Abstract
Rationale: All U.S. acute care hospitals must maintain protocols for recovering organs from donors after circulatory determination of death (DCDD), but the numbers, types, and whereabouts of available organs are unknown.
Objectives: To assess the maximal potential supply and distribution of DCDD organs in U.S. intensive care units.
Methods: We conducted a population-based cohort study among a randomly selected sample of 50 acute care hospitals in the highest-volume donor service area in the United States. We identified all potentially eligible donors dying within 90 minutes of the withdrawal of life-sustaining therapy from July 1, 2008 to June 30, 2009.
Measurements and Main Results: Using prespecified criteria, potential donors were categorized as optimal, suboptimal, or ineligible to donate their lungs, kidneys, pancreas, or liver. If only optimal DCDD organs were used, the deceased donor supplies of these organs could increase by up to 22.7, 8.9, 7.4, and 3.3%, respectively. If optimal and suboptimal DCDD organs were used, the corresponding supply increases could be up to 50.0, 19.7, 18.5, and 10.9%. Three-quarters of DCDD organs could be recovered from the 17.2% of hospitals with the highest annual donor volumes—typically those with trauma centers and more than 20 intensive care unit beds.
Conclusions: Universal identification and referral of DCDD could increase the supply of transplantable lungs by up to one-half, and would not increase any other organ supply by more than one-fifth. The marked clustering of DCDD among a small number of identifiable hospitals could guide targeted interventions to improve DCDD identification, referral, and management.
At least 10,000 Americans die each year because of an inadequate supply of transplantable organs (1), causing similar numbers of life-years lost annually as through stroke or liver disease (2). Therefore, substantial increases in quality-adjusted life expectancy are obtained through deceased organ donation, which is cost-effective by conventional standards (3) and cost-saving in the case of kidney transplantation (4).
Because the annual supply of donors after neurological determination of death (DNDD, formerly called “brain-dead” donors) would be insufficient to meet the growing demand even if it were fully realized (5, 6), alternative methods to increase the organ supply are needed. In May 2006, an Institute of Medicine committee concluded that among available options to augment the organ supply, expanded use of donors after circulatory determination of death (DCDD) held the greatest potential (7). In turn, the Centers for Medicare and Medicaid Services and Joint Commission issued policies requiring all hospitals to establish and implement protocols for recovering DCDD organs (8, 9).
Clinical outcomes after DCDD organ transplantation are increasingly understood (10). Relative to organs from DNDD, those obtained from properly selected DCDD produce roughly comparable outcomes for kidney (11–14) and pancreas (11) transplant recipients, and poorer outcomes for liver transplant recipients (15–17). Very favorable experiences are being reported for DCDD lungs (18–23), and DCDD hearts have been evaluated in an experimental protocol in infants (24).
Although these data on individual outcomes suggest promise, measuring the societal benefits that may accrue from using DCDD organs also requires knowledge of how many organs are available and where they are likely to be found. We reported that complete identification and referral of controlled DCDD (donors in whom life-sustaining therapies are withdrawn and organs are recovered after the loss of spontaneous circulation) could increase the number of deceased organ donors by roughly 10% if only optimal candidates were considered, or by up to 25% if optimal and suboptimal candidates were included (25). The present study addresses three additional aims. First, we sought to quantify the proportionate increases obtainable in the kidney, liver, lung, and pancreas supplies so as to guide organ-specific allocation policies. Second, we aimed to characterize missed opportunities for DCDD referral so as to inform efforts to educate intensive care unit (ICU) physicians and nurses responsible for initiating referrals. Third, we sought to define the types of hospitals at which DCDD would be most commonly found so as to guide the efficient deployment of staff and ICU resources needed to enhance use of the potential supply.
We conducted a population-based cohort study of potential controlled DCDD across the Gift of Life Donor Program donor service area (DSA), which includes eastern Pennsylvania, southern New Jersey, and Delaware. On the basis of the 2000 census, this area included 10.2 million Americans, or 3.62% of the U.S. population. In 2008, of 7,991 deceased organ donors in the United States, 428 (5.36%) were supplied by this DSA—the largest total among the nation’s 58 DSAs (26).
We selected a stratified random sample of 50 of the DSA’s 134 acute care hospitals. We sampled hospitals after stratifying by average deceased donor volume during the preceding 3 years (level 1, ≥20; level 2, 10–19; level 3, 5–9; and level 4, ≤4), median ICU bed number, racial distribution of the local county, and geographic region. We included all 23 hospitals designated by the Organ Procurement Organization (OPO) as level 1 or 2 to maximize data precision at hospitals anticipated to yield the most donors. We then selected a stratified 25% random sample of level 3 and 4 hospitals. This strategy resulted in the inclusion of 8 of 23 (34.8%) level 3 hospitals, 19 of 88 (21.6%) level 4 hospitals, and 2 of the region’s 4 dedicated children’s hospitals.
We identified all patients dying in the 50 study hospitals from July 1, 2008 through June 30, 2009. Similar to a population-based cohort study of DNDD potential (6), we excluded patients who would be ineligible to donate on the basis of age greater than 70 years or the presence of any diagnostic codes (e.g., metastatic cancer, human immunodeficiency virus [HIV], West Nile virus) that would have precluded donation per United Network for Organ Sharing (UNOS) guidelines (see Table E1 in the online supplement). For all remaining patients, we abstracted data using an instrument (available on request) that was developed for this study, pilot tested at 5 local hospitals from July 1, 2007 to October 31, 2007, and then taught to all 20 OPO data abstractors via training sessions from December 1, 2007 through June 1, 2008.
Because we aimed to capture the maximal potential for controlled DCDD, we sought clinical data on patients who were declared dead on the basis of circulatory criteria within 90 minutes of the withdrawal of one or more life-sustaining therapies (mechanical ventilation, vasopressor or inotropic agents, ventricular assist devices, or extracorporeal membrane oxygenation). We excluded patients who suffered an unexpected cardiac arrest because they would be candidates only for “uncontrolled DCDD,” which is presently experimental and controversial (27). We used OPO identification numbers to maintain the anonymous nature of the data and to prevent double-counting. This study was exempt from review by institutional review boards.
For all patients meeting the foregoing criteria, OPO abstractors collected patients’ demographic and diagnostic data; laboratory, hemodynamic, respiratory, and urinary data; and the types and magnitudes of cardiovascular and respiratory support being provided before death. All recorded values were selected as those closest to the time of withdrawal of life-sustaining therapy.
To assess the reliability of coding, a senior chart abstractor reevaluated the complete clinical records from all patients who died at one of five study hospitals during any of three study months selected via random number generation: September and November of 2008, and February of 2009. Of the 92 in-hospital deaths among patients 70 years or younger who lacked exclusionary diagnoses, this abstractor classified 8 as potential controlled DCDD. Of these, seven (87.5%) had previously been identified through the coordinators’ record reviews. Coordinators did not identify any additional donors who were not corroborated by the senior abstractor’s assessment.
As reported previously (25), we classified each potential donor’s kidneys, liver, pancreas, and lungs individually into one of three groups: optimal DCDD organs (those with no known risks for suboptimal graft function), suboptimal DCDD organs (those that might be selected for use by some transplant physicians or for some potential recipients despite harboring known risks for suboptimal graft function), or nontransplantable organs (those that presently would not be considered for transplantation) (Table E2).
Although standards exist for defining so-called “expanded criteria” for DNDD, few evidence-based criteria are available in the realm of DCDD. Thus, our classification scheme started with guidance from the available literature delineating expanded criteria for DNDD (and where available, DCDD) kidney (10, 28, 29), liver (10, 30, 31), lung (21, 32), and pancreas (33, 34) donors. We then modified these criteria through iterative feedback and consensus-building among a panel of nationally recognized experts in DCDD transplantation surgery who were blinded to all data (experts listed in the Acknowledgment). Finally, to assess the consistency of our criteria with current practice, we evaluated all actual transplants from DCDD during the study. This step confirmed that of the 108 DCDD organs actually transplanted during the study, 66 came from donors that our criteria classified as optimal, 42 from donors classified as suboptimal, and 0 from donors classified as ineligible.
To generate estimates of the potential supply of DCDD organs for each organ type, we first extrapolated our counts of optimal and suboptimal kidney, liver, lung, and pancreas donors from the 50 study hospitals to the entire DSA. This was accomplished by multiplying the numbers of donors identified at level 3 and level 4 hospitals by the inverse of the percentages of these hospitals that were selected, at random, for study inclusion. Second, we anticipated the number of eligible organs by multiplying the number of potential kidney and lung donors by the proportions of each who would donate both kidneys or both lungs on the basis of data from known donors. Third, we discounted each organ supply by the proportion of identified eligible donors for whom consent was likely to be obtained, based on observed rates among identified potential donors. Finally, to determine the percentage increases in the recovery of each type of organ, we divided these estimates of the DCDD organ supply across the DSA by the numbers of DNDD organs of each type recovered from these same 134 hospitals during the study period. We calculated similar increases in the percentages of organs transplanted after discounting the numbers of both DCDD and DNDD organs by the proportions of recovered organs that were actually transplanted (either to recipients within our DSA or in another DSA). We generated 95% confidence intervals about these proportionate increases from Poisson distributions.
We used Wilcoxon rank-sum tests and chi-squared tests as appropriate to identify patient characteristics (Table 1) and hospital characteristics (Table 2) associated with failures to identify potential DCDD and to identify hospital characteristics associated with potential DCDD supply. All hospital characteristics associated with the DCDD supply at P < 0.20 in bivariate analyses were included in a multivariable Poisson model designed to predict a hospital’s potential DCDD supply. All analyses were performed with Stata 10.1 (Stata, College Station, TX).
| Characteristic | Value |
|---|---|
| Age (yr), median (IQR) | 47 (31–58) |
| Male | 68.2% |
| Race* | |
| Black | 10.1% |
| White | 83.0% |
| Other | 6.9% |
| Height (cm), median (IQR) | 175 (165–178) |
| Weight (kg), median (IQR) | 82 (68–101) |
| Minutes from withdrawal of life support to declaration of death, median (IQR) | 28 (15–40) |
| Primary injury or illness leading to withdrawal of life support† | |
| Brain injury | 110 (84.6%) |
| Anoxia | 43 |
| Stroke | 35 |
| Trauma | 35 |
| Other | 4 |
| Respiratory failure | 17 (13.1%) |
| Neuromuscular disease | 4 (3.1%) |
| Spinal cord injury | 1 (0.8%) |
| Hospital location | |
| Intensive care unit | 124 (95.4%) |
| Emergency department | 3 (2.3%) |
| Burn unit | 3 (2.3%) |
| Donor designation on driver’s license or through online registry | 36 (27.7%) |
| Hospital Characteristic | Hospitals (n = 50) | Median DCDD Potential (IQR) | Coefficient (95% Confidence Interval) | Adjusted P Value | |
|---|---|---|---|---|---|
| Unadjusted | Adjusted | ||||
| Annual deceased donors* | |||||
| ≤4 | 19 | 0 (0–0) | — | — | |
| 5–9 | 8 | 0 (0–1.0) | 2.1 (0.8–3.4)† | — | |
| 10–19 | 11 | 3.0 (1.0–5.0) | 3.0 (1.8–4.2)† | — | |
| ≥20 | 12 | 7.0 (2.5–10.5) | 3.8 (2.7–5.0)† | — | |
| ICU beds‡ | |||||
| ≤13 | 11 | 0 (0–0) | — | — | 0.017 |
| 14–20 | 12 | 0 (0–2.0) | 2.6 (0.6–4.6)† | 2.5 (0.4–4.5) | 0.011 |
| 21–43 | 14 | 2.5 (0–5.0) | 3.7 (1.7–5.7)† | 2.6 (0.6–4.6) | 0.023 |
| ≥44 | 13 | 4.0 (2.0–9.0) | 4.0 (2.1–6.0)† | 2.4 (0.3–4.4) | |
| Transplant center | |||||
| No | 36 | 0 (0–3.0) | — | — | 0.85 |
| Yes | 14 | 4 (2.0–10.0) | 1.2 (0.9–1.6)† | 0.1 (–0.5 to 0.6) | |
| Trauma center | |||||
| None | 27 | 0 (0–0) | — | — | — |
| Level 2 or 3 | 11 | 3.0 (0–5.0) | 1.7 (1.1–2.3)† | 1.4 (0.7–2.0) | <0.001 |
| Level 1 | 12 | 7.0 (2.0–10.5) | 2.4 (1.9–3.0)† | 2.1 (1.3–2.8) | <0.001 |
During the 1-year study, 130 (0.60%) of 21,802 deaths occurring at the 50 study hospitals were potentially eligible DCDD, including 52 optimal DCDD (i.e., eligible to donate ≥1 optimal organ) and 78 suboptimal DCDD (i.e., eligible to donate no optimal organs but ≥1 suboptimal organ). Of these potential DCDD, clinicians identified and referred 108 (49 optimal and 59 suboptimal; 83.1%) to the OPO before withdrawal of life-sustaining therapy (25). The remaining 22 (3 optimal and 19 suboptimal) were identified only through medical record review (Figure 1).
Figure 1. Identification of potential donors after circulatory determination of death (DCDD). *Exclusionary ICD-9 code (e.g., HIV, cancer), loss of circulation more than 90 minutes after withdrawal of life-sustaining therapy, or unexpected cardiac arrest. DNDD = donors after neurological determination of death; OPO = Organ Procurement Organization.
[More] [Minimize]Among the 108 potential DCDD who were identified and referred, 108 organs from 50 donors were actually transplanted (2.16 organs per donor). Nontransplantation among the remaining 58 identified potential donors was due to families refusing consent or because at the time of recovery, the organs were deemed inappropriate for transplantation (Table 3). Transplanted organs included 91 kidneys, 15 livers, and 2 lungs. Both kidneys were transplanted from 29 of 32 optimal kidney donors (90.6%) and from 11 of 17 suboptimal kidney donors (64.7%), providing estimates from which to calculate the total numbers of kidneys that may have been obtained if all potential DCDD were identified. To generate similar proportions for lungs, we evaluated all deceased organ donors in our DSA from 2005 to 2007, finding that both lungs were transplanted from 85.7% of donors who donated at least one lung.
| DNDD Organs* | Optimal DCDD Organs | All DCDD Organs | ||||
|---|---|---|---|---|---|---|
| Recovered | Transplanted | Recoverable† (% increase)‡ | Transplantable§ (% increase) | Recoverable† (% increase) | Transplantable§ (% increase) | |
| Kidney | 563 | 432 | 50 (8.9%) | 47 (10.9%) | 111 (19.7%) | 95 (22.0%) |
| (6.6–11.7%) | (8.0–14.5%) | (16.2–23.7%) | (17.8–26.9%) | |||
| Liver | 276 | 220 | 9 (3.3%) | 9 (4.1%) | 30 (10.9%) | 25 (11.4%) |
| (1.5–6.2%) | (1.9–7.8%) | (7.3–15.5%) | (7.4–16.8%) | |||
| Lung|| | 110 | 99 | 25 (22.7%) | 23 (23.2%) | 55 (50.0%) | 47 (47.5%) |
| (14.7–33.5%) | (14.7–34.9%) | (37.7–65.1%) | (34.9–63.1%) | |||
| Pancreas | 54 | 35 | 4 (7.4%) | 4 (11.4%) | 10 (18.5%) | 8 (22.8%) |
| (2.0–18.9%) | (3.1–29.2%) | (8.9–34.1%) | (9.9–45.0%) | |||
| All organs | 1,003 | 786 | 88 (8.8%) | 83 (10.6%) | 205 (20.4%) | 176 (22.4%) |
| (7.0–10.8%) | (8.4–13.1%) | (17.7–23.4%) | (19.2–26.0%) |
Using the figures previously given, and the actual numbers of each organ that were recovered and transplanted from DNDD during the study period, we calculated the potential increases in the supplies of kidney, liver, lung, and pancreas transplants that might be recovered and transplanted from controlled DCDD (Table 3). Specifically, if only optimal DCDD organs were used, the number of organs recovered and transplanted would increase by up to 8.8% (7.8–10.8%) and 10.6% (8.4–13.1%), respectively. If both optimal and suboptimal DCDD organs were used, the total increase in organs recovered and transplanted would be up to 20.4% (17.7–23.4%) and 22.4% (19.2–26.0%), respectively. These increases were nonuniform, with a roughly 50% increase possible in the lung supply, but no more than an 11% increase possible in the liver supply (Table 3).
Of the 134 acute care hospitals in this DSA, the 12 (9.0%) with level 1 trauma centers accounted for 46.2% of the DSA’s total DCDD supply. The 21 hospitals (15.7%) with any type of trauma center and more than 20 ICU beds accounted for 65.9% of the DCDD supply. A Poisson model including only trauma center level and number of ICU beds as covariates explained 41.4% of the variance in hospitals’ potential DCDD supplies. As shown in Table 2, the 23 hospitals (17.2%) that the OPO had designated as level 1 or 2 based on historical contributions of at least 10 donors per year provided 75.6% of potential DCDD.
Compared with the 108 potential DCDD who were identified and referred to the OPO, the 22 potential DCDD who were not referred were more likely to be suboptimal donors (86.4 vs. 55.1%; P = 0.006) and older (median age, 55 vs. 45; P = 0.05). Additional bivariate analyses revealed that patients’ race, sex, body mass index, and time from extubation to the declaration of death were unrelated to the probability that a potential DCDD would be referred to the OPO. Similarly, no relationships were found between hospital characteristics (e.g., presence or absence of a transplant or trauma center, or the number of ICU beds) and the probability that a potential DCDD would be referred. Multivariable analyses were not performed because of the small number of nonreferred patients.
As increasing resources are devoted to augmenting the capacities of ICUs to identify, refer, and manage potential DCDD, it is important to understand the potential impact of such efforts. The current population-based study suggests that the maximal supply of organs that may be recovered from controlled DCDD, assuming that all potential DCDD could be identified and referred, is no greater than one-fifth of the estimated supply of organs from DNDD (5, 6). If only optimal DCDD organs were used, as some experts advocate (10), DCDD would be unlikely to expand the deceased donor organ supply by more than one-tenth. For perspective, extrapolating our data for the largest of the United States’ 58 DSAs to the country as a whole, based on its contribution to the national organ supply of 5.36%, suggests that an additional 1,642 optimal and 2,183 suboptimal organs (3,825 total) could be provided annually if all potential DCDD were identified and referred.
This study also provides data to guide allocation policies for specific organs. Specifically, the results support the optimism (19–21, 35, 36) that has surrounded controlled DCDD lung transplantation since the first successful case was reported in 1995 (37). However, in contrast to the up to 50% increase in the lung supply possible with full use of DCDD, our data suggest that DCDD would not increase any other organ supply by more than one-fifth.
In addition to estimating the supply of controlled DCDD organs, this study also shows that less than one-fifth of hospitals account for more than three-quarters of DCDD. This finding is consistent with patterns identified in the DNDD supply (6). Importantly, the hospitals with high donor potential appear to be easily identifiable using a small number of readily available hospital characteristics. Just as Sheehy and colleagues found that hospitals with neurosurgical services and emergency departments were likely to yield greater numbers of DNDD (6), we found that 41% of the variation in DCDD supply among hospitals was explained by just two variables: the level of trauma center and the number of ICU beds.
Knowing where DCDD are most likely to be found can inform the efficient deployment of interventions that may enhance use of the potential supply. For example, 24-hour staffing of hospitals with transplantation coordinators can augment the proportion of potential donors who become actual donors (38); our results suggest the types of hospitals in which such approaches might be cost-effective. Similarly, because the greatest barriers to identifying DCDD seem to be related to knowledge of the process (39–41), understanding the types of hospitals likely to account for most DCDD can help target educational interventions. Finally, promoting education about DCDD recovery among high-volume hospitals may augment the quality of end-of-life care provided for most donors, thereby reducing the chances that clinicians with little experience would be recovering organs from DCDD (42, 43).
To test prevailing views that DCDD could substantially mitigate the organ shortage (7), we intentionally designed this study to provide optimistic estimates of the DCDD organ supply. First, we based organ classifications on the standards of highly experienced DCDD transplant surgeons. These surgeons may have more liberal acceptance criteria than surgeons less experienced in the use of such organs. For example, on the basis of our experts’ recommendations, kidneys from donors with times from extubation to circulatory arrest of 60–90 minutes were classified as suboptimal. However, many practicing transplant surgeons would exclude kidneys in this category entirely, limiting recovery to donors with warm ischemic times of no more than 60 minutes (10). Restricting our analyses to this 60-minute window would have reduced the reported numbers of viable DCDD kidneys by 5–10% (data not shown).
Second, classifying DCDD as potentially eligible on the basis of any fixed interval between the withdrawal of life-sustaining therapy and the declaration of death may overestimate the DCDD supply because this approach does not account for potentially significant physiological changes, such as drops in mean arterial pressure, that may occur during this interval and cause ischemic injuries to the organs (10). Although our estimates of expected DCDD organs account for this in part by discounting totals for the number of organs expected to be deemed nontransplantable at the time of recovery, some degree of overestimation may persist.
Third, our estimates assume that barriers to simultaneously procuring both abdominal and thoracic organs from DCDD can be overcome. Fourth, our calculations assume that recovery of organs from DCDD would not limit the DNDD supply by procuring organs early from patients with catastrophic neurological injuries who otherwise would have become DNDD. The possibility that promoting DCDD could limit DNDD is a legitimate concern given the generally more favorable outcomes using organs from DNDD (10). Our DSA has produced consistent numbers of DNDD each year despite increasing the number of DCDD (44), suggesting that diversion of potential DNDD to DCDD did not impact our results substantively. To the extent that this phenomenon may occur in any DSA, our results again may overestimate the overall gains achievable through increased identification of DCDD. Finally, our estimates assume that potential donors at level 3 and 4 hospitals would be consented at the same rates and have the same transplantation rates among consented donors as in more experienced hospitals. If less experienced hospitals do not perform as well on these metrics, this too may artificially increase our estimates.
This study has several strengths. First, it was conducted over a full calendar year, thereby mitigating seasonal effects on the donor supply. Second, unlike single-center studies focusing on the potential supplies of DCDD kidneys (45–49), kidneys and livers (50), or lungs (36), we evaluated the potential for DCDD to expand the supply of all organs presently recovered from such donors in nonexperimental settings. Third, although data were collected within one DSA, the use of a population-based cohort design at a large number of hospitals across a demographically diverse three-state region supports the generalizability of our regional estimates to the United States as a whole. Indeed, generalizability is supported by the facts that the DSA examined has the largest number of transplant centers (16) of any DSA, the greatest number of donors per year, and serves one of the largest populations (approximately 10.2 million people) across three states with different legislation regarding brain death determination and donation. By contrast, unique characteristics of the DSA that may affect generalizability include its above-average proportion of donors who die of anoxic brain injury (41%), and that OPO staff become involved in the donation process relatively early.
An additional strength is that we employed a prospectively defined set of criteria to categorize each potential donor as optimal, suboptimal, or ineligible to donate each organ individually. Given the absence of uniform standards for acceptable DCDD, broad agreement on what constitutes an “optimal” DCDD kidney or a “suboptimal” DCDD lung is unlikely. Nonetheless, our tiered classification scheme, designed to be inclusive, enables clinicians, patients, and policy makers with varying thresholds for organ acceptance to draw conclusions about the organ supply on the basis of these thresholds. For example, as experience and evidence accumulate with lung transplantation, eligibility criteria may become more liberal; if so, comparisons with our benchmark eligibility criteria will assist in gauging the impact of these more liberal criteria.
This study also has limitations. First, as noted previously, we made several decisions in designing this study that could each lead to overestimating the DCDD supply. Thus, our results should be considered as best-case scenarios, and policies that these results might inform should reflect the possibility that the true DCDD potential may be somewhat less. A second limitation is that we excluded patients who suffered unexpected cardiac arrests—patients who might be considered for uncontrolled DCDD. However, the recovery of organs from uncontrolled DCDD remains rare and largely experimental in the United States (51) because of substantial logistical and ethical barriers, as well as uncertainty regarding the outcomes associated with use of these organs (10). Third, identification of DCDD in our region was higher than expected during the study period, thereby limiting power to identify patient or hospital characteristics associated with missed opportunities for donation. Further research in other settings therefore is needed to understand ways to improve recognition of potential DCDD among ICU clinicians, many of whom report feeling ill-prepared for this task (41).
In summary, this study provides maximal estimates of the potential supply of DCDD organs in the United States These results suggest limits to the impact that aggressive pursuit of DCDD could have on patients awaiting kidney, liver, or pancreas transplantation, but provide reason for greater optimism among those awaiting lung transplantation. Whatever the actual impact, the bulk of it could be realized by pursuing DCDD only at those hospitals with trauma centers and large numbers of ICU beds. These findings provide context for policies promoting DCDD organ recovery, and suggest that additional methods are needed to substantially narrow the gap between the supply of and demand for transplantable organs.
S.D.H. had full access to all data in this study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The authors thank David A. Axelrod, M.D., M.B.A., Anthony M. D’Alessandro, M.D., Robert B. Love, M.D., Joshua D. Mezrich, M.D., Kim M. Olthoff, M.D., and Abraham Shaked, M.D., Ph.D. for providing expertise regarding the designation of potential donors as optimal, suboptimal, or ineligible.
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Supported by a Greenwall Foundation Faculty Scholars Award in Bioethics (S.D.H.).
Author Contributions: Conception and design (S.D.H.); acquisition of data (R.D.H.); analysis and interpretation of data (S.D.H., R.D.H., P.L.A.); drafting of the article (S.D.H.); revising it critically for important intellectual content (S.D.H., R.D.H., P.L.A.); final approval of the version to be published (S.D.H., R.D.H., P.L.A.).
This article has an online supplement, which is available from this issue’s table of contents at www.atsjournals.org
Author disclosures are available with the text of this article at www.atsjournals.org.
