Project Grant R01HL169798

Award Date 4/11/24
Completion Date 1/31/28
Dollars Obligated $3.2M
Federal Grant Program
93.837
Assistance Type
Project Grant
Place of Performance
New York, USA
Similar Awards
This federal Project Grant award from the Center for Evidence and Practice Improvement (CFDA 93.226 - Research on Healthcare Costs, Quality and Outcomes) will fund the development of predictive models and a decision support tool to optimize pediatric donor heart utilization and reduce waitlist mortality. The University of Virginia will receive $138,009 from September 2024 to September 2026 to: 1) create machine learning models to assess post-transplant survival and waitlist survival for...
This federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) aims to leverage multi-omic profiling technologies to identify novel pre-transplant biomarkers associated with the risk of acute rejection in heart transplant recipients. The $554,737 award to the University of Texas Southwestern Medical Center will fund the validation of three previously identified protein biomarkers (FGF-2, SPRY-2, IRAK-1) and the exploration of...
This $1,527,766 Project Grant awarded by the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) seeks to develop, validate, and demonstrate the impact of a novel in-hospital mortality prediction model (MPM) that optimizes fairness across key subgroups defined by demographic and socioeconomic factors. The objectives are to: Develop fairness-informed in-hospital MPMs by identifying predictive features, assessing missing data bias, and implementing bias...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $1,800,000 to Missouri University of Science & Technology to develop an artificial intelligence decision support system for kidney transplant healthcare. The goal is to reduce kidney discard rates by at least 10% by embedding preferences and fairness considerations into AI models used to match donor kidneys with transplant centers. Two subawards totaling $XXX,XXX are provided to Saint...
This federal Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $1,790,599.00 to the University of Pittsburgh to develop an automated frailty scoring system for lung transplantation patients. The key objectives are to systematically validate a "bio-geo-composition" concept as a biomarker for assessing lung transplant candidates, and to create the "Pittsburgh Transplant Fitness...
This Project Grant award of $799,354 from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) aims to comprehensively understand and pharmacologically target the necroptotic pathways in both the donor and recipient lungs to reduce the incidence of primary graft dysfunction (PGD) in lung transplantation. The research has two specific aims: 1) Exploring the role of TNF-α-induced autocrine necroptosis in monocyte-derived alveolar...
This $1,564,220 Project Grant awarded by the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) will support research to develop an imaging-compatible ex vivo lung perfusion (EVLP) system for assessing structural, functional, and metabolic biomarkers in donor lungs. The goal is to optimize EVLP parameters and apply injury-specific treatment strategies to recondition "marginal" donor lungs with defects like atelectasis,...
This Project Grant from the National Institute for Minority Health and Health Disparities, part of the Department of Health and Human Services National Institutes of Health, provides $769,755 to develop an unbiased machine learning tool for the prediction of acute coronary syndrome. The tool aims to minimize bias in predictions between patient demographic groups, as measured by equal opportunity difference and the Zemel statistic, to ensure machine learning algorithms do not exacerbate...
This Project Grant award from the National Heart Lung and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) provides $1,411,136 to The Washington University in St. Louis to study the role of circadian rhythms in organ transplantation. The key objectives are to: Develop a model to predict biological rhythms and circadian clock function in organ donors, leveraging a partnership with the Mid-America Transplant Services organ procurement organization. This will generate the first...
This federal Project Grant award, provided by the National Institute of Diabetes and Digestive and Kidney Diseases (CFDA 93.847 - Diabetes, Digestive, and Kidney Diseases Extramural Research), will fund a 5-year research project led by Dr. Carrie Thiessen at the University of Wisconsin-Madison. The $193,652 award aims to assess the impact of cognitive biases on patient and provider willingness to accept imperfect kidneys for transplantation. The project has three key objectives: Characterize the...

OPTIMIZING THE ALLOCATION OF HEARTS FROM DECEASED DONORS - PROJECT ABSTRACT IN 2018, HEART ALLOCATION MOVED FROM USING THREE STATUSES TO SIX STATUSES, BUT THE PRIORITY GROUPS REMAIN UNDIFFERENTIATED AND LARGE, ONLY COARSELY REFLECTING EACH CANDIDATE'S RISK OF DEATH ON THE WAITING LIST. THE NEW SYSTEM AIMED TO REDUCE EXCEPTION REQUESTS AND MORE ACCURATELY RANK CANDIDATES; INSTEAD, EXCEPTIONS, WHICH MIGHT BE SUBJECTIVELY OR INAPPROPRIATELY ASSIGNED, HAVE RISEN TO COMPRISE 30% OF HEART TRANSPLANTS. THE SYSTEM ALSO INCENTIVIZED DRAMATIC CHANGES IN CLINICAL PRACTICE: BECAUSE INTRAORTIC BALLOON PUMPS YIELD HIGHER PRIORITY FOR TRANSPLANT, BALLOON PUMP USAGE INCREASED THREE-FOLD EVEN THOUGH BALLOON PUMPS ARE ASSOCIATED WITH INCREASED RISK OF NEUROLOGIC COMPLICATIONS. OTHER DISPARITIES PERSIST: SENSITIZED CANDIDATES WAIT FOUR TIMES AS LONG FOR TRANSPLANTS BUT GET NO INCREASED PRIORITY FOR HEARTS, IN CONTRAST TO INCREASED KIDNEY PRIORITY FOR SENSITIZED CANDIDATES. OUR STUDY WILL FIRST DESCRIBE THE LANDSCAPE OF DISPARITIES IN HEART TRANSPLANT, DIAGNOSING WHETHER TRANSPLANTS ARE EQUALLY AVAILABLE TO CANDIDATES WHO ARE SENSITIZED, OF SMALLER OR LARGER SIZE, AND OF DIFFERENT RACES AND ETHNICITIES. WE WILL ALSO DETERMINE WHETHER EXCEPTION STATUSES ARE JUSTIFIED BY CANDIDATES' INDIVIDUAL RISKS OF WAITLIST DEATH, AND WHETHER EXCEPTIONS ARE BEING REQUESTED AND GRANTED IN AN EQUITABLE FASHION. WE WILL USE MACHINE LEARNING TO BUILD A MESH (MODEL FOR END STATE HEART DISEASE) SCORE THAT PREDICTS DEATH ON THE WAITLIST FOR HEART TRANSPLANT CANDIDATES FROM NATIONAL DATA. AN INDIVIDUALIZED MESH SCORE BASED ON HEMODYNAMIC CRITERIA IN THE CONTEXT OF CARDIAC PATHOLOGY, END ORGAN FUNCTION, CAUSE OF HEART FAILURE, AND ELIGIBILITY FOR MECHANICAL CIRCULATORY SUPPORT THERAPIES WOULD BETTER PRIORITIZE HEART TRANSPLANT CANDIDATES TO REDUCE WAITLIST DEATHS WITHOUT DISTORTING CLINICAL PRACTICE. IMPLEMENTING AN ANALOGOUS LUNG ALLOCATION SCORE IN 2005 REDUCED WAITLIST DEATHS FROM 500 TO 300 PER YEAR, SO THIS CHANGE IS OVERDUE IN HEART ALLOCATION. FINALLY, WE WILL DESIGN A COMPOSITE ALLOCATION SCORE FOR HEARTS. THE ORGAN PROCUREMENT AND TRANSPLANTATION NETWORK HAS RESOLVED TO REPLACE THE 250 AND 500 MILE CIRCLES IN CURRENT POLICY WITH CONTINUOUS DISTRIBUTION BY IMPLEMENTING A COMPOSITE ALLOCATION SCORE. A COMPOSITE ALLOCATION SCORE IS A WEIGHTED COMBINATION OF MEDICAL URGENCY (MESH), WITH DISTANCE BETWEEN DONOR AND CANDIDATE, AND OTHER PRIORITY CONSIDERATIONS LIKE BLOOD TYPE, CANDIDATE AND DONOR SIZE, SENSITIZATION, AND PRIORITY FOR PRIOR LIVING DONORS. HOWEVER, ELIMINATING GEOGRAPHIC BOUNDARIES IN THIS WAY CREATES AN ENORMOUS COMBINATORIAL DESIGN SPACE WITH COMPLEX TRADEOFFS. WE WILL USE SIMULATION OPTIMIZATION TO EXPLORE MANY POSSIBLE CHOICES FOR THE NUMERICAL WEIGHTS USING CLINICALLY DETAILED SIMULATIONS, GUIDED BY A DIFFERENTIAL EVOLUTION ALGORITHM. OUR TEAM IS EXCEPTIONALLY WELL-SUITED TO THE TASK, WITH DEDICATED QUANTITATIVE SCIENTISTS WHO HAVE YEARS OF COLLABORATIVE EXPERIENCE ADVANCING TRANSPLANTATION PARTNERING WITH CLINICIANS OF A SUPERIOR HEART TRANSPLANT PROGRAM. THE PROPOSED RESEARCH WOULD CORRECT AN ARBITRARY AND COARSE PRIORITIZATION SCHEME, BY ESTABLISHING A VALIDATED HEART ALLOCATION SCORING SYSTEM THAT REDUCES WAITLIST DEATHS AND INCREASES EQUITY IN HEART ALLOCATION.

Posted 4/11/24, 12:00 AM