Donation After Circulatory Death Significantly Reduces Waitlist Times While Not Changing Post-Heart Transplant Outcomes: A United Network for Organ Sharing Analysis

Abstract

Objective:

Recently, several centers in the US have begun performing donation after circulatory death (DCD) heart transplants (HT) in adults. We sought to characterize the recent use of DCD HT, waitlist-time, and outcomes compared to donation after brain death (DBD).

Methods:

Using the UNOS database, 10,402 adult (>18yo) HT recipients from January 2019-June 2022 were identified: 425(4%) were DCD and 9,977(96%) were DBD recipients. Post-transplant outcomes in matched and unmatched cohorts, and waitlist-times were compared between groups.

Results:

DCD and DBD recipients had similar age [57y for both, p=0.791]. DCD recipients were more likely white (67% vs. 60%,p=0.002), on LVAD (40% vs. 32%,p<0.001) & listed as status 4–6 (60% vs. 24%,p<0.001); however, less likely to require inotropes (22% vs. 40%,p<0.001), & preoperative ECMO (0.9% vs. 6%,p<0.001). DCD donors were younger (29 vs. 32y,p<0.001), had less renal dysfunction (15% vs. 39%,p<0.001), diabetes (1.9% vs. 3.8%,p=0.050) or hypertension (9.9% vs. 16%,p=0.001). In matched & unmatched cohorts, early survival was similar (p=0.22). Adjusted waitlist-time was shorter in DCD group (21d vs. 31d,p<0.001) compared to DBD cohort and 5-fold shorter (DCD-22d vs DBD-115d,p<0.001) for candidates in status 4–6 which was 60% of DCD cohort.

Conclusions:

The community is using DCD mostly for those recipients who are expected to have extended wait list times (e.g., Durable LVADs, Status >4). DCD recipients had similar post-transplant early survival, and shorter adjusted waitlist-time compared to DBD group. Given this early success, efforts should be made to expand the donor pool using DCD, especially for traditionally disadvantaged recipients on the waitlist.

Introduction:

Heart transplantation (HT) has been and continues to be one of the most effective treatments for patients with end-stage heart failure. However, shortages of donor hearts have limited the number of patients able to receive this treatment. Due to this, the number of potential recipients on the waiting list has outpaced the number of transplantations, with the number of patients on the waiting list increasing by 42.6% from 2008 to 2019 [1]. Additionally, patients on the waiting list have increasingly needed to rely more on mechanical circulatory support and inotropic support for survival, and although modern mechanical and pharmaceutical advancements have improved waitlist mortality, there are limits to their utility [2].

Increasing utilization of organs from donation after circulatory death (DCD) is a potential way to combat the shortage of donor hearts. It has been estimated that effective utilization of DCD donor organs could increase the donor pool by as much as 30% and subsequently lead to a significant decrease in waiting list mortality [3]. DCD transplantation was historically looked upon with caution and not widely pursued because it was thought that myocardial damage would be sustained during the asystolic warm ischemic phase of procurement and subsequently render the heart unsuitable for transplantation [4]. However, recent use of DCD hearts has yielded similar outcomes as hearts that were donated after brain death (DBD), renewing interest in this alternative procurement strategy [5, 6].

In the US, despite the recent promise of DCD transplantation, there remains a resistance to widely adopt the use of DCD donors to address organ shortages and waiting list mortality. We sought to characterize the recent national trends in DCD donor utilization for heart transplantation and outcomes compared to DBD donor utilization.

Materials and Methods:

A retrospective analysis of United Network for Organ Sharing (UNOS) data from the Scientific Registry of Transplant Recipients (SRTR) was done. The study was approved by the Institutional review board at Cincinnati Children’s Hospital Medical Center and a waiver of consent was granted (IRB #2019–0641). All adult patients (>18yo) who received a DCD donor heart from January 2019 to June 2022 and their corresponding donors were identified using the “non-heart beating donors” variable. Heart-Lung recipients, patients under 18 years of age, DBD transplants done using ex-vivo perfusion, and transplants with missing follow-up data were excluded from our analysis. The cohort was divided into two groups according to the method of declaration of death: DCD HT and DBD HT. Baseline characteristics and post-transplant outcomes were determined using median and interquartile range [IQR] for continuous variables and percentages for categorical variables. Renal dysfunction was defined as an estimated glomerular filtration rate (using Schwartz equation) less than 60 mL/min and hepatic dysfunction was defined as bilirubin level more than 1.2mg/dL. The primary outcome of the study was to compare 1- and 2-year patient survival. In order to compare waitlist time among the two cohorts, total waitlist time was compared. Adjusted waitlist time was also assessed from the time when patients were made eligible to accept DCD hearts, as applicable in both cohorts (patients that were listed to accept DCD hearts from the beginning of the list and conversely patients that were never listed to accept DCD hearts, no adjustments were required). Secondary outcomes were post-transplant length of stay (LOS), index acute rejection episodes, in-hospital stroke, and need for dialysis. Comparisons between DCD and DBD groups were done using Student’s ttest for continuous variables & Pearson’s chi-squared test with Yates’ continuity correction for discrete variables. Univariable regression analysis was done to identify risk factors for mortality among patients underwent DCD HT. Multivariable regression analysis was conducted, inclusive of all variables, which showed p-value ≤0.2 in univariable regression to identify risk adjusted hazards for post DCD HT survival. Further regression analysis was conducted to examine the effect of clamp-to-clamp time on survival in both DCD and DBD groups.

Propensity-Score-Matching

Propensity score matching sub-analysis was conducted to account for differences in baseline characteristics between the primary DCD and DBD cohorts. Propensity scores were estimated using the nearest neighbor method in a 2:1 fashion and included covariates that were different and were selected based on clinical experience The variables chosen for inclusion were recipient ethnicity, recipient listing status, recipient inotropes, existing LVAD at time of transplant, use of ECMO or IABP at time of transplant, donor age, donor ethnicity, donor hypertension, donor diabetes mellitus, and donor renal impairment (Figure 1). We refrained from adding waitlist times to the matched analysis as waitlist time is a surrogate of listing status and is not representative of acceptance for DCD hearts. In other words, the majority of the candidates were changed while on the list, making a significant difference in their waiting times after the change. Also, ischemic time was excluded from the matched analysis because it’s not truly represented in this case, it’s a “clamp to clamp time”, as a large percentage of the DCD hearts were ex vivo perfused after procurement, “normothermic perfusion time” is included in the reported “ischemic time” in the UNOS dataset. The absolute standardized mean difference for each variable was used to determine the efficacy of the matching process with a score of less than 0.1 being considered an acceptable match for the given variable. Once the propensity score matching was deemed successful, Kaplan Meier curves were constructed to evaluate survival. Log-rank tests were used to compare survival and Cox proportional-hazards models were constructed to compare hazards between the DBD and DCD cohorts at 6, 12, 18, and 24 months in the matched and unmatched cohorts by censoring the data at each interval. Statistical analyses were performed using SPSS (IBM Corp. Released 2020. IMB SPSS Statistics, Version 27.0. Armonk, NY: IMB Corp), and SAS version 9.4 (Cary, North Carolina, USA). Statistical significance was determined as p<0.05.

Figure 1:

Kaplan Meier curves comparing unmatched DCD vs. DBD HTx recipients

Results:

The Recipients

A total of 10,402 adult HT recipients were identified, of which 425 (4%) were DCD recipients and 9,977 (96%) were DBD recipients. Both cohorts had similar age [57 [46–64] years vs. 57 [47–63] years, p=00.791]. DCD recipients were heavier (89 kg vs 83 kg, p<0.001), more likely to be White (67% vs. 60%, p=0.002) and less likely to be Hispanic (7.1% vs. 10%, p=0.038). DCD recipients were less likely to be listed as status 1 (0.9% vs. 9.8%, p<0.001) or status 2 (20% vs. 50%, p<0.001) and more likely to be listed as status 4 (39% vs. 19%, p<0.001) with more waitlist days [45 [13–187] vs. 33 [9–161], p=0.006) in comparison with DBD group. Pre-transplant, DCD recipients were less likely to be on inotropes (22% vs. 40%, p<0.001) or require extra-corporeal membrane oxygenation (ECMO) (0.9% vs. 6%, p<0.001) or Intraaortic balloon pump (IABP) (9.6% vs 29.5%, p<0.001) and more likely to be on LVAD (40% vs. 32%, p<0.001) (Table 1).

Table 1:

Demographics and basic characteristics of heart transplantation Unmatched cohort, stratified by DCD vs. DBD

Heart Donor Demographics
Characteristics	DCD (n=425)	DBD (n=9977)	P-value
Age, years, median [IQR]	29 [23–35]	32 [24–40]	<0.001
Sex male, n (%)	375 (88%)	7164 (72%)	<0.001
Ethnicity
White	329 (77%)	6227 (62%)	<0.001
Black	39 (9.2%)	1614 (16%)	<0.001
Hispanic	50 (12%)	1822 (18%)	<0.001
Asian	4 (1%)	168 (1.7%)	0.239
Other	3 (0.7%)	146 (1.5%)	0.198
Weight, kg, median [IQR]	84 [74–97]	82 [71–96]	0.018
Height, cm, median [IQR]	178 [173–183]	175 [168–180]	<0.001
Hypertension, n (%)	42 (9.9%)	1559 (16%)	0.001
Diabetes mellitus, n (%)	8 (1.9%)	384 (3.8%)	0.050
Cause of Death
Anoxia, n (%)	184 (43.3%)	3754 (37.6%)	0.018
CVA, n (%)	23 (5.4%)	1380 (13.8%)	<0.001
Head Trauma, n (%)	205 (48.2%)	4119 (41.3%)	0.004
Other, n (%)	13 (3.1%)	724 (7.3%)	0.001
Renal Dysfunction, n (%)	63 (15%)	3866 (39%)	<0.001
Hepatic Dysfunction, n (%)	72 (17%)	2309 (23%)	0.003
Ischemic Time, hours [IQR]	4.88 [3.48–6.34]	3.41 [3.85–3.97]	<0.001
Clinical Infection, n (%)	344 (81%)	7957 (80%)	0.619
EF >50%, n (%)	408 (96%)	9540 (96%)	0.827
Travel distance, nautical miles, median [IQR]	345 [136–575]	218 [85–389]	<0.001
Heart Recipient Demographics
Characteristics	DCD (n=425)	DBD (n=9977)
Age, years, median [IQR]	57 [45–64]	57 [47–63]	0.791
Sex, male, n (%)	335 (79%)	7279 (73%)	0.008
Ethnicity
White	286 (67%)	5994 (60%)	0.002
Black	94 (22%)	2481 (25%)	0.198
Hispanic	30 (7.1%)	1011 (10%)	0.038
Asian	10 (2.4%)	377 (3.8%)	0.128
Other	5 (1.1%)	114 (1.1%)	0.948
Weight, kg, median [IQR]	89 [78–103]	83 [71–96]	<0.001
Height, cm, median [IQR]	178 [172–183]	175 [168–180]	<0.001
Diabetes Mellitus, n (%)	135 (32%)	2946 (30%)	0.354
End Listing Status, n (%)
1	4 (0.9%)	976 (9.8%)	<0.001
2	83 (20%)	4966 (50%)	<0.001
3	85 (20%)	1687 (17%)	0.096
4	165 (39%)	1862 (19%)	<0.001
5	8 (1.9%)	85 (0.9%)	0.027
6	80 (19%)	401 (4.0%)	<0.001
Diagnosis, n (%)
DCM	351 (88%)	7906 (86%)	0.095
HCM	17 (4.2%)	328 (3.6%)	0.421
RCM	17 (4.2%)	467 (5.1%)	0.514
CHD	12 (3.0%)	358 (3.9%)	0.404
VHD	4 (1.0%)	99 (1.1%)	0.917
Other	24 (5.6%)	819 (8.2%)	0.058
Unadjusted waitlist days, median [IQR]	45 [13–178]	33 [9–161]	0.006
Inotropes at Tx, n (%)	95 (22%)	3962 (40%)	<0.001
Ventilator at Tx, n (%)	4 (0.9%)	233 (2.3%)	0.085
Renal Dysfunction at Tx, n (%)	200 (47%)	4830 (48%)	0.609
Hepatic Dysfunction at Tx, n (%)	69 (16%)	2263 (23%)	0.002
Pre-Tx MCS Support at Tx, n (%)
LVAD	169 (40%)	3151 (32%)	<0.001
RVAD	0 (0%)	43 (0.04%)	0.331
ECMO	4 (0.9%)	596 (6%)	<0.001
IABP	41 (9.6%)	2942 (29.5%)	<0.001

The Donors

DCD donors were younger (29 [23–35] years vs. 32 [24–40] years, p<0.001), heavier (84 kg vs 82 kg, p=0.018) more likely to be White (77% vs. 62%, p<0.001), less likely to be Black (9.2% vs. 16% p<0.001) or Hispanic (12% vs. 18%, p=0.001). DCD donors were less likely to have renal dysfunction (15% vs. 39%, p<0.001), less likely to be diabetic (1.9% vs. 3.8%, p=0.050) or hypertensive (9.9% vs. 16%, p=0.001), had longer ischemic time (4.8hrs vs. 3.4 hrs. p<0.001) and organ travel distance (345 nautical miles vs. 218 nautical miles, p<0.001). In addition, the mechanism of death among DCD donors was more likely to be trauma (48.2% vs. 41.3%, p=0.004) or anoxia (43.3% vs 37.6%, p=0.018), and less likely to be cerebrovascular stroke compared to the DBD group (5.4% vs. 13.8%, p<0.001) (Table 1).

Primary and Secondary Outcomes

After transplantation, Kaplan-Meier analysis showed that at 6 months, 12 months, and 24 months post-transplant, DCD recipients had survival rates of 94%, 92%, 80% and DBD recipients had survival rates of 92%, 90%, 86%, respectively, with no significant differences between the 2 groups [HR 0.937 (95% CI, 0.655–1.34), p=0.72] (Figure 1). Perioperative stroke was comparable between cohorts (p=0.264) as were rates of acute rejection (p=0.383), post-transplant dialysis requirement (p=0.892) and hospital length of stay (p=0.097) (Table 3).

Table 3:

Survival and secondary outcomes post DCD HT vs. DBD HT

	Unmatched cohort			Matched Cohort
	DCD (n=425)	DBD (n=9977)	P-value	DCD (n=425)	DBD (n=850)	p-value
Survival % (95% CI)			0.72 HR=0.937 (0.655–1.34)			0.22 HR=1.3 (0.84–2)
6mo	94 (9196)	92 (92–93)		94 (91–96)	94 (92–96)
12mo	92 (8995)	90 (90–91)		92 (89–95)	93 (91–95)
18mo	90 (8594)	88 (87–88)		90 (85–94)	91 (89–93)
24mo	80 (71–91)	86 (85–86)		80 (71–91)	88 (86–91)
Stroke, n (%)	14 (3.3%)	385 (3.9%)	0.264	14 (3.3%)	26 (3.1%)	0.465
Acute Rejection episodes, n (%)	82 (19%)	1752 (18%)	0.383	82 (19%)	152 (18%)	0.578
Dialysis Requirement, n (%)	73 (17%)	1678 (16.8%)	0.892	73 (17%)	111 (13%)	0.059
Hospital Length of Stay, median [IQR]	16 [12–24]	17 [12–26]	0.097	16 [12–24]	16 [12–24]	0.894
Cause of Death, n (%)
Cardiac	6 (1.4%)	244 (2.4%)	0.172	6 (1.4%)	21 (2.5%)	0.215
Pulmonary	3 (0.7%)	74 (0.7%)	0.932	3 (0.7%)	7 (0.8%)	0.822
Infection	11 (2.6%)	278 (2.8%)	0.807	11 (2.6%)	21 (2.5%)	0.899
CVA	1 (0.2%)	90 (0.9%)	0.148	1 (0.2%)	3 (0.4%)	0.723
Other	10 (2.4%)	365 (3.7%)	0.157	10 (2.4%)	22 (2.6%)	0.800

Matched cohort analysis

In a 2:1 matched cohort; 425 DCD-HT recipients were matched to 850 DBD HT recipients (Table 2). The absolute standardized mean difference across covariates is shown in Figure 2. Post matching analysis showed similar survival rates at 6,12,18 and 24 months post-transplant [HR 1.3 (95% CI, 0.84–2.0), p=0.22] (Figure 3). Similarly, secondary outcomes in terms of stroke, rejection, dialysis requirement, and length of hospital stay were similar in both cohorts (Table 3).

Table 2:

Demographics and basic characteristics of heart transplantation Matched cohort, stratified by DCD vs. DBD

Heart Donor Demographics
Characteristics	DCD (n=425)	DBD (n=850)	P-value
Age, years, median [IQR]	29 [23–35]	28 [22–35]	0.491
Ethnicity
White	329 (77%)	665 (78%)	0.738
Black	39 (9.2%)	76 (8.9%)	0.890
Hispanic	50 (12%)	100 (12%)	1
Asian	4 (0.9%)	8 (0.9%)	1
Other	3 (0.7%)	1 (0.1%)	0.076
Hypertension, n (%)	42 (9.9%)	66 (7.8%)	0.240
Diabetes mellitus, n (%)	8 (1.9%)	13 (1.5%)	0.815
Renal Dysfunction, n (%)	63 (15%)	114 (13%)	0.547
Hepatic Dysfunction, n (%)	72 (17%)	180 (21%)	0.073
Clinical Infection, n (%)	344 (81%)	671 (79%)	0.469
EF >50%, n (%)	408 (96%)	807 (95%)	0.483
Heart Recipient Demographics
Characteristics	DCD (n=425)	DBD (n=850)
Age, years, median [IQR]	57 [45–64]	57 [47–64]	0.696
Ethnicity
White	286 (67%)	581 (68%)	0.702
Black	94 (22%)	183 (22%)	0.810
Hispanic	30 (7.1%)	55 (6.5%)	0.691
Asian	10 (2.4%)	22 (2.6%)	0.800
Other	5 (1.1%)	9 (1.1%)	0.849
Diabetes Mellitus, n (%)	135 (32%)	227 (27%)	0.070
End Listing Status, n (%)
1	4 (0.9%)	9 (1.1%)	0.843
2	83 (20%)	177 (21%)	0.588
3	85 (20%)	174 (20%)	0.843
4	165 (39%)	322 (38%)	0.744
5	8 (1.9%)	15 (1.8%)	0.881
6	80 (19%)	153 (18%)	0.719
Diagnosis, n (%)
DCM	351 (88%)	688 (88%)	0.475
HCM	17 (4.2%)	28 (3.6%)	0.519
RCM	17 (4.2%)	32 (4.1%)	0.836
CHD	12 (3.0%)	30 (3.9%)	0.505
VHD	4 (1.0%)	6 (0.8%)	0.653
Other	24 (5.6%)	66 (7.7%)	0.164
Inotropes at Tx, n (%)	95 (22%)	185 (22%)	0.867
Ventilator at Tx, n (%)	4 (0.9%)	3 (0.4%)	0.348
Renal Dysfunction at Tx, n (%)	200 (47%)	405 (48%)	0.889
Hepatic Dysfunction at Tx, n (%)	69 (16%)	140 (16%)	1
Pre-Tx MCS Support at Tx, n (%)
LVAD	169 (40%)	315 (37.1%)	0.348
RVAD	0 (0%)	2 (0.2%)	0.316
ECMO	4 (0.9%)	18 (2.1%)	0.128
IABP	41 (9.6%)	102 (12%)	0.209

Figure 2:

Love plot depicting covariate balance using SMD

Figure 3:

Kaplan Meier curves comparing matched DCD vs. DBD HTx recipients

Waitlist Times Analysis

Median waitlist time for the overall DCD vs DBD cohorts was 45 [13–178] vs 33 [9–161] days (p= 0.006). Of the DCD cohort, 62% (265) of the recipients were not originally listed to accept DCD hearts and were transitioned to accept DCD at some point on the waitlist. Waitlist time for all DCD vs DBD recipients after excluding time on the list when they were not eligible to accept DCD hearts (where applicable) was 21 [7–59] vs 31 [9–153] days (p<0.001). Of the 425 DCD recipients, 38% (160) were listed as DCD from the beginning of the listing and their median waitlist time was 19 [8–47] days. Among status 4–6 recipients, waitlist time of DCD vs DBD recipients was 22 [9–58] vs 115 [32–347] days (p<0.001) (Table 4).

Table 4:

Waitlist Times (WLT) Analysis

	DCD (n=425)	DBD (n=9977)	P-value
Unadjusted WLT, days, median [IQR]	45 [13–178]	33 [9–161]	0.006
Adjusted WLT, days, median [IQR]	21 [7–59]	31 [9–153]	<0.001
WLT in recipients listed as DCD from the beginning*, days, median [IQR]	19 [8–47]	31 [9–153]	<0.001
WLT in recipients with Listing status ≥4, days, median [IQR]	22 [9–58]	115 [32–347]	<0.001

^*Number of Patients = 160 (38% of DCDs)

Regression Sub-Analysis

Univariable and Multivariable analyses for mortality risk following DCD HT are shown in Table 5 and 6. Pre-transplant recipient mechanical ventilation was associated with worse post-transplant survival (HR (95%CI) =8.69 [1.2–65], p= 0.035). No other variables were associated with increased mortality risk post-transplant. Further regression analysis investigating the effect of clamp-to-clamp time on post-transplant survival has shown prolonged (> 4hrs) ischemic (clamp-to-clamp) time was associated with poor post-transplant survival in the DBD group (HR (95%CI) =1.27 [1.11–1.45], p<0.001). However, in the DCD group, no significant association between prolonged ischemic time and survival was identified (HR (95%CI) =2.23 [0.85–5.85], p=0.100) (Supplemental Table 1).

Table 5:

Univariable survival analysis post DCD heart transplantation

Determinants of DCD Survival	Univariable HR (95%CI)	P value
Recipients’ characteristics
Age	1.03 (0.99–1.06)	0.119
Male sex	0.73 (0.34–1.59)	0.436
Inotropes	0.32 (0.96–1.04)	0.059
Mechanical Ventilation	8.69 (1.15–65.2)	0.036
Renal dysfunction	1.56 (0.77–3.18)	0.221
Hepatic dysfunction	0.78 (0.29–2.04)	0.607
VAD	1.23 (0.61–2.50)	0.555
IABP	0.86 (0.26–2.83)	0.805
ECMO	5.32 (0.71–39.3)	0.234
Donors’ characteristics
Age	0.96 (0.92–1.01)	0.248
Male sex	0.86 (0.30–2.45)	0.774
Hypertension	0.87 (0.26–2.89)	0.832
Diabetes mellitus	0.00 (0-inf)	0.604
Renal dysfunction	0.71 (0.29–1.73)	0.455
Hepatic dysfunction	1.65 (0.74–3.68)	0.225
Ejection fraction (<50%)	2.28 (0.54–9.60)	0.258
Ischemic time (>4 hrs)	2.23 (0.85–5.85)	0.224

Table 6:

Multivariable survival analysis post DCD heart transplantation

Determinants of DCD Survival	Multivariable HR (95%CI)	P value
Recipient’s Age	1.021 (0.988–1.055)	0.212
Inotropes	0.344 (0.103–1.141)	0.081
Mechanical Ventilation	8.230 (1.102–61.477)	0.040

Discussion:

With the aim of increasing the donor pool, the use of extended selection criteria has been implemented in the field of heart transplantation. Recently, there has been a growing interest in using DCD donors in heart transplantation to overcome donor shortages and to limit the waitlist mortality for recipients who die awaiting traditional DBD heart donors. A multicenter randomized trial that was recently published has shown that survival rates for DCD recipients are not inferior when compared to DBD recipients [6]. However, reservations still remain regarding the safety and feasibility of using DCD due to increased risk of ischemic injury [7]. Despite reservations, it has been shown that DCD heart donation may have the potential to significantly increase the pool of available donors by as much as 30%. With this potential increase would come a substantial decrease in waitlist mortality and more opportunities for heart failure patients [3]. This study investigated donor/recipient characteristics, current trends, and outcomes of DCD heart transplantation in the United States.

The analysis demonstrates DCD HT recipients were less ill prior to transplant and experienced similar post-transplant survival compared to DBD HT up to 2 years post-transplant. These findings are in line with Madan et al study which included 127 DCD HT recipients using the UNOS registry and reported no significant difference in 30-day or 6-months survival [8, 9]. Furthermore, similar results were described by Messer et al. who investigated the Royal Papworth Hospital experience with 79 DCD transplants and reported comparable 1-year survival outcomes with DBD patients [10]. Another study investigated midterm outcomes and reported similar survival among 32 DCD recipients compared with DBD patients out to 5 years [5]. Our study adds to the existing literature by including a larger cohort size and/or a longer follow-up. The current analysis demonstrated only mechanical ventilation as a risk factor for worse post-transplant survival in DCD HT patients. This can be compared to a previously published study from the UNOS registry which showed increased recipient age and waitlist time to be associated with an increased risk of 1-year mortality post DCD transplants [11].

Our analysis showed DCD recipients had a better pre-transplant overall condition; were less likely to be supported on ECMO, IABP, or inotropes. Similarly, the DCD donors had better overall baseline features as well. These findings could perhaps explain why DCD and DBD outcomes are similar even if DCD hearts are of lesser quality. Therefore, cohort matching analysis was performed and again demonstrated that individuals who received DCD organs still demonstrate similar survival outcomes compared to DBD transplants. This included secondary outcomes—stroke, need for dialysis, treatment for acute rejection, and LOS—where no difference among the 2 groups in either the matched or unmatched cohorts was seen, which agrees with the findings in the UK experience. However, we are cautious in these assertions realizing that cohort matching analysis has its limitations.[10, 12]. However, on the contrary, some US studies have reported higher rate of post-transplant in hospital treated acute rejections associated with DCD HT [11, 13]. These current results are reassuring since they encompass a larger study cohort and may support the view that the widespread adoption of heart transplantation using DCD donors in the United States should be encouraged.

We found overall waitlist time to be longer in the DCD group which was similar to the findings reported in the previously mentioned studies which exhibited > 50% longer waitlist time in the DCD patients [11, 13]. However, this is an unadjusted comparison as 62% of the DCD heart recipients were not originally listed to accept DCD hearts and were transitioned to accept DCD at some point on the waitlist. Importantly, the current analysis showed that after excluding time on the list when potential recipients were not eligible to accept DCD hearts, waitlist time is almost fivefold shorter in the DCD group. Therefore, our analysis sheds light on the effectiveness of DCD heart donors’ utilization in shortening waitlist times for potentially disadvantaged transplant candidates in the current allocation scheme. In addition, it suggests that the paramount goal should be to reduce wait time in heart transplant patients by increasing the donor pool of quality organs. It is worth mentioning that part of these findings reflects the current practice patterns. Being recently introduced, programs rapidly developed protocols for DCD hearts and even to date, the practice is still variable. As a result, there were more DCD hearts because of lower competition. All these “practices” may change when more programs are accepting DCD and there may be no difference in use of DCD vs DBD hearts for different status patients. However, if the majority of programs begin to accept DCD hearts, then the total number of donor hearts for the community will increase significantly which should decrease overall waiting times for all recipients. Further investigations on the impact of such change in waitlist time on post-transplant survival is warranted.

Clinically, many centers have been using DCD donors for those patients who are unlikely to get transplanted without extended waiting periods. Our data supports this by showing DCD recipients are healthier, have higher listing status (≥4), and more likely to be on durable VADs. Around 60% of DCD recipients are status 4 or above with only 24% of DBD being status 4 or above. It has been shown that at six months post listing, 53% of patients in status ≥4 remained waitlisted and around 4.3% died or deteriorated on the waitlist [14]. Therefore, if consistently practiced, DCD transplantation may offer an opportunity to improve waitlist outcomes and survival in this population. The community is not using DCD donors to get the sickest recipients transplanted quicker, because in the new UNOS organ distribution they are being transplanted efficiently. However, DCD donors are being used to transplant those who will not get transplanted or may wait for an extended period. This perhaps explains the plateau if not decrease in the placement of durable VADs, since clinicians may feel if they place a durable VAD and send their patient home, the chance of transplantation is hampered. However, with the increasing use of DCD donors, we may see that change.

The current study has several limitations. First, The UNOS registry lacks some important data about the DCD donor heart retrieval process. For example, information about any supportive meds pre- and post—withdrawal, which may affect the agonal phase and potentially post-transplant outcomes. Furthermore, the time of reperfusion of donor organ and warm ischemic time are not captured in the UNOS registry. Second, the ischemic time data reported in the UNOS registry is not a true ischemic time, it’s a “clamp to clamp time” because a large percentage of these DCD procured hearts were perfused during transportation using ex vivo perfusion machine. In other words, they are not subjected to ischemia for the entire period. Although our results have demonstrated that prolonged clamp-to-clamp time does not negatively impact post DCD HT survival, we assume this is because of ex-vivo perfusion. However, until this data is accurately tracked, we will not know the exact impact of ex-vivo perfusion on ischemia time and post-transplant survival. Third, we did not analyze differences in DCD technique of procurement whether direct procurement and perfusion (DPP) or normothermic regional perfusion (NRP) since it is not included in the UNOS dataset. Some previously published literatures have used length of time from circulatory standstill to cross-clamp and cardioplegia perfusion as a differentiation method, however, the cutoff point used was not the same among these studies ranging from 15–30 minutes [11, 13, 15]. Furthermore, we checked utilization rates of ex vivo perfusion machine in the UNOS registry based on the mentioned identification method and found only around 70% of hearts procured using presumed DPP technique were ex vivo perfused which is not realistic. Similarly, Kwon et al and colleagues reported ex vivo perfusion utilization rate of 81% among DPP transplants [11]. These findings raise some concerns about the accuracy of such methods and/or the possibility of underreported data. Going forward, it would be impactful if the UNOS registry captured type of DCD procurement technique and details about each technique so we can understand the impact on post-transplant survival. Furthermore, being recently introduced into the US practice, the current analysis reported comparable early/short term results between DCD and DBD HT, however mid-term and long-term follow-up with larger sample size, and more granular data (especially post-transplant grade of rejection) is still needed to understand if survival is constant or changes overtime. Lastly, the overly selective donors and recipients’ criteria for DCD HT have led to variation in the baseline characteristics between the DCD and the DBD cohorts, which may make our comparison flawed, however we performed propensity score matching to eliminate the impact of potential confounding when comparing the two groups.

Conclusions

In conclusion, the current study investigated the contemporary experience and early outcomes with heart transplantation using DCD donors in the United States. Like international and previously reported US experiences, similar early term survival was detected between DCD and DBD recipients. It appears that the community is using DCD donors for the healthier candidates awaiting transplantation (e.g., durable LVADs, listing status >4, etc.) for whom transplant is unlikely without extended waitlist times in order to achieve the best outcomes. This practice was shown to drastically (> 5-fold) reduce waitlist time with no change in post-transplant survival. Also, further investigations focusing on the optimum method of procurement are warranted. Based on the current results, heart transplantation using DCD may offer an opportunity to appreciably expand the donor pool and reduce the waitlist time especially in the absence of suitably available DBD donor hearts.

Abbreviations:

DBD

Donation after brain death

DCD

Donation after circulatory death

ECMO

Extracorporeal membrane oxygenation

HT

Heart transplantation

IABP

Intraortic balloon pump

LVAD

Left ventricular assist device

SRTR

Scientific Registry of Transplant Recipients

UNOS

United Network for Organ Sharing

CVA

Cerebrovascular accident