CORA_TM_A Personalized Cardiac Counselor for Optimal Therapy

CORA_TM_最佳治疗的个性化心脏咨询师

基本信息

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
项目类别：
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

项目摘要

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（由申请人提供）：该项目旨在引入临床决策支持系统，CORA（心脏结局的风险评估），以进行晚期心力衰竭（HF）一种毁灭性疾病，影响了超过500万美国人，以及医疗保险住院的主要原因。该项目专门旨在调节最近被批准为目的地（DT）的部署心室辅助设备（VAD），以使患者最有可能受益的患者将得到优先级，而那些更好地使用姑息治疗的患者将摆脱不必要的副作用的不必要风险。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后模型，并将其作为用户友好的计算机应用程序包装，在治疗过程中将在关键决策点使用。它将基于以下方式融合：特定于患者的数据，专家知识和回顾性荟萃分析，为医师和患者提供预后评估。这个为期四年的项目将开发一个多平台软件应用程序，该应用程序集成用于：数据的预测，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）扩大现有推理（预后）算法并开发专家决策模型，以计算预期寿命的个性化估计和不良事件的风险；（SA2）创建计算机应用程序，以帮助患者在反映其个人偏好和信念时浏览其治疗选择；（SA3）将这些预后和决策模型纳入用于医生，患者及其家庭护理人员的用户友好用户界面；（SA4）就与死亡率，发病率和生活质量有关的疗效的定性和定量指标进行了多个中心研究。培训数据利用了NIH资助的机械循环支持（Intermacs）的机构间登记处，以及美国心脏协会（AHA）和国际心脏和肺部国际学会（ISHLT）最近发布的指导文件（ISHLT。道德和姑息治疗。卡内基·梅隆大学（Carnegie Mellon University）是美国领先的计算机科学机构之一，将协调该项目，以确保与四个临床站点进行富有成效的合作：Allegheny Health Network（匹兹堡），美国科罗拉多州丹佛，杜克大学，哈佛大学/布里格姆和妇女医院。通过在利益相关者之间达成共识，我们希望确保接受Cora的接受，并最终提高终末期心力衰竭治疗的效率，功效和成本效益。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

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
影响因子：
0
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
影响因子：
0
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)
影响因子：
0
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

Sequential Pattern Mining of Longitudinal Adverse Events After Left Ventricular Assist Device Implant.

DOI：
10.1109/jbhi.2019.2958714
发表时间：
2020-08
期刊：
IEEE journal of biomedical and health informatics
影响因子：
7.7
作者：
Movahedi F;Kormos RL;Lohmueller L;Seese L;Kanwar M;Murali S;Zhang Y;Padman R;Antaki JF
通讯作者：
Antaki JF