Clinical Research
Open Access

End-of-Life Care among US Adults with ESKD Who Were Waitlisted or Received a Kidney Transplant, 2005–2014

Catherine R. Butler, Peter P. Reese, James D. Perkins, Yoshio N. Hall, J. Randall Curtis, Manjula Kurella Tamura and Ann M. O'Hare
JASN October 2020, 31 (10) 2424-2433; DOI: https://doi.org/10.1681/ASN.2020030342

Significance Statement

For patients with ESKD, hoping for or receiving a kidney transplant can shape prognostic expectations and care processes. In this manuscript, the authors describe more intensive, inpatient-oriented patterns of end-of-life care for patients with ESKD who had been waitlisted for a kidney transplant or received a transplant, compared with other patients with ESKD. Patients who died while on the transplant waitlist were also less likely to have received hospice services and less likely to have discontinued dialysis before death. Because there are powerful defaults favoring use of aggressive interventions to prolong life in most health systems in the United States, these findings suggest that the broad relevance of advance care planning for patients with ESKD extends to the relatively healthy segment of this population that has engaged in the transplant process.

Abstract

Background The care of patients in the United States who have ESKD is often shaped by their hopes and prognostic expectations related to kidney transplant. Little is known about how patients’ engagement in the transplant process might relate to patterns of end-of-life care.

Methods We compared six measures of intensity of end-of-life care among adults in the United States with ESKD who died between 2005 and 2014 after experiencing differing exposure to the kidney transplant process.

Results Of 567,832 decedents with ESKD, 27,633 (5%) had a functioning kidney transplant at the time of death, 14,653 (3%) had a failed transplant, 16,490 (3%) had been removed from the deceased donor waitlist, 17,010 (3%) were inactive on the waitlist, 11,529 (2%) were active on the waitlist, and 480,517 (85%) had never been waitlisted for or received a transplant (reference group). In adjusted analyses, compared with the reference group, patients exposed to the transplant process were significantly more likely to have been admitted to an intensive care unit and to have received an intensive procedure in the last 30 days of life; they were also significantly more likely to have died in the hospital. Those who died on the transplant waitlist were also less likely than those in the reference group to have been enrolled in hospice and to have discontinued dialysis before death.

Conclusions Patients who had engaged in the kidney transplant process received more intensive patterns of end-of-life care than other patients with ESKD. These findings support the relevance of advance care planning, even for this relatively healthy segment of the ESKD population.

Kidney transplant is the preferred form of RRT for many patients with ESKD because it offers the opportunity for longer survival and better quality of life compared with remaining on dialysis.1,2 However, only a small and relatively healthy segment of the ESKD population will ultimately receive a kidney.3 Available evidence suggests that for patients with advanced kidney disease, hopes and expectations around kidney transplant strongly shape their prognostic expectations4,5 and may affect how they think about and plan for the future.

Little is currently known about how engagement in the kidney transplant process—whether this be in the form of evaluation, waitlisting, or receipt of a kidney transplant—might shape the care that patients receive as they approach the end of life. Prior work among candidates for, and recipients of, other kinds of solid organ transplant (i.e., heart, lung, or liver) describes their limited involvement in advance care planning (ACP)6⇓⇓⇓–10 and high burden of unmet palliative care needs.11⇓⇓⇓–15 Although results are mixed,10,16 there is some evidence that patients preparing for these other types of solid organ transplant received more intensive patterns of end-of-life care than similar patients who had not been considered for transplant, even when their death was expected.8 However, systematic differences in the selection process for kidney, as compared with other kinds of solid organ transplant,17 and the availability of dialysis as an alternative form of organ replacement therapy for people with ESKD may contribute to distinctive patterns of end-of-life care for patients engaged in the kidney transplant process.

We are not aware of prior studies that have described patterns of end-of-life care for patients engaged in the kidney transplant process. We hypothesized that because of their younger age, lower burden of comorbidity, and engagement in a process intended to extend life, patients who had been waitlisted for, or received, a kidney would experience more intensive patterns of end-of-life care than other patients with ESKD. To test this hypothesis, we examined patterns of end-of-life care among a national cohort of decedents with ESKD with differing exposure to the kidney transplant process.

Methods

Cohort Derivation

Using data from the United States Renal Data System (USRDS), a national registry of patients with ESKD, we identified all adults (ages 19–99 years) who had been treated with maintenance dialysis or received a kidney transplant; died between January 1, 2005 and December 31, 2014; and had Medicare Parts A and B coverage throughout their final year of life (Figure 1). We excluded patients who had been treated with maintenance dialysis but subsequently recovered kidney function and those who received a kidney transplant outside the United States. We also excluded patients for whom it was unclear from source data whether their allograft was functioning at the time of death (Supplemental Table 1).

Figure 1.
Figure 1.

Cohort derivation.

Exposure

Using USRDS Standard Analysis Files, we defined six mutually exclusive groups of patients with differing exposure to the transplant process at the time of death: (1) patients with a functioning kidney transplant; (2) patients who were active on the deceased donor waitlist; (3) patients who were inactive on the waitlist; (4) patients who had been removed from the waitlist without receiving a kidney; (5) patients with a failed kidney transplant; and (6) patients who had never been waitlisted for or received a kidney transplant.

We used the following stepwise hierarchical approach to assign each patient to one of these six exposure groups. First, we used the USRDS Treatment History and Death Files to identify patients with a functioning kidney transplant at the time of death. Second, among the remaining patients, we used waitlist removal codes in the USRDS Kidney and/or Kidney-Pancreas Transplant Files to identify patients who died while on the deceased donor waitlist. These patients were further classified as active or inactive on the waitlist at the time of death on the basis of their most recent United Network of Organ Sharing (UNOS) status codes. Patients were classified as being active on the waitlist at the time of death if they were listed as such by at least one transplant center. Third, patients were classified as having been removed from the waitlist at the time of death if they were not included in any of the preceding groups and their most recent UNOS removal code in the USRDS Kidney and/or Kidney-Pancreas Transplant Files indicated that they had been removed for reasons other than death (e.g., “condition deteriorated,” “medically unsuitable”). Fourth, patients were classified as having a failed transplant if they were not included in any of the preceding groups and had a record of at least one prior kidney transplant in the USRDS Patients File. The remaining cohort members, who were on maintenance dialysis but had never been waitlisted for or received a kidney transplant, were assigned to the reference group.

Outcomes

We used Medicare fee-for-service institutional claims to define the following measures of intensity of end-of-life care during the last 30 days of life or at the time of death18: admission to a short- or long-stay hospital and admission to an intensive and/or coronary care unit in the last 30 days of life, receipt of one or more intensive procedures (cardiopulmonary resuscitation, mechanical ventilation, and/or artificial nutrition) in the last 30 days of life, and death in a hospital. We used the Centers for Medicare and Medicaid Services (CMS)-2746 form to ascertain whether patients were enrolled in hospice at the time of death and whether they had discontinued dialysis before death.

Covariates

Using Medicare institutional claims, the Medicare Denominator File and the USRDS Patients and Medical Evidence Files (CMS-2728 form), we ascertained each cohort member’s date of death, age at the time of death, sex, and race (Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, Black, White, or other or multiple races). We identified the following comorbid conditions on the basis of the International Classification of Diseases (ICD)-9 diagnostic codes for claims during the year before death: diabetes mellitus, coronary artery disease, congestive heart failure, stroke, emphysema, cirrhosis, and dementia. Because all of these characteristics could both differ across exposure groups and be associated with study outcomes, these were treated as potential confounding variables in the relationship between the exposure of interest (exposure to the transplant process) and study outcomes (measures of intensity of end-of-life care).

Statistical Analyses

We described cohort member characteristics using percentages for categoric variables and mean (SD) or median (interquartile range [IQR]) values for continuous variables. We used logistic regression to measure the association between exposure to the transplant process and each study outcome. Results of logistic regression analyses were adjusted for the following measured patient characteristics: age, sex, race, individual comorbid conditions, and date of death. Results are presented as adjusted proportions and risk differences with 95% confidence intervals on the basis of the distribution of covariates in the overall cohort. We used a P value of <0.002 as a threshold defining statistical significance for individual tests to achieve an overall false-positive error rate (α-level) of 0.05 for all comparisons on the basis of the Bonferroni correction.19

Supplementary Analyses

We examined time between the most recent transplant procedure and death among patients who died with a functioning kidney transplant (≤1 year, >1–5 years, >5–10 years, >10 years versus the reference group of patients who were not transplanted or waitlisted). We also examined time between graft failure and death among patients with a failed transplant who had not been waitlisted after their most recent graft had failed (≤1 year, >1–5 years, >5–10 years, >10 years versus the same reference group). These analyses were adjusted for the same covariates as the primary analyses.

Sensitivity Analyses

The mortality follow-back approach is often used to describe patterns of end-of-life care among decedents. A limitation of this approach is that it cannot capture patterns of end-of-life care for patients who survive the ascertainment period. For this reason, for studies that aim to comprehensively describe patterns of end-of-life care among a prospective cohort, the mortality follow-back approach can produce biased results if there are systematic differences between cohort members who die and those who survive beyond the ascertainment period. To evaluate the extent to which our results might be sensitive to this type of bias, we repeated the primary analysis among the subset of cohort members who developed ESKD early on in the ascertainment period between January 1, 2005 and December 31, 2008. As compared with patients who developed ESKD later in the ascertainment period, patterns of end-of-life care for these patients would be expected to more closely resemble those of a denominator population of otherwise eligible patients who developed ESKD over the same time period.

The analytic approach was guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) criteria20 and statistical tests were conducted using R studio (version 1.1.453, RStudio, Inc.)21 and Stata SE, version 13.1 (Stata Corp, College Station, TX). The study was approved by the Institutional Review Board at the University of Washington in Seattle, WA.

Results

In this national cohort of 567,832 adults with ESKD who died between 2005 and 2014, 27,633 patients (5%) had a functioning kidney transplant at the time of death, 14,653 (3%) were on dialysis after a failed transplant and had not been relisted, 16,490 (3%) had been removed from the waitlist, 17,010 (3%) were inactive on the waitlist, 11,529 (2%) were active on the waitlist, and 480,517 (85%) had never been waitlisted for or received a kidney transplant (Table 1). For patients with a functioning transplant at the time of death, the median interval between their most recent transplant procedure and death was 6.7 (IQR 2.9–11.4) years. For those with a failed transplant, the median time since their most recent transplant failure was 2.5 (IQR 0.9–5.8) years. For those who had been removed from the waitlist, the median time since their most recent waitlist removal was 1.8 (IQR 0.7–3.6) years.

View this table:
Table 1.

Cohort characteristics

Patients exposed to the transplant process were much younger than the reference group of patients who had never been transplanted or waitlisted, with the mean age ranging from 56.9 (SD 12.1) years for patients who were active on the waitlist to 65.1 (SD 11.6) years for those with a functioning transplant at the time of death as compared with 72.5 (SD 12.3) years for the reference group (Table 1). The proportion of Black patients was higher for all except those with a functioning transplant (in whom the proportion of Black patients was lower) compared with the reference group. With the exceptions of cancer (which was more common in those with a functioning transplant) and cirrhosis (which was more common in those who had been waitlisted or had a failed transplant), the prevalence of comorbid conditions was highest among members of the reference group.

Adjusted Association of Transplant Status with Study Outcomes

With the exception of patients who were active on the waitlist at the time of death, the adjusted proportion admitted to a hospital in the last 30 days of life was higher for those exposed to the transplant process than for the reference group (adjusted proportion 75% for those with a transplant, 77% for those with a failed transplant, 75% for those removed from the waitlist, 76% for those who were inactive on the waitlist, and 72% for those who were active on the waitlist versus 73% for the reference group; P value for adjusted risk difference <0.002 for all comparisons except for patients active on the waitlist) (Figure 2, Supplemental Table 2). Compared with the reference group, a higher adjusted proportion of all groups exposed to the transplant process was admitted to an intensive and/or coronary care unit (55%, 55%, 53%, 56%, and 54% versus 51%, respectively; P<0.002 for all comparisons) and received an intensive procedure (35%, 31%, 30%, 33%, and 34% versus 28%, respectively; P<0.002 for all comparisons) in the last 30 days of life and a higher adjusted proportion died in the hospital (49%, 45%, 44%, 46%, and 45% versus 40%, respectively; P<0.002 for all comparisons). Compared with the reference group, a lower adjusted proportion of patients who were waitlisted at the time of death received hospice services (18% of patients inactive on the waitlist and 12% of those active on the waitlist versus 25% of those in the reference group; P<0.002 for both comparisons) and discontinued dialysis before death (25% and 17% versus 28%, respectively; P<0.002 for both comparisons).

Figure 2.
Figure 2.

Measures of intensity of end-of-life care for adults with ESKD with exposure to the transplant process. Proportions adjusted for age, sex, race, date of death, and all measured individual comorbidities. *P value for adjusted risk difference <0.002. **Mechanical ventilation, cardiopulmonary resuscitation, and/or artificial nutrition. ICU, intensive or coronary care unit.

Supplementary Analyses

In adjusted analyses, intensity of care was higher than for the reference group for patients with a functioning transplant regardless of time since transplant and was especially high for those who had died within a year of transplant. These patients were also less likely than the reference group to have received hospice services (Figure 3, Supplemental Table 3).

Figure 3.
Figure 3.

Measures of intensity of end-of-life care among cohort members with a functioning kidney transplant at the time of death by time since transplant. Proportions adjusted for age, sex, race, date of death, and all measured individual comorbidities. *P value for adjusted risk difference <0.002 **Mechanical ventilation, cardiopulmonary resuscitation, and/or artificial nutrition. ICU, intensive or coronary care unit.

Among patients with a failed transplant, adjusted measures of inpatient intensity of care were all higher than for the reference group regardless of time since transplant failure (Supplemental Table 4). Use of hospice and dialysis discontinuation followed a similar pattern to the reference group and did not vary as a function of time since transplant failure.

Sensitivity Analyses

Results of a sensitivity analysis among cohort members who developed ESKD between 2005 and 2008 were similar to the primary analysis (Supplemental Table 5).

Discussion

Patients with ESKD who had been waitlisted for or received a kidney transplant received more intensive patterns of end-of-life care than other members of this population, even after adjusting for differences in measured patient characteristics. Those patients who died on the kidney transplant waitlist—regardless of whether they were active or inactive at the time of death—were also less likely to have received hospice services and to have discontinued dialysis. Patterns of end-of-life care were more intensive than for the reference group regardless of time since transplant or transplant failure.

Prior studies in the wider population with ESKD have described intensive patterns of end-of-life care focused on life extension22,23 that do not seem to reflect the kind of care many of these patients say they would want to receive if they were seriously ill or dying.24,25 Because there are strong defaults favoring use of aggressive interventions to prolong life in many US health systems,26,27 our findings underline the importance of educating patients engaged in the transplant process about what to expect at the end of life and offering opportunities to engage in advance care planning (ACP).28,29 High levels of end-of-life intensity of care among patients engaged in the kidney transplant process highlight the relevance of ACP even for this relatively healthy segment of the ESKD population. Our findings may also help to inform discussions with patients and families about the kinds of situations and treatment decisions that might lie ahead were they to become seriously ill.

Existing models of ACP developed for patients undergoing other kinds of organ transplant30⇓⇓–33 and for the overall ESKD population34⇓–36 may need to be adapted to accommodate the potentially dynamic and varied illness trajectories of patients engaged in the kidney transplant process. Unlike patients with other kinds of organ failure, where deteriorating health is anticipated (or even required) before they can receive a transplant, patients awaiting kidney transplant must remain relatively healthy in order to maintain their transplant candidacy.37⇓⇓–40 Most patients are thus relatively young and healthy when they are first listed for kidney transplant. However, within 3 years of listing, approximately one in five patients die or are removed from the waitlist due to deteriorating health.41 Although many of the deaths that occur among patients who are active on the waitlist or recently transplanted may be sudden and unexpected, even cohort members who had been inactivated or removed from the list received very intensive patterns of end-of-life care, as did those who had not been relisted after a failed kidney transplant.

Prior studies among candidates for other kinds of solid organ transplant suggest that patients generally welcome the opportunity to receive palliative care services and engage in ACP while planning for transplant.13,30⇓⇓–33,42 However, there may be unique challenges to integrating ACP with care processes related to kidney transplant. Existing qualitative work suggests that an emphasis on preventative and curative interventions during the evaluation can sometimes undermine other care processes,43,44 particularly if these seem inconsistent with the goal of receiving a transplant.45⇓⇓⇓–49 Further, hope for transplant—even for patients unlikely to receive a kidney—can foster overly optimistic expectations or uncertainty about the future that could limit the effectiveness of ACP.4,5 Uncertainty about where patients stand in the transplant evaluation process and about whether they are likely to receive a kidney may also make it difficult for patients and families to formulate realistic plans for their future care.50,51 This may perhaps explain why patterns of end-of-life care for patients who had been inactivated or removed from the transplant waitlist—events that may signal worsening health status 52,53—largely mirrored those for patients who were actively listed at the time of death.

We suspect that conceptualizing of ACP as an ongoing and iterative “process”54 rather than a one-time event may be particularly helpful in supporting patients engaged in the kidney transplant process. Early on, strategies to support patients and families in understanding prognostic uncertainty,55,56 including “hoping for the best and preparing for the worst,”57 may help to align ACP with the transplant evaluation process. Patients’ values, goals, and future expectations could then be revisited over time, particularly in the setting of deteriorating health and/or at critical junctures in the transplant process such as allograft failure or removal from the waitlist. More open communication and clear delineation of roles between the multiple clinicians who care for patients engaged in the transplant process may also help to support ACP in this population.

Our study has the following limitations. First, although the results of the sensitivity analysis provide some reassurance that patterns of end-of-life care would likely be similar for patients who did not die during the ascertainment period, it is possible that our results may not be generalizable to patients who survive for long periods of time after ESKD onset. Second, our results do not speak to whether patterns of end-of-life care were aligned with the goals, preferences, and values of individual patients. Third, our cohort was restricted to fee-for-service Medicare beneficiaries, which may limit generalizability to patients with Medicare Advantage or other types of health insurance. Fourth, our analyses do not describe patterns of end-of-life care for the subgroup of patients who had been accepted for living donor transplant but had not yet received a kidney. Fifth, because selection for waitlisting and transplant relies on information ascertained during a detailed physical and psychosocial evaluation, there are almost certainly unmeasured differences between patients in the reference group and those exposed to the transplant process. Our analyses also do not account for other factors (e.g., socioeconomic status) that can shape patterns of end-of-life care.58 Finally, inaccurate or incomplete information on transplant status at the time of death in source data may have led to misclassification of the exposure, although this would likely have biased our results toward detecting no differences between groups.

In a national cohort of Medicare beneficiaries with ESKD who died between 2005 and 2014, those who had engaged in the transplant process—regardless of the nature of this engagement—received more intensive patterns of end-of-life care than other patients with ESKD. Because there are powerful defaults favoring aggressive intervention to prolong life in most US health systems, these findings highlight the broad relevance of ACP even for this relatively healthy segment of the ESKD population.

Data Sharing Statement

The data reported here have been supplied by the United States Renal Data System and are available upon request. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as official policy or interpretation of the US government.

Disclosures

C.R. Butler reports personal fees from the Washington State Medical Association, outside the submitted work. P.P. Reese reports National Institutes of Health (NIH) grant support; investigator-initiated grants from Merck and AbbVie to the University of Pennsylvania to support research on transplantation of Hepatitis C Virus infected organs into uninfected recipients, followed by antiviral treatment; investigator-initiated grants from CVS Caremark and Merck to the University of Pennsylvania to support research on medication adherence (focus: Statins); Associate Editor for the American Journal of Kidney Diseases; and COHRDATA (epidemiology analytics firm)—consultation on design of studies of therapies for patients on dialysis, outside the submitted work. Y.N. Hall reports other support from Northwest Kidney Centers, outside the submitted work. J. Randall Curtis reports grants from NIH, grants from the Cambia Health Foundation, and grants from the National Palliative Care Research Center, outside the submitted work. A.M. O'Hare reports grants from NIDDK; grants from the Centers for Disease Control and Prevention; grants from the Department of Veterans Affairs Health Services Research & Development service; personal fees from Dialysis Clinics Inc.; personal fees from Fresenius Medical Care; personal fees from the Health and Aging Policy Fellows Program; personal fees from the University of Pennsylvania; personal fees from the University of Alabama, Birmingham; personal fees from Hammersmith Hospital; personal fees from Uptodate; personal fees from Devenir Foundation; personal fees from Japanese Society for Dialysis Therapy; personal fees from Chugai Pharmaceutical Co. Ltd.; other support from the Editorial Board of JASN and CJASN; and personal fees from ASN, outside the submitted work. All remaining authors have nothing to disclose.

Funding

This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (U01DK102150). The sponsor had no role in the design and conduct of the study; in collection, management, analysis, or interpretation of the data; in preparation, review, or approval of the manuscript; or in the decision to submit for publication. We are also grateful to the NIDDK for supporting C.R. Butler’s time through a training grant (5T32DK007467-33), and to the National Institute of Allergy and Infectious Disease for supporting P.P. Reese through a mentoring grant (K24AI146137-02).

Acknowledgments

We would like to thank William Kreuter in the Department of Pharmacy at the University of Washington for assistance with programming to extract information from Medicare claims.

Dr. Catherine R. Butler and Dr. Ann M. O'Hare designed the study and analyzed the data. Dr. Catherine R. Butler made the tables and figures, and drafted the initial manuscript. All authors contributed to the interpretation and presentation of data, revised the manuscript, and approved the final version of the manuscript.

Ethics approval and consent to participate, consent for publication: The study was approved by the Institutional Review Board at the University of Washington in Seattle, Washington.

Supplemental Material

This article contains the following supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2020030342/-/DCSupplemental.

Supplemental Table 1. USRDS registry codes used to define exposure groups.

Supplemental Table 2. Measures of intensity of end-of-life care by exposure to the transplant process.

Supplemental Table 3. Measures of intensity of end-of-life care among cohort members with a functioning kidney transplant at the time of death by time since transplant.

Supplemental Table 4. Measures of intensity of end-of-life care among cohort members with a failed transplant at the time of death by time since transplant failure.

Supplemental Table 5. Measures of intensity of end-of-life care by exposure to the transplant process for patients who developed ESKD from 2005 to 2008.

Footnotes

  • Published online ahead of print. Publication date available at www.jasn.org.

References

  1. ↵
    1. Wolfe RA,
    2. Ashby VB,
    3. Milford EL,
    4. Ojo AO,
    5. Ettenger RE,
    6. Agodoa LY, et al
    : Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant. N Engl J Med 341: 1725–1730, 1999 pmid:10580071
    OpenUrlCrossRefPubMed
  2. ↵
    1. Rao PS,
    2. Merion RM,
    3. Ashby VB,
    4. Port FK,
    5. Wolfe RA,
    6. Kayler LK
    : Renal transplantation in elderly patients older than 70 years of age: Results from the Scientific Registry of Transplant Recipients. Transplantation 83: 1069–1074, 2007 pmid:17452897
    OpenUrlCrossRefPubMed
  3. ↵
    1. United States Renal Data System
    : 2018 ADR Chapters. Available at: https://www.usrds.org/2018/view/Default.aspx. Accessed March 1, 2020
  4. ↵
    1. O’Hare AM,
    2. Kurella Tamura M,
    3. Lavallee DC,
    4. Vig EK,
    5. Taylor JS,
    6. Hall YN, et al
    : Assessment of self-reported prognostic expectations of people undergoing dialysis: United States Renal Data System Study of Treatment Preferences (USTATE). JAMA Intern Med 179: 1325–1333, 2019 pmid:31282920
    OpenUrlCrossRefPubMed
  5. ↵
    1. Wachterman MW,
    2. Marcantonio ER,
    3. Davis RB,
    4. Cohen RA,
    5. Waikar SS,
    6. Phillips RS, et al
    : Relationship between the prognostic expectations of seriously ill patients undergoing hemodialysis and their nephrologists. JAMA Intern Med 173: 1206–1214, 2013 pmid:23712681
    OpenUrlCrossRefPubMed
  6. ↵
    1. Colman RE,
    2. Curtis JR,
    3. Nelson JE,
    4. Efferen L,
    5. Hadjiliadis D,
    6. Levine DJ, et al
    : Barriers to optimal palliative care of lung transplant candidates. Chest 143: 736–743, 2013 pmid:22922517
    OpenUrlCrossRefPubMed
  7. ↵
    1. Song MK,
    2. De Vito Dabbs A,
    3. Studer SM,
    4. Arnold RM
    : Palliative care referrals after lung transplantation in major transplant centers in the United States. Crit Care Med 37: 1288–1292, 2009 pmid:19242344
    OpenUrlCrossRefPubMed
  8. ↵
    1. Walling AM,
    2. Asch SM,
    3. Lorenz KA,
    4. Wenger NS
    : Impact of consideration of transplantation on end-of-life care for patients during a terminal hospitalization. Transplantation 95: 641–646, 2013 pmid:23197177
    OpenUrlPubMed
  9. ↵
    1. Lange AV,
    2. Rueschhoff A,
    3. Terauchi S,
    4. Cohen L,
    5. Reisch J,
    6. Jain R, et al
    : End-of-Life care in cystic fibrosis: Comparing provider practices based on lung transplant candidacy [published online ahead of print May 7, 2020]. J Palliat Med pmid:32380886
    OpenUrlPubMed
  10. ↵
    1. Ufere NN,
    2. Halford JL,
    3. Caldwell J,
    4. Jang MY,
    5. Bhatt S,
    6. Donlan J, et al
    : Health care utilization and end-of-life care outcomes for patients with decompensated cirrhosis based on transplant candidacy. J Pain Symptom Manage 59: 590–598, 2020 pmid:31655192
    OpenUrlPubMed
  11. ↵
    1. Poonja Z,
    2. Brisebois A,
    3. van Zanten SV,
    4. Tandon P,
    5. Meeberg G,
    6. Karvellas CJ
    : Patients with cirrhosis and denied liver transplants rarely receive adequate palliative care or appropriate management. Clin Gastroenterol Hepatol 12: 692–698, 2014 pmid:23978345
    OpenUrlPubMed
  12. ↵
    1. Kathpalia P,
    2. Smith A,
    3. Lai JC
    : Underutilization of palliative care services in the liver transplant population. World J Transplant 6: 594–598, 2016 pmid:27683638
    OpenUrlPubMed
  13. ↵
    1. Bayoumi E,
    2. Sheikh F,
    3. Groninger H
    : Palliative care in cardiac transplantation: An evolving model. Heart Fail Rev 22: 605–610, 2017 pmid:28474326
    OpenUrlPubMed
  14. ↵
    1. Nolley EP,
    2. DeSensi R,
    3. Nouraie M,
    4. Schenker Y,
    5. Morrell MR
    : Characteristics, trends, and predictors of specialty palliative care utilization after lung transplantation. J Palliat Med 22: 1092–1098, 2019 pmid:30964390
    OpenUrlPubMed
  15. ↵
    1. Kousoulas L,
    2. Neipp M,
    3. Barg-Hock H,
    4. Jackobs S,
    5. Strassburg CP,
    6. Klempnauer J, et al
    : Health-related quality of life in adult transplant recipients more than 15 years after orthotopic liver transplantation. Transpl Int 21: 1052–1058, 2008 pmid:18680483
    OpenUrlPubMed
  16. ↵
    1. Nakagawa S,
    2. Garan AR,
    3. Takayama H,
    4. Takeda K,
    5. Topkara VK,
    6. Yuzefpolskaya M, et al
    : End of life with left ventricular assist device in both bridge to transplant and destination therapy. J Palliat Med 21: 1284–1289, 2018 pmid:29874117
    OpenUrlPubMed
  17. ↵
    1. Hauptman PJ,
    2. O’Connor KJ
    : Procurement and allocation of solid organs for transplantation. N Engl J Med 336: 422–431, 1997 pmid:9010150
    OpenUrlCrossRefPubMed
  18. ↵
    1. United States Renal Data System
    : Chapter 12: End-of-life care for patients with end-stage renal disease: 2000-2014. Available at: https://www.usrds.org/2017/view/v2_12.aspx. Accessed March 1, 2020
  19. ↵
    1. Dunn OJ
    : Multiple comparisons among means. J Am Stat Assoc 56: 52–64, 1961
    OpenUrlCrossRef
  20. ↵
    1. von Elm E,
    2. Altman DG,
    3. Egger M,
    4. Pocock SJ,
    5. Gøtzsche PC,
    6. Vandenbroucke JP; STROBE Initiative
    : The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Lancet 370: 1453–1457, 2007 pmid:18064739
    OpenUrlCrossRefPubMed
  21. ↵
    R Core Team: R: A language and environment for statistical computing. Vienna, Austria, R Foundation for Statistical Computing, 2019. Available at: https://www.R-project.org/ [computer program]
  22. ↵
    1. Wong SP,
    2. Kreuter W,
    3. O’Hare AM
    : Treatment intensity at the end of life in older adults receiving long-term dialysis. Arch Intern Med 172: 661–663; discussion 663–664, 2012pmid:22529233
    OpenUrlCrossRefPubMed
  23. ↵
    1. Wachterman MW,
    2. Pilver C,
    3. Smith D,
    4. Ersek M,
    5. Lipsitz SR,
    6. Keating NL
    : Quality of end-of-life care provided to patients with different serious illnesses. JAMA Intern Med 176: 1095–1102, 2016 pmid:27367547
    OpenUrlCrossRefPubMed
  24. ↵
    1. Baddour NA,
    2. Siew ED,
    3. Robinson-Cohen C,
    4. Salat H,
    5. Mason OJ,
    6. Stewart TG, et al
    : Serious illness treatment preferences for older adults with advanced CKD. J Am Soc Nephrol 30: 2252–2261, 2019 pmid:31511360
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Davison SN
    : End-of-life care preferences and needs: Perceptions of patients with chronic kidney disease. Clin J Am Soc Nephrol 5: 195–204, 2010 pmid:20089488
    OpenUrlAbstract/FREE Full Text
  26. ↵
    1. Kaufman S
    : Ordinary Medicine: Extraordinary Treatments, Longer Lives, and Where to Draw the Line, Durham, NC, Duke University Press, 2015
  27. ↵
    1. Halpern SD,
    2. Loewenstein G,
    3. Volpp KG,
    4. Cooney E,
    5. Vranas K,
    6. Quill CM, et al
    : Default options in advance directives influence how patients set goals for end-of-life care. Health Aff (Millwood) 32: 408–417, 2013 pmid:23381535
    OpenUrlAbstract/FREE Full Text
  28. ↵
    1. Renal Physicians Association
    : Shared Decision-Making in the Appropriate Initiation of and Withdrawal from Dialysis, 2nd Ed., Rockville, MD, Renal Physicians Association, American Society of Nephrology, 2010
  29. ↵
    1. Davison SN,
    2. Levin A,
    3. Moss AH,
    4. Jha V,
    5. Brown EA,
    6. Brennan F, et al; Kidney Disease: Improving Global Outcomes
    : Executive summary of the KDIGO controversies conference on supportive care in chronic kidney disease: Developing a roadmap to improving quality care. Kidney Int 88: 447–459, 2015 pmid:25923985
    OpenUrlCrossRefPubMed
  30. ↵
    1. Freeman N,
    2. Le LW,
    3. Singer LG,
    4. Colman R,
    5. Zimmermann C,
    6. Wentlandt K
    : Impact of a transplant palliative care clinic on symptoms for patients awaiting lung transplantation. J Heart Lung Transplant 35: 1037–1039, 2016 pmid:27311372
    OpenUrlPubMed
  31. ↵
    1. Schwarz ER,
    2. Baraghoush A,
    3. Morrissey RP,
    4. Shah AB,
    5. Shinde AM,
    6. Phan A, et al
    : Pilot study of palliative care consultation in patients with advanced heart failure referred for cardiac transplantation. J Palliat Med 15: 12–15, 2012 pmid:22216757
    OpenUrlCrossRefPubMed
  32. ↵
    1. Baumann AJ,
    2. Wheeler DS,
    3. James M,
    4. Turner R,
    5. Siegel A,
    6. Navarro VJ
    : Benefit of early palliative care intervention in end-stage liver disease patients awaiting liver transplantation. J Pain Symptom Manage 50: 882–886.e2, 2015 pmid:26303186
    OpenUrlPubMed
  33. ↵
    1. Lamba S,
    2. Murphy P,
    3. McVicker S,
    4. Harris Smith J,
    5. Mosenthal AC
    : Changing end-of-life care practice for liver transplant service patients: Structured palliative care intervention in the surgical intensive care unit. J Pain Symptom Manage 44: 508–519, 2012 pmid:22765967
    OpenUrlCrossRefPubMed
  34. ↵
    1. Lim CE,
    2. Ng RW,
    3. Cheng NC,
    4. Cigolini M,
    5. Kwok C,
    6. Brennan F
    : Advance care planning for haemodialysis patients. Cochrane Database Syst Rev 7: CD010737, 2016 pmid:27457661
    OpenUrlPubMed
  35. ↵
    1. O’Halloran P,
    2. Noble H,
    3. Norwood K,
    4. Maxwell P,
    5. Shields J,
    6. Fogarty D, et al
    : Advance care planning with patients who have end-stage kidney disease: A systematic realist review. J Pain Symptom Manage 56: 795–807.e18, 2018 pmid:30025939
    OpenUrlPubMed
  36. ↵
    1. O’Riordan J,
    2. Noble H,
    3. Kane PM,
    4. Smyth A
    : Advance care plan barriers in older patients with end-stage renal disease: A qualitative nephrologist interview study [published online ahead of print June 25, 2019]. BMJ Support Palliat Care doi:10.1136/bmjspcare-2018-001759pmid:31239255
    OpenUrlPubMed
  37. ↵
    1. Ortega T,
    2. Deulofeu R,
    3. Salamero P,
    4. Roman A,
    5. Masnou N,
    6. Rubio S, et al; Y Red Temática de Investigatión en Trasplante
    : Health-related Quality of Life before and after a solid organ transplantation (kidney, liver, and lung) of four Catalonia hospitals. Transplant Proc 41: 2265–2267, 2009 pmid:19715893
    OpenUrlCrossRefPubMed
  38. ↵
    1. Dobbels F,
    2. Wernli-Fluri C,
    3. Denhaerynck K,
    4. Dickenmann M,
    5. Vanrenterghem Y,
    6. Dupont L, et al
    : Comparison of perceived health status among solid organ transplant candidates. Clin Transplant 24: 660–668, 2010 pmid:19925463
    OpenUrlCrossRefPubMed
  39. ↵
    1. Wall A,
    2. Lee GH,
    3. Maldonado J,
    4. Magnus D
    : Medical contraindications to transplant listing in the USA: A survey of adult and pediatric heart, kidney, liver, and lung programs. World J Surg 43: 2300–2308, 2019 pmid:31111229
    OpenUrlPubMed
  40. ↵
    1. Larson AM,
    2. Curtis JR
    : Integrating palliative care for liver transplant candidates: “too well for transplant, too sick for life”. JAMA 295: 2168–2176, 2006 pmid:16684988
    OpenUrlCrossRefPubMed
  41. ↵
    1. Hart A,
    2. Smith JM,
    3. Skeans MA,
    4. Gustafson SK,
    5. Wilk AR,
    6. Castro S, et al
    : OPTN/SRTR 2017 annual data report: Kidney. Am J Transplant 19[Suppl 2]: 19–123, 2019 pmid:30811893
    OpenUrlCrossRefPubMed
  42. ↵
    1. Colman R,
    2. Singer LG,
    3. Barua R,
    4. Downar J
    : Outcomes of lung transplant candidates referred for co-management by palliative care: A retrospective case series. Palliat Med 29: 429–435, 2015 pmid:25634636
    OpenUrlCrossRefPubMed
  43. ↵
    1. Bogue Kerr S,
    2. Soulière M,
    3. Bell L
    : The transliminal self: The Ebb and flow of the kidney transplant experience. Qual Health Res 28: 561–571, 2018 pmid:29216809
    OpenUrlPubMed
  44. ↵
    1. Crowley-Matoka M
    : Desperately seeking “normal”: The promise and perils of living with kidney transplantation. Soc Sci Med 61: 821–831, 2005 pmid:15950094
    OpenUrlCrossRefPubMed
  45. ↵
    1. Kaufman S
    : Fairness and the tyranny of potential in kidney transplantation. Curr Anthropol 54: S56–S66, 2013
    OpenUrl
  46. ↵
    1. Shim JK,
    2. Russ AJ,
    3. Kaufman SR
    : Risk, life extension and the pursuit of medical possibility. Sociol Health Illn 28: 479–502, 2006 pmid:16669809
    OpenUrlPubMed
  47. ↵
    1. Tong A,
    2. Hanson CS,
    3. Chapman JR,
    4. Halleck F,
    5. Budde K,
    6. Josephson MA, et al
    : ‘Suspended in a paradox’-patient attitudes to wait-listing for kidney transplantation: Systematic review and thematic synthesis of qualitative studies. Transpl Int 28: 771–787, 2015 pmid:25847569
    OpenUrlCrossRefPubMed
  48. ↵
    1. Molmenti EP,
    2. Dunn GP
    : Transplantation and palliative care: The convergence of two seemingly opposite realities. Surg Clin North Am 85: 373–382, 2005 pmid:15833478
    OpenUrlCrossRefPubMed
  49. ↵
    1. Wentlandt K,
    2. Weiss A,
    3. O’Connor E,
    4. Kaya E
    : Palliative and end of life care in solid organ transplantation. Am J Transplant 17: 3008–3019, 2017 pmid:28976070
    OpenUrlPubMed
  50. ↵
    1. Calestani M,
    2. Tonkin-Crine S,
    3. Pruthi R,
    4. Leydon G,
    5. Ravanan R,
    6. Bradley JA, et al; ATTOM Investigators
    : Patient attitudes towards kidney transplant listing: Qualitative findings from the ATTOM study. Nephrol Dial Transplant 29: 2144–2150, 2014 pmid:24997006
    OpenUrlCrossRefPubMed
  51. ↵
    1. Spiers J,
    2. Smith JA
    : Waiting for a kidney from a deceased donor: An interpretative phenomenological analysis. Psychol Health Med 21: 836–844, 2016 pmid:26584590
    OpenUrlPubMed
  52. ↵
    1. Norman SP,
    2. Kommareddi M,
    3. Luan FL
    : Inactivity on the kidney transplant wait-list is associated with inferior pre- and post-transplant outcomes. Clin Transplant 27: E435–E441, 2013 pmid:23923971
    OpenUrlPubMed
  53. ↵
    1. Grams ME,
    2. Massie AB,
    3. Schold JD,
    4. Chen BP,
    5. Segev DL
    : Trends in the inactive kidney transplant waitlist and implications for candidate survival. Am J Transplant 13: 1012–1018, 2013 pmid:23399028
    OpenUrlCrossRefPubMed
  54. ↵
    1. Sudore RL,
    2. Fried TR
    : Redefining the “planning” in advance care planning: Preparing for end-of-life decision making. Ann Intern Med 153: 256–261, 2010 pmid:20713793
    OpenUrlCrossRefPubMed
  55. ↵
    1. Krawczyk M,
    2. Gallagher R
    : Communicating prognostic uncertainty in potential end-of-life contexts: Experiences of family members. BMC Palliat Care 15: 59, 2016 pmid:27405352
    OpenUrlPubMed
  56. ↵
    1. Etkind SN,
    2. Koffman J
    : Approaches to managing uncertainty in people with life-limiting conditions: Role of communication and palliative care. Postgrad Med J 92: 412–417, 2016 pmid:27129911
    OpenUrlAbstract/FREE Full Text
  57. ↵
    1. Back AL,
    2. Arnold RM,
    3. Quill TE
    : Hope for the best, and prepare for the worst. Ann Intern Med 138: 439–443, 2003 pmid:12614110
    OpenUrlCrossRefPubMed
  58. ↵
    1. Davies JM,
    2. Sleeman KE,
    3. Leniz J,
    4. Wilson R,
    5. Higginson IJ,
    6. Verne J, et al
    : Socioeconomic position and use of healthcare in the last year of life: A systematic review and meta-analysis. PLoS Med 16: e1002782, 2019 pmid:31013279
    OpenUrlPubMed
Back to top

In this issue

View Selected Citations (0)
Print
Download PDF
Email Article
Citation Tools
Request Permissions
End-of-Life Care among US Adults with ESKD Who Were Waitlisted or Received a Kidney Transplant, 2005–2014
Catherine R. Butler, Peter P. Reese, James D. Perkins, Yoshio N. Hall, J. Randall Curtis, Manjula Kurella Tamura, Ann M. O'Hare
JASN Oct 2020, 31 (10) 2424-2433; DOI: 10.1681/ASN.2020030342
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo

Jump to section

Keywords