory Panel. The proposed research will be completed under the guidance of Dr. Kheterpal, as well as co-mentors Milo Engoren, MD, Daniel Clauw, MD, and Kayvan Najarian, PhD. An advisory panel of experts in HF diagnosis and data science methodologies will provide Dr. Mathis with additional guidance. Background: HF is among the most common chronic conditions requiring hospitalization and carries high rates of mortality. In the perioperative period, HF is a risk factor for major cardiac complications. Despite advances in care, little progress has been made to reduce HF healthcare burden, with difficulties attributable to a lack of inexpensive, reliable diagnostic measures. Consequently, patients with HF can go unrecognized in early stages and do not receive treatments to reduce mortality. The perioperative period is an underutilized opportunity to improve HF diagnosis. Beyond the wealth of preoperative data available, the intraoperative period serves as a cardiac stress test through which hemodynamic responses to surgical and anesthetic stimuli are recorded with high resolution. Yet, this data remains an untapped resource for HF evaluation. Research: The goal of the proposed research is to incorporate the perioperative period as an opportunity for early diagnosis of HF. The two specific Aims are to develop a data-driven diagnostic algorithm for HF using preoperative EHR data (Aim 1) as well as intraoperative EHR data (Aim 2). Both aims will use automated techniques to extract features of HF from the perioperative EHR, developed at UM and scalable to multiple centers via the MPOG infrastructure. This work represents a paradigm shift in perioperative evaluation, using perioperative data as a diagnostic tool rather than a risk-assessment tool. The proposed research and training will provide Dr. Mathis with necessary data science computational experience to become an independent physician-investigator focused on improving perioperative management strategies for patients with HF.