How Do We Choose? Predicting Utilization Of Cardiac Donors And The Effect Of Era
D. A. Baran1, J. T. Lansinger2, A. Long2, J. Philpott3, H. Copeland4, W. Old3, G. Zeevi3, C. Barreiro3, C. Kemp3, B. H. Smith3, K. Stelling3, A. Ingemi3, P. Bourassa3, J. M. Herre3
1Sentara Heart Hospital, Virginia Beach, VA, 2Eastern Virginia Medical School, Norfolk, VA, 3Sentara Heart Hospital, Norfolk, VA, 4University of Mississippi Medical Center, Jackson, MS
Meeting: 2019 American Transplant Congress
Abstract number: 299
Keywords: Age factors, Donors, unrelated, Heart, Risk factors
Session Information
Session Name: Concurrent Session: Donor and Recipient Selection in Heart Transplanation
Session Type: Concurrent Session
Date: Monday, June 3, 2019
Session Time: 2:30pm-4:00pm
Presentation Time: 3:18pm-3:30pm
Location: Room 206
*Purpose: The number of patients on the heart transplant waitlist continues to rise. However, the rate of organ acceptance is only about 1/3 of all organs considered for transplant. We wanted to explore the predictive factors for utilization of heart transplants and investigate whether they vary by era.
*Methods: We obtained the UNOS Standard Transplant Analysis and Research file through March 2018. We compared donors that were utilized for heart transplantation with those that were not, and divided by multiple factors in the UNOS database as well as by era of transplant. Eras were defined as 1987-1996, 1997-2006, and 2007- 2018. Additionally, we utilized multivariate nominal logistic regression to examine the factors predictive of utilization of heart donors for transplant.
*Results: From 1987 to March 2018 there were a total of 204999 organ donors in the United States. Of these, 71470 hearts (34.9 %) were accepted for transplant. The three tables below list donor factors, divided in two ways: First, whether the donor was utilized (“taken”) or not and then by the 3 eras in the database. All comparisons were highly significant (p<0.0001). In Table 1, donors utilized had consistently lower age, male preponderance and smaller BMI. More donors over time were Black race and had a history of hypertension. Anoxia was less common as a cause of death in the first era but rose significantly over the next 2 periods. CVA was quite common in the oldest era but became the least common in the final era. On Table 2, we see that donor angiography has been much more common and left ventricular hypertrophy and valve abnormalities have become modestly more common with greater increases for donor antihypertensives and tattoos. In Table 3, we note that utilization of donors who smoked has dropped dramatically while alcohol use has not changed and cocaine and other drug use has become much more common, along with Public Health Service Increased Risk status. For logistic regression, we included 29 UNOS fields, including donor factors such as era of transplant, age, gender, BMI, blood type, serum creatinine, cause of death, ethnic group, history of clinical infection, history of hypertension, diabetes, and valve disease. We examined whether the donor was considered Public Health Service Increased Risk, a history of tattoos, smoking, IV drug use, alcohol, cocaine or other illicit drugs. We looked at region of the country, donor need for inotropic support, and whether the donor had a coronary angiogram done as part of organ donation evaluation. The strongest predictors of the donor heart being used for transplant were donor age, donor coronary angiogram being performed, donor valve disease, left ventricular hypertrophy, cause of death, donor weight and gender. None of the social variables such as drugs, alcohol or smoking were significant predictors. Era of transplant was not a significant predictor of utilization of organs. We suspected that coronary angiogram was a surrogate for donor age (though some young drug donors might undergo coronary angiography). The mean age was 36.4 ± 18.9 without coronary angiogram and 46.4 ± 9 years with angiography (p<0.0001). We then removed the coronary angio term from the multivariate analysis since it was co-linear with donor age. Donor age remained the strongest predictor, with even higher strength but no new variables emerged as significant.
*Conclusions: The strongest predictor of heart transplant utilization regardless of era is donor age, with size of the donor and anatomic quality of the donor also highly associated with donor utilization. Given the young mean donor age, there is a significant opportunity to use donors of somewhat older age, particularly in those patients who may be willing to accept this compromise since young, perfect donors are relatively rare.
Era 1987-1996 | Era 1997-2006 | Era 2007-2018 | ||||
Donor Not Taken | Donor Taken | Donor Not Taken | Donor Taken | Donor Not Taken | Donor Taken | |
Donor Age | 36.6 +/- 19.8 | 26.7 +/- 13.3 | 44.2 +/- 19.1 | 28.5 +/- 14.5 | 45.3 +/- 17.1 | 28.2 +/- 14 |
Donor Male | 55.4% | 69.3% | 53.7% | 67.9% | 55.7% | 68.7% |
Donor BMI |
24.2 +/- 5.8
|
23.7 +/- 5.1 | 26.2 +/- 6.5 | 24.9 +/- 5.7 | 28.1 +/- 7.3 | 26.1 +/- 6.4 |
Donor White/Black | 80%/10.6% | 78.9%/10.6% | 72.3%/13.3% | 70.9%/12.4% | 68.1%/15.5% | 62.4%/17.3% |
Donor Hx of HTN | 27.6% | 8.9% | 36.4% | 10.2% | 44.0% | 12.7% |
Donor COD: Anoxia/CVA/Head Trauma | 9.8%/44.6%/28.7% | 5.6%/25.0%/44.1% | 14.2%/52.3%/30.2% | 10.3%/25.1%/61.5% | 32.8%/41.0%/23.2% | 27.1%/17.8%/52.1% |
Era 1987-1996 | Era 1997-2006 | Era 2007-2018 | ||||
Donor Not Taken | Donor Taken | Donor Not Taken | Donor Taken | Donor Not Taken | Donor Taken | |
Donor Coronary Angiogram Done | No Data | No Data | 5.7% | 12.0% | 9.6% | 25.8% |
Donor LVH | No Data | No Data | 26.0% | 9.4% | 21.9% | 8.1% |
Donor Abnormal Valves | No Data | No Data | 25.6% | 12.3% | 25.1% | 11.6% |
Donor on Antihypertensives | 12.8% | 10.1% | 16.4% | 14.4% | 22.6% | 27.5% |
Donor Tattoos Present | No Data | No Data | 10.3% | 14.6% | 30.7% | 41.7% |
Era 1987-1996 | Era 1997-2006 | Era 2007-2018 | ||||
Donor Not Taken | Donor Taken | Donor Not Taken | Donor Taken | Donor Not Taken | Donor Taken | |
Donor Hx Cigarette Use | 44.2% | 36.0% | 39.7% | 27.7% | 28.6% | 10.9% |
Donor Hx Heavy Alcohol Use | No Data | No Data | 17.5% | 13.4% | 18.5% | 13.6% |
Donor Hx Cocaine Use | No Data | No Data | 8.5% | 8.0% | 16.2% | 14.9% |
Donor Hx Other Drug Use | 12.4% | 18.6% | 18.5% | 25.0% | 33.9% | 40.9% |
Donor Hep C + | 3.5% | 1.6% | 4.8% | 0.9% | 7.1% | 0.6% |
Donor PHS Increased Transmission Risk | No Data | No Data | 8.3% | 7.8% | 15.4% | 16.1% |
To cite this abstract in AMA style:
Baran DA, Lansinger JT, Long A, Philpott J, Copeland H, Old W, Zeevi G, Barreiro C, Kemp C, Smith BH, Stelling K, Ingemi A, Bourassa P, Herre JM. How Do We Choose? Predicting Utilization Of Cardiac Donors And The Effect Of Era [abstract]. Am J Transplant. 2019; 19 (suppl 3). https://atcmeetingabstracts.com/abstract/how-do-we-choose-predicting-utilization-of-cardiac-donors-and-the-effect-of-era/. Accessed November 22, 2024.« Back to 2019 American Transplant Congress