CORA_TM_A Personalized Cardiac Counselor for Optimal Therapy

CORA_TM_最佳治疗的个性化心脏咨询师

• 批准号: 9675403
• 负责人: JAMES F. ANTAKI
• 金额: $ 81.46万
• 依托单位: CORNELL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-03 至 2020-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9675403
• 关键词: Address; Admission activity; Adverse effects; Adverse event; Affect; Algorithms; American; American Heart Association; Anxiety; Attitude; Belief; Benefits and Risks; Biomedical Engineering; Cardiac; Cardiac Surgery procedures; Cardiology; Caregiver Burden; Caregiver support; Caregivers; Caring; Cessation of life; Clinical; Clinical Data; Clinical Decision Support Systems; Collaborations; Colorado; Communication; Comprehension; Computer software; Computers; Congestive Heart Failure; Consensus; Consultations; Data; Databases; Decision Making; Decision Modeling; Dependence; Destinations; Devices; Disease; Dyspnea; Environment; Family; Family Caregiver; Foundations; Frequencies; Funding; Future; Guidelines; Health; Health Personnel; Heart failure; Heart-Assist Devices; Heart-Lung Transplantation; Hospitals; Imagery; Implant; Incidence; Infection; Institution; Intention; Interagency Registry for Mechanically Assisted Circulatory Support; International; Intervention; Interview; Knowledge; Lead; Length of Stay; Life; Life Expectancy; Machine Learning; Mechanics; Medical; Medical Ethics; Medicare; Mental Depression; Meta-Analysis; Morbidity - disease rate; Multicenter Studies; Multicenter Trials; Muscular Atrophy; Outcome; Palliative Care; Patient-Focused Outcomes; Patients; Physicians; Probability; Process; Professional counselor; Provider; Publishing; Quality of life; Risk; Risk Assessment; Savings; Societies; Stents; Stress; Stroke; Supervision; System; Technology; Time; Touch sensation; Training; Treatment Effectiveness; United States National Institutes of Health; Universities; Woman; Work; base; clinical research site; computer program; computer science; cost effectiveness; data mining; data visualization; design; discount; experience; implantable device; improved; individual patient; interactive tool; left ventricular assist device; literacy; medical specialties; meetings; mortality; multidisciplinary; non-compliance; optimal treatments; outcome forecast; patient response; predictive modeling; preference; prognostic; prospective; prototype; public health relevance; readmission rates; satisfaction; shared decision making; technology validation; tool; treatment planning; treatment strategy; usability; user-friendly; ventricular assist device; willingness

DESCRIPTION (provided by applicant): This project aims to introduce a clinical decision support system, CORA (Cardiac Outcomes Risk Assessment) for advanced heart failure (HF) a devastating disease affecting over 5 million Americans, and a leading cause of Medicare hospital admissions. The project specifically aims to moderate the deployment ventricular assist devices (VADs) which have been recently approved as destination (DT) such that patients most likely to benefit will be prioritized, while those better served with palliative care will be spare from unnecessary risks of debilitating side effects. The proposed system will leverage proven prognostic models based on advanced data mining and machine learning algorithms, and be packaged as a user-friendly computer application that would be used at key decision points in the course of treatment. It would provide both physician and patient with prognostic assessment based on the fusion of: patient-specific data, expert knowledge, and retrospective meta-analysis. This four-year project will develop a multi-platform software application that integrates modules for: forecasting, decision support, communication, decision making and visualization of data. This will be achieved through completion of four specific aims: (SA1) Expand existing inference (prognostic) algorithms and develop expert decision models to compute personalized estimate of life expectancy and risk of adverse events; (SA2) Create a computer application to assist patients to navigate their treatment options as they reflect their personal preferences and beliefs; (SA3) Incorporate these prognostic and decision models into user-friendly user interfaces for physicians, patients and their family caregivers; and (SA4) Conduct a multi- center study with respect to both qualitative and quantitative metrics of efficacy related to mortality, morbidity and quality of life. Training data capitalizing upon the NIH-funded Interagency Registry for Mechanical Circulatory Support (INTERMACS) as well as recently published guidance documents by the American Heart Association (AHA) and International Society of Heart & Lung Transplantation (ISHLT.) This project will involve a multi-disciplinary group of specialties including: bioengineering, advanced heart failure cardiology, cardiac surgery, computer science (machine learning/data mining), medical ethics, and palliative care. Carnegie Mellon University, one of the Nation's leading institutions for Computer Science will coordinate this project to assure a productive collaboration with four clinical sites: Allegheny Health Network (Pittsburgh), U. Colorado Denver, Duke University, and Harvard/Brigham & Women's hospital. By achieve consensus amongst stakeholders, we hope to assure the acceptance of CORA into practice and ultimately improve the efficiency, efficacy, and cost- effectiveness of the treatment of end-stage heart failure.

描述(由申请者提供)：该项目旨在为晚期心力衰竭(HF)引入临床决策支持系统CORA(心脏结果风险评估)，这是一种影响500多万美国人的破坏性疾病，也是联邦医疗保险入院人数的主要原因。该项目特别旨在缓和最近被批准为目的地(DT)的脑室辅助装置(VAD)的部署，以便最有可能受益的患者将被优先考虑，而那些得到更好姑息治疗的患者将免受不必要的削弱副作用的风险。拟议的系统将利用基于高级数据挖掘和机器学习算法的经过验证的预测模型，并打包为用户友好的计算机应用程序，将在治疗过程中的关键决策点使用。它将为医生和患者提供基于患者特定数据、专家知识和回顾性荟萃分析的融合的预后评估。这个为期四年的项目将开发一个多平台的软件应用程序，它集成了 用于：预测、决策支持、沟通、决策和数据可视化的模块。这将通过完成四个具体目标来实现：(SA1)扩展现有的推断(预测)算法，并开发专家决策模型，以计算预期寿命和不良事件风险的个性化估计；(SA2)创建一个计算机应用程序，以帮助患者导航他们的治疗选择，因为它们反映了他们的个人偏好和信念；(SA3)将这些预测和决策模型纳入医生、患者及其家庭照顾者的用户友好的用户界面；以及(SA4)对与死亡率、发病率和生活质量相关的疗效的定性和定量指标进行多中心研究。培训数据利用了NIH资助的机构间机械循环支持注册(INTERMACS)以及美国心脏协会(AHA)和国际心肺移植学会(ISHLT)最近发布的指导文件。该项目将涉及多个专业领域，包括：生物工程、高级心力衰竭心脏病学、心脏外科、计算机科学(机器学习/数据挖掘)、医学伦理学和姑息治疗。美国领先的计算机科学机构之一卡内基梅隆大学将协调这一项目，以确保与四个临床网站进行富有成效的合作：阿勒格尼健康网络(匹兹堡)、科罗拉多大学丹佛分校、杜克大学和哈佛/布里格姆和妇女医院。通过在利益相关者之间达成共识，我们希望确保CORA进入实践，并最终提高终末期心力衰竭治疗的效率、疗效和成本效益。

项目成果

Limitations of receiver operating characteristic curve on imbalanced data: Assist device mortality risk scores.

• DOI: 10.1016/j.jtcvs.2021.07.041
• 发表时间: 2023-04
• 期刊: The Journal of thoracic and cardiovascular surgery
• 作者: Movahedi F;Padman R;Antaki JF
• 通讯作者: Antaki JF

A Bayesian Model to Predict Survival After Left Ventricular Assist Device Implantation.

• DOI: 10.1016/j.jchf.2018.03.016
• 发表时间: 2018-09
• 期刊: JACC. Heart failure
• 作者: Kanwar MK;Lohmueller LC;Kormos RL;Teuteberg JJ;Rogers JG;Lindenfeld J;Bailey SH;McIlvennan CK;Benza R;Murali S;Antaki J
• 通讯作者: Antaki J

Timelines of adverse event journeys of LVAD patients.

LVAD 患者不良事件经历的时间表。

• DOI: 10.1111/aor.14596
• 发表时间: 2023
• 期刊: Artificial organs
• 影响因子: 2.4
• 作者: Movahedi,Faezeh;Kanwar,ManreetK;Antaki,JamesF
• 通讯作者: Antaki,JamesF

Risk Assessment in Patients with a Left Ventricular Assist Device Across INTERMACS Profiles Using Bayesian Analysis.

使用贝叶斯分析对 INTERMACS 档案中左心室辅助装置患者进行风险评估。

• DOI: 10.1097/mat.0000000000000910
• 发表时间: 2019
• 期刊: ASAIO journal (American Society for Artificial Internal Organs : 1992)
• 作者: Kanwar,ManreetK;Lohmueller,LisaC;Teuteberg,Jeffrey;Kormos,RobertL;Rogers,JosephG;Benza,RaymondL;Lindenfeld,Joann;McIlvennan,Colleen;Bailey,StephenH;Murali,Srinivas;Antaki,JamesF
• 通讯作者: Antaki,JamesF

Retrospective Evaluation of Bayesian Risk Models of LVAD Mortality at a Single Implant Center.

• DOI: 10.3389/fmed.2018.00277
• 发表时间: 2018
• 期刊: Frontiers in medicine
• 影响因子: 3.9
• 作者: Lohmueller LC;Kanwar MK;Bailey S;Murali S;Antaki JF
• 通讯作者: Antaki JF