Post-transfer predictors of poor outcomes in pediatric renal transplant recipients.
Historically, the transfer of care occurred during moments of crisis, such as pregnancy, increase in risk-taking behaviors, or periods of mental distress, leading to poor outcomes, such as an increase in nonadherence behaviors, the number of patients lost to follow up, and disease complications (Pote et al., 2008; Viner, 1999; Watson, 2000). Specifically, research on kidney transplant recipients has shown there is an increase in kidney transplant failure rate (from 30% to 35%) as youth transition care from pediatric to adult providers (Harden et al, 2012; Pote et al, 2008; Watson, 2000). However, there has been little research on post-transfer predictors that may lead to graft loss after transfer of care, such as medication nonadherence, acute rejection, and change in kidney function, which can also serve as "red flags" to help identify those medically at-risk for graft loss after transfer of care. Other medically at-risk adolescents, such as survivors of childhood cancer, have been identified for increased monitoring due to risky behaviors related to health outcomes and can serve as an example for development of a clinical profile to help improve adolescent decision making (Hollen, 2000; Tercyak, Britto, Hanna, Hollen, & Hudson, 2008).
Medication Nonadherence and Graft Loss
Medication nonadherence after transplantation has been shown to be an independent risk factor for late graft loss, accounting for as much as 35% of grafts lost in all transplant recipients (Butkus, Dottes, Meydrech, & Barber, 2001; Butler, Roderick, Mullee, Mason, & Peveler, 2004). Additionally, medication nonadherence has been linked to chronic graft nephropathy, which often has a further impact on long-term graft outcomes (Chisholm, 2002). Youth specifically have a seven-fold increased risk of graft failure with medication nonadherence (Butler et al., 2004). This is a significant issue; between 5% to 57% of adolescents with kidney transplants have been nonadherent at some point in time (Achille, Ouellette, Fournier, Vachon, & Hebert, 2006; Butler et al., 2004; Connelly et al., 2015; Pabst, Bertram, Zimmermann, Schiffer, & de Zwaan, 2015; Watson, 2005; Wolff, Strecker, Vester, Latta, & Ehrich, 1998).
Medication nonadherence in the adolescent young adult can be linked to developmental changes. To date, neuroscience substantiates that the adolescent brain may not be fully developed until the early to middle 20s, as demonstrated by studies using functional magnetic resonance imaging (MRI) (Casey, Jones, & Hare, 2008; Institute of Medicine & National Research Council Committee on the Science of Adolescence, 2011; Johnson, Blum, & Giedd, 2009; Luna et al., 2001). The immaturity of the executive function of the brain (the functions of self-regulation, flexibility, response inhibition, planning, and organization of behavior), in conjunction with the emotional brain function from the limbic system, may have an impact on adherence in this population because youth feel invincible and focus on immediate consequences versus long-term outcomes (Giedd et al., 1999; Hsu, 2005; Institute of Medicine & National Research Council Committee on the Science of Adolescence, 2011; Johnson et al., 2009). This delayed cognitive development combined with the emotional impact of peer pressure and the adolescent sense of invincibility often lead to risky behaviors, such as experimenting with illicit substances or careless nonadherence by the adolescent transplant recipient. Given the risk of medication nonadherence in this population of adolescents and the impact of medication nonadherence on graft survival, it is essential to monitor for deliberate or careless nonadherent behaviors and risk factors for nonadherence, particularly in relation to medications.
Acute Rejection and Graft Loss
The increase in nonadherent behaviors puts the adolescent and young adult with a history of kidney transplantation at risk for acute rejection of the transplanted kidney, which can lead to subsequent graft loss (Feinstein et al., 2005; Warady, Mudge, Wiser, Wiser, & Rader, 1996). Acute rejection remains a significant cause of graft loss in adolescents with kidney transplants. Specifically, data from O PTN (2016) show that the five-year graft survival for adolescents is lowest among all pediatric patients at 69% compared to over 80% for other pediatric recipients. Acute rejection is listed as the cause for graft loss in 14% of adolescents compared to 7% of other age groups, and nonadherence is listed as the cause of acute rejection in 12% of adolescents compared to 3% in others (OPTN, 2016). Acute rejection episodes in kidney transplant recipients are important to monitor because the incidence of acute rejection is the most accepted short-term surrogate marker of long-term graft survival (Fleiner, Fritsche, Glander, Neumayer, & Budde, 2006). Because of this, acute rejection episodes are often used as clinical endpoints in randomized controlled trials on transplant recipients. Thus, in addition to measuring nonadherent behavior, monitoring the number of acute rejection episodes within a defined time period after transfer of care in adolescents and young adults with a history of a kidney transplant is warranted.
Change in Kidney Function and Loss of Graft Over Time
A study from the United Kingdom retrospectively evaluated 20 young adults (15.7 to 20.9 years) who had transferred from pediatric to adult providers (Watson, 2000). The researcher examined evidence of nonadherence, graft loss, and other poor outcomes. Seven of the 20 patients had an unexpected loss of the transplanted kidney within 31 months after transfer; 86% of patients who lost their graft lost it within the first 24 months after transfer. Nonadherence was thought to be a major factor in the loss of the grafts, although this was difficult to prove. Another study conducted at the University of Pennsylvania found similar results (Pote et al., 2008). In this study, 41 records of kidney transplant recipients who had transferred from pediatric to adult providers were retrospectively analyzed. Within 31 months after transfer, nearly one-third (31.5%) of patients lost their transplant, with half of those having documented nonadherence. Results of these studies support the need for further research examining graft outcomes and predictors for graft loss after the transfer from pediatric to adult healthcare services.
Currently, there is little evidence on the incidence of poor outcomes after transfer of care and on specific predictors that could serve as "red flags" to foretell graft loss after the transfer of care of pediatric transplant recipients to adult providers. The aims of this study were twofold: 1) to describe the post-transfer (defined as from pediatric to adult providers) incidence of predictors (medication nonadherence, acute rejection, and change in kidney function), as well as outcomes (graft loss) for adolescent and young adult kidney transplant recipients during a three-year post-transfer follow-up period; and 2) to identify variables to monitor these predictors, in the form of a clinical profile, so providers can promote early intervention for these medically at-risk adolescents.
Design, Data Source, and Study Sample for Primary Aim
This study used data derived from methods previously described (Coyne, Hollen, Yan, & Brayman, 2016). A retrospective, longitudinal, descriptive design using secondary data from a national database was conducted. This study used data from the Scientific Registry of Transplant Recipients (SRTR), which includes data on all donor, wait-listed candidates, and transplant recipients in the United States, submitted by the members of the O PTN and has been described elsewhere (SRTR 2017). The Health Resources and Services Administration (HRSA), U.S. Department of Health and Human Services, provides oversight to the activities of the O PTN and SRTR contractors.
Data on individuals were included in the analysis using four criteria: 1) aged 16 to 25 years, 2) who received a kidney transplant while under the care of a pediatric provider at least six months prior to transfer, 3) who transferred care from a pediatric to adult provider at least two years prior to data extraction, and 4) had functioning graft at the time of transfer. Data were excluded for exceptions, such as ABO incompatible transplants, those who had a serum creatinine greater than 3 mg/dL at the time of transfer, those who died with a functioning graft within the three years after transfer, with a history of delayed graft function, were diagnosed with a post-transplant lymphoproliferative disorder (PTLD), or with recurrent disease or a de novo glomerulonephritis because these exclusions are independent risk factors for late graft loss (Butkus et al., 2001; Feldman et al., 1996, 1998; Hariharan et al., 2002; Johnson, Cherikh, Kauffman, Pavlakis, & Hanto, 2006; Parada et al., 2006).
Procedures for Primary Aim
After approval by the Institutional Review Board and the data source body, SRTR data were extracted by yearly intervals from two years prior to transfer to three years after the transfer of care. The date of transfer was created by using National Provider Identifiers (NPI) or Unique Physician Identification Numbers (UPIN). The NPI and UPIN numbers were identified as either pediatric or adult providers using the National Provider Identifier Database. Surgeons and urologists were included as pediatric providers if their scope of practice included children. Cases in which the NPI/UPIN number changed from one transplant follow-up file to the following transplant follow-up file were captured. Those individuals who were initially followed by a pediatric provider but were subsequently followed by an adult provider were selected. The date of the last follow-up form with an NPI number of a pediatric provider was used as a proxy for the date of transfer of care.
Study Variables for Primary Aim
The incidence of three predictors (medication nonadherence, acute rejection, and change in kidney function) and one outcome (graft loss) were analyzed. Data from two years prior to transfer were used as baseline data at the time of transfer for the three predictors. Follow-up data were extracted yearly during the three-year post transfer follow-up period.
Medication nonadherence. The term nonadherence versus noncompliance is used more readily in the current literature; however, SRTR data use the term noncompliance. For this study, nonadherence will be used to report SRTR noncompliance data to be consistent with current literature. Medication noncompliance in the SRTR database is based on the transplant center's reporting. The specific question related to medication noncompliance states, "Was there evidence of noncompliance with immunosuppression medication during this follow-up period that compromised the patient's recovery?" Answer options are (1) Yes, (2) No, or (3) Unknown. Any cases with "yes" were counted as an episode of noncompliance. If individuals had evidence of noncompliance in the two years prior to transfer, they were counted as being noncompliant at baseline.
Acute rejection. Acute rejection in the SRTR database is based on transplant center reports. The specific question addressing acute rejection states, "Did the patient have any acute rejection episodes during the follow-up period?" Selection options were: 1) Yes, at least one episode treated with anti-rejection agent; 2) Yes, but none treated with additional anti-rejection agent; 3) No; or 4) Unknown. Selections of either "Yes, at least one episode treated with anti-rejection agent" or "Yes, but none treated with additional anti-rejection agent" were counted as an episode of acute rejection. If individuals had an acute rejection episode in the two years prior to transfer, they were counted as having acute rejection at baseline.
Change in kidney function. Serum creatinine was used as a proxy for kidney function. Serum creatinine (mg/dL) values from two years prior to transfer were averaged and used to estimate kidney function at the time of transfer. Change in kidney function was computed from yearly serum creatinine values compared to baseline.
Graft loss. SRTR data listed the date of graft loss for those who lost their graft. Data were verified to confirm the date of graft loss was after the date of transfer of care by creating a time variable from transfer to graft loss.
Statistical Analyses for Primary Aim
Descriptive statistics were used to describe the incidence of post-transfer predictors and outcomes over the three years of post-transfer. Medication nonadherence, acute rejection, and change in kidney function were reported for patients at the time of transfer from pediatric to adult providers, and at one year, two years, and three years post-transfer. Graft loss was reported at one year, two years, and three years post-transfer.
Methods for Secondary Aim
To develop a preliminary clinical profile for early identification of those at-risk for poor outcomes, predictors from the SRTR database were combined with previously published literature on poor outcomes after transfer of care. CINAHL and Ovid Medline were searched for articles that evaluated outcomes in pediatric transplant recipients (liver and kidney) after transfer of care from pediatric to adult providers.
From the possible 13,840 youth available, 250 cases met the eligibility criteria and were analyzed as previously described (see Figure 1) (Coyne et al., 2016). Patient characteristics at the time of transfer of care are presented in Table 1. The mean age at transfer was 19.5 years (SD, [+ or -] 2.0 years). Most individuals were adolescents at the time of transplant (mean age 15.1 years; SD, [+ or -] 3.4). The majority of adolescents were males (59%), received a living donor kidney transplant (57%), and were Caucasian (60%). Of these, 92 (37%) had a glomerulonephritis as a cause of kidney failure followed by 79 (32%) with a congenital anomaly. The average time from transplant to transfer was 4.4 years (SD, [+ or -] 3.2 years).
The incidence of post-transfer predictors (medication nonadherence, acute rejection, change in kidney function) and the outcome of graft loss were analyzed by post-transfer time (see Table 2). The incidence of medication nonadherence increased by year post-transfer, with an incidence of medication nonadherence of 14 (5.6%) at one year post-transfer, 21 (8.4%) at two years post-transfer, and 29 (11.6%) at three years post-transfer. Acute rejection episodes also increased by year post-transfer, with an incidence of acute rejection of 11 (4.4%) at one year post-transfer, 21 (8.4%) at two years post-transfer, and 27 (10.8%) at three years post-transfer. Serum creatinine values increased after transfer of care, with an average increase in serum creatinine of 27.8% from transfer to three years post-transfer. Of the 250 cases, 61 (24.4%) lost their graft during the three-year follow-up time period. Among the 61 individuals who lost their graft, 16 (26%) lost their graft in the first year post-transfer, 22 (36%) in the second year post-transfer, and 23 (38%) in the third year. The average time to graft loss after transfer of care was 20.8 months with a range of 3 to 36 months. Missing data on all predictors increased yearly after transfer. Data remained consistent when those with missing data at baseline were excluded.
Three variables for monitoring graft loss were identified from the primary aim of this study: medication nonadherence, acute rejection, and change in kidney function. Additionally, nine studies published from 2002-2012 were identified with additional predictors of poor outcomes (graft loss, death) for adolescent and young adult kidney transplant recipients (see Table 3). Additional predictors previously reported in the literature included nonadherence, acute rejection, kidney function, loss to follow-up, and hospitalization rates.
In four of the nine (44%) studies reporting on outcomes after transfer of care, nonadherence was evaluated (Annunziata et al, 2007; Pote et al, 2008; Remorino & Taylor, 2006; Watson, 2000). Three of these four studies monitored nonadherence using a subjective measure of nonadherence. Pote et al. (2008) and Remorino and Taylor (2006) relied on the provider's subjective assessment of adherence. Watson (2000) utilized the patient's subjective report of adherence. Two studies reported an objective measure of adherence (Annunziata et al, 2007; Watson, 2000). Annunziata et al. (2007) used standard deviation of tacrolimus levels as a proxy for adherence as previously this was shown to be an accurate predictor of adherence in liver transplant recipients (Shemesh et al, 2004). Watson (2000) used undetectable cyclosporine levels as a proxy for nonadherence.
Five of the nine (56%) studies evaluated acute rejection episodes after transfer of care (Annunziato et al, 2007; Chaturvedi, Jones, Walker, & Sawyer, 2009; Koshy, Hebert, Lam, Stukel, & Guttmann A, 2009; Remorino & Taylor, 2006; van den Heuvel et al, 2010). Four of these (80%) counted only biopsy-proven acute rejection as acute rejection episodes. Change in kidney function was monitored in five (56%) of the nine studies (Chaturvedi et al, 2009; Prestidge, Romann, Djurdjev, & Matsuda-Abedini, 2012; Remorino & Taylor, 2006; van den Heuvel et al, 2010; Watson, 2000). In all studies, serum creatinine was used as a proxy for kidney function. Only two (22%) studies monitored for loss of follow-up (Chaturvedi et al, 2009; Remorino & Taylor, 2006). Chaturvedi et al. (2009) monitored clinic attendance rates while Remorino and Taylor (2006) counted the number of missed clinic appointments. Three studies (33%) included hospitalization rates in their analyses (Chaturvedi et al, 2009; Koshy et al, 2009; Remorino & Taylor, 2006). Two studies (Chaturvedi et al, 2009; Remorino & Taylor, 2006) counted inpatient days; only one study (Koshy et al, 2009) only included hospitalization days for acute rejection or kidney biopsy.
In this study, using secondary data analysis from a national database, the incidence of predictors for poor outcomes was fairly consistent post-transfer. Predictors analyzed in this study (medication nonadherence, acute rejection, and change in kidney function) combined with the six predictors for poor outcomes after transfer identified from a review of the literature aid in the development of a preliminary clinical profile for early identification of those at most risk for poor outcomes after transfer of care (see Table 4). The six suggested predictors for monitoring during the first three years after transfer are: 1) self-report of nonadherence and related behaviors (medication adherence, substance abuse, and impact of peer pressure), 2) objective measure of medication nonadherence (measured using standard deviation of tacrolimus levels), 3) episodes of acute rejection, 4) serum creatinine as a proxy for kidney function (a change in serum creatinine greater than 0.3 mg/dL during a six-month period), 5) monitoring for loss to follow-up (missed clinic appointment, laboratory studies), and 6) number and type of hospitalizations.
Previous studies report that between 5% to 57% of adolescents with kidney transplants have been nonadherent at some point in time (Achille et al., 2006; Butler et al 2004; Watson, 2000; Wolff et al, 1998). In this study, the overall incidence of medication nonadherence after transfer of care was small, with only 29 (11.6%) individuals having documented medication nonadherence within the first three years after transfer. The method of identifying the medication nonadherence in the dataset, subjective report by provider, may have contributed to the low incidence of nonadherence in this study. Using the provider's subjective assessment of nonadherence has been shown to underestimate nonadherence because previous work has demonstrated a poor correlation between provider assessment of nonadherence and outcomes (Shemesh et al, 2004).
In the literature, others have analyzed objective measures of adherence. In one small, retrospective study in 14 liver transplant recipients, medication nonadherence (measured using standard deviation of tacrolimus levels) was found to increase after transfer of care from pediatric to adult services (Annunziato et al, 2007). In that study, there was a significant increase in nonadherence in the first year after transfer; the increase in nonadherence in the second year post-transfer also approached statistical significance, and there was a significant increase in nonadherence during the entire four-year post-transfer period (Annunziato et al, 2007). In this current descriptive study, the incidence of medication nonadherence also increased over the three-year post-transfer period, from to 12 (5%) at transfer to 14 (5.6%) at one year post-transfer, to 21 (8.4%) at two years post-transfer, to 29 (11.6%) at three years post-transfer. These results highlight the importance of monitoring for medication nonadherence both subjectively and objectively for at least three years after transfer of care.
Rates of acute rejection have been decreasing overall since the 1990s due to changes in immunosuppression regimens (Meier-Kriesche, Schold, Srinivas, & Kaplan, 2004). Since 1987, the North American Pediatric Renal Trials and Collaborative Studies (NAPRTCS) collected data on pediatric transplant recipients. To date, NAPRTCS has collected data on 10,762 transplants performed in pediatric patients. In 2008, NAPRTCS examined the percentage of individuals by age who experienced their first rejection episode late (defined as greater than 12 months after transplantation) and found 19.7% of individuals over the age of 12 years experienced a late acute rejection versus 17.1% in individuals under the age of 12 years (NAPRTCS, 2008). There are limited data, however, on acute rejection rates, specifically after the transfer of care. One study in The Netherlands evaluated acute rejection episodes after transfer of care and found no increase in acute rejection (van den Heuvel et al, 2010). In this current descriptive study, acute rejection rates increased after transfer of care, from 11 (4%) to 27 (10.8%) during the three-year post-transfer interval. These results demonstrate the importance of monitoring for acute rejection episodes. Late acute rejection has been found to be a risk factor in the development of chronic allograft nephropathy (CAN), now one of the most common causes of graft loss (Keith, Cantarovich, Paraskevas, & Tchervenkov, 2006; Matas, 2000). In a large database analysis of pediatric renal transplant recipients, late acute rejection increased the risk of graft failure of CAN by 3.6-fold (Tejani, Ho, Emmett & Stablein, 2002). Thus, acute rejection episodes after transfer of care will be important to monitor both clinically and in future studies examining outcomes in adolescent and young adult kidney transplant recipients who are transferring care.
Change in Kidney Function
In this descriptive study, serum creatinine as a proxy for kidney function increased after transfer, with an average increase in serum creatinine of 27.8% from transfer to three years post-transfer. Previous small center studies have failed to find a significant change in kidney function after transfer of care. One study in Australia reported on 11 patients two years after transfer of care and found serum creatinine values to be stable during the follow-up time period (Chaturvedi et al, 2009). Another study with a larger sample examined a cohort of 162 patients in The Netherlands; this study also failed to find any significant change in serum creatinine values during a three-year post-transfer period (van den Heuvel et al, 2010).
Previous research on renal transplant recipients (all ages) has evaluated change in serum creatinine as a predictor of graft loss. Findings have shown that a change in serum creatinine greater than 0.3 mg/dL during a six-month period increased the risk of graft loss by 2.3 times (Fernandez-Fresnedo et al., 2005; Hariharan et al., 2002; Helal et al., 2009). In this current descriptive study, the average change in serum creatinine from transfer to three years post-transfer was +0.35 mg/dl. This change in kidney function, reaching the previously researched significant change of 0.3 mg/dL/year, is important to monitor after transfer because serum creatinine is a sensitive marker for early changes in graft function (Fernandez-Fresnedo et al., 2005; Hariharan et al., 2002; Helal et al., 2009). Adolescents and young adults who have a decline in kidney function (increase in serum creatinine) after transfer of care should be identified and monitored closely for medication nonadherence or acute rejection to prevent graft loss.
Loss to Follow-Up
In this current study, there was an increase in missing data each year after transfer of care for these adolescent and young adult transplant recipients. This increase in missing data seen in the years post-transfer may signal an increase in the patients lost to follow-up after transfer. One small, single-center study with 11 patients (ages 18 to 23 years at the time of transfer) in Australia found a decrease in proportion of scheduled appointment attendance after transfer of care from 61 (73%) of clinic appointments attended prior to transfer to 57% after transfer (Chaturvedi et al., 2009). Another small English study with 16 patients (aged 17 to 20 years at the time of transfer) also found a higher rate of missed follow-up appointments in the one-year time period after transfer of care (Remorino & Taylor, 2006).
With few studies and small samples, this warrants further study. It is hypothesized that further study with a large dataset may demonstrate that follow-up with clinic appointments, frequency of laboratory studies, and other testing decreases after transfer of care, and thus, may have an impact on the health of youth with a transplanted kidney. Adolescents and young adults who are lost to follow-up after transfer of care may be at increased risk for poor outcomes and early recognition, and interventions may be helpful to ensure close follow-up for long-term graft stability.
The descriptive portion of this study did not evaluate hospitalization rates after transfer of care. However, in the literature reviewed, three studies (33%) included hospitalization rates in their analyses (Chaturvedi et al., 2009; Koshy et al., 2009; Remorino & Taylor, 2006). Hospitalization rates are likely an indicator of poor disease management and could signal an increased risk of poor outcomes. Thus, monitoring hospitalization rates is recommended after transfer of care.
Previous studies on the transfer of care for adolescent and young adult kidney transplant recipients have demonstrated an increase in graft loss. In this current study, 61 (24.4%) individuals lost their graft within three years after transfer of care. These results are slightly lower than the previously reported literature on transfer of care in pediatric kidney transplant recipients; however, this study only examined graft loss during the first three years after transfer of care. Two studies specifically found an increased risk of graft loss (30% to 35%) up to 31 months after the transfer of care (Pote et al, 2008; Watson, 2000). While another study examining a transition model for the transfer of care of adolescent and young adult kidney transplant recipients evaluated both graft loss and patient death, investigators found that 9% of patients died after transfer, and 21% lost their graft (Prestidge et al., 2012). Combining the poor outcomes, the authors reported a 24% increase in poor outcomes after the transfer of care within a two-year time period.
In this current study, most individuals lost their graft about two years (mean 20.1, range 3 to 36 months) after transfer of care. However, the number of individuals who lost their graft after transfer of care increased by year, with the highest number of individuals losing their graft in the third year after transfer (16 in the first year, 22 in the second year, and 23 in the third year). Harden et al. (2012) evaluated outcomes of 21 kidney transplant recipients who had transferred care and found a substantially higher rate of graft loss (67%), with a slightly longer median time from transfer to graft loss at 40 months (range 1 to 62 months). In another study conducted with 149 transplant recipients who transferred care at 18 years of age, researchers reported that the highest risk of graft failure was within the first year after transfer (Samuel et al., 2011). Prestidge et al. (2012) found eight of 45 patients (17.8%) lost their graft within two years of transfer of care. Combined, these results may indicate that the first three years after transfer is a crucial time for providing increased support for those at-risk for poor outcomes after transfer of care.
Conclusions and Nursing Implications
A 2008 consensus conference report focusing on transition of care for adolescent and young adult solid organ transplant recipients recommended six potential areas of prospective research (Bell et al., 2008). One recommendation was to determine which specific transition elements had the greatest impact on adolescent and young adult outcomes. This descriptive study reports on the incidence of three predictors (medication nonadherence, acute rejection, change in kidney function) for a poor outcome (graft loss) after transfer of care in the pediatric kidney transplant population, specifically adolescents and young adults ages 16 to 25 years. With a supplemental review of the literature, a preliminary clinical profile was developed to identify those most medically at-risk for poor outcomes after transfer of care. Development of a clinical profile of predictors of graft loss for medically at-risk adolescents with a renal transplant is imperative for busy providers (Hollen et al, 2013; Hollen, Hobbie, & Finley, 1999; O'Laughlen et al, 2015).
Given the difficulty and complexity of the issues facing youth as they transfer care to adult providers, there is also a need for a dedicated healthcare professional to help guide the transition process. The Society of Adolescent Medicine, the American Academy of Pediatrics (AAP), the American Academy of Family Physicians (AAFP), and the American Society of Internal Medicine released clear consensus statements on the need for better healthcare transitions for youths with special health care needs AAP, AAFP, American College of Physicians [ACP]-American Society of Internal Medicine [ASIM], 2002; Rosen, Blum, Britto, Sawyer, & Siegel, for the Society for Adolescent Medicine, 2003). These statements called for an identified healthcare professional in each practice to assume responsibility for the transition process for these youths. A consensus conference report specifically evaluating the transition needs of individuals with a solid organ transplant echoed the need for a dedicated healthcare provider to serve as a transition coordinator and healthcare planner for transplant recipients (Bell et al, 2008). Repeatedly, in the transition literature, adolescents with special healthcare needs identify nurses as the ideal persons to oversee the transition process.
In summary, based on the recommendations of these five authoritative bodies, a dedicated healthcare professional who serves as a transition coordinator is needed. Moreover, a clinical profile developed specifically for these medically at-risk adolescents and young adult renal transplant recipients is needed for monitoring by nephrology nurses and nurse practitioners. Three predictors for graft loss are supported in the literature and this secondary data analysis from a national database form an acceptable initial clinical profile for use.
Further research to enhance this evidence-based clinical profile is needed as more predictors that prevent loss to follow-up in these medically at-risk renal transplant recipients are identified and supported with evidence.
Bethany Coyne, PhD, RN, CPNP, is an Assistant Professor, University of Virginia Health System, Department of Pediatrics, and University of Virginia, School of Nursing, Charlottesville, VA.
Patricia J. Hollen, PhD, RN, FAAN, is a Full Professor, University of Virginia Health System, School of Nursing, and Department of Pediatrics, University of Virginia, Charlottesville, VA.
Guofen Yan, PhD, is an Associate Professor of Biostatistics, University of Virginia, Schools of Medicine and Nursing, Department of Public Health Sciences, Charlottesville, VA
John Barcia, MD, is an Associate Professor, Department of Pediatrics, University of Virginia Health System, Charlottesville, VA.
Kenneth Brayman, MD, PhD, is a Professor of Surgery, Department of Surgery, University of Virginia Health System, Charlottesville, VA.
Sponsor: This work was supported by the National Institute of Health, National Research Service Award Individual Fellowship (NRSA Grants : F31NR011237-02). The contents are solely the responsibility of the author (s) and do not necessarily represent the view of the National Institute of Health.
Data Disclaimer: The data here have been supplied by the Minneapolis Medical Research Foundation (MMRF) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy of or interpretation by the SRTR or the U.S. Government.
Statement of Disclosure: The authors reported no actual or potential conflict of interest in relation to this continuing nursing education activity.
Note: The Learning Outcome, additional statements of disclosure, and instructions for CNE evaluation can be found on page 130.
Achille, M.A., Ouellette, A, Fournier, S., Vachon, M., & Hebert, M.J. (2006). Impact of stress, distress and feelings of indebtedness on adherence to immunosuppressants following kidney transplantation. Clinical Transplantation, 20(3), 301-306.
American Academy of Pediatrics (AAP), American Academy of Family Physicians (AAFP), American College of Physicians (ACP)-American Society of Internal Medicine (ASIM). (2002). A consensus statement on health care transitions for young adults with special health care needs. Pediatrics, 110(6, Pt. 2), 1304-1306.
Annunziato, R.A., Emre, S., Shneider, B., Barton, C., Dugan, C.A., & Shemesh, E. (2007). Adherence and medical outcomes in pediatric liver transplant recipients who transition to adult services. Pediatric Transplantation, 11(6), 608-614.
Bell, L.E., Bartosh, S.M., Davis, C.L., Dobbels, F., Al-Uzri, A., Lotstein, D., ... Dharnidharka, V.R. (2008). Adolescent transition to adult care in solid organ transplantation: A consensus conference report. American Journal of Transplantation, 8(11), 2230-2242.
Butkus, D.E., Dottes, A.L., Meydrech, E.F., & Barber, W.H. (2001). Effect of poverty and other socioeconomic variables on renal allograft survival. Transplantation, 72(2), 261-266.
Butler, J.A., Roderick, P., Mullee, M., Mason, J.C., & Peveler, R.C. (2004). Frequency and impact of nonadherence to immunosuppressants after renal transplantation: A systematic review. Transplantation, 77(5), 769-776.
Casey, B.J., Jones, R.M., & Hare, T.A. (2008). The adolescent brain. Annals of the New York Academy of Sciences, 1124, 111-126. doi:10.1196/annals. 1440.010
Chaturvedi, S., Jones, C.L., Walker, R.G., & Sawyer, S.M. (2009). The transition of kidney transplant recipients: A work in progress. Pediatric Nephrology, 24(5), 1055-1060.
Chisholm, M.A. (2002). Enhancing transplant patients' adherence to medication therapy. Clinical Transplantation, 76(1), 30-38.
Connelly, J., Pilch, N., Oliver, M., Jordan, C., Fleming, J., Meadows, H., ... Taber, D. (2015). Prediction of medication nonadherence and associated outcomes in pediatric kidney transplant recipients. Pediatric Transplantation, 19(5), 555-562. doi:10. 1111/petr. 12479
Coyne, B., Hollen, P.J., Yan, G. & Brayman, K. (2016). Risk factors for graft loss in pediatric renal transplant recipients after transfer of care. Progress in Transplantation, 26(4), 356-364. doi: 10.1177/1526924816667952.
Feinstein, S., Keich, R., Becker-Cohen, R., Rinat, C., Schwartz, S.B., & Frishberg, Y. (2005). Is noncompliance among adolescent renal transplant recipients inevitable?. Pediatrics, 775(4), 969-973.
Feldman, H.I., Burns, J.E., Roth, D.A., Berlin, J.A., Szczech, L., Gayner, R., ... Grossman, R.A. (1998). Race and delayed kidney allograft function. Nephrology Dialysis Transplantation, 13(3), 704-710.
Feldman, H.I., Gayner, R., Berlin, J.A., Roth, D.A., Silibovsky, R., Kushner, S., ... Grossman, R.A. (1996). Delayed function reduces renal allograft survival independent of acute rejection. Nephrology Dialysis Transplantation, 11(7), 1306-1313.
Fernandez-Fresnedo, G., Rodrigo, E., de Francisco, A.L., Escallada, R., Ruiz, J.C., Cotorruelo, J.C., ... Arias, M. (2005). Change in serum creatinine levels between 6 and 12 months and kidney graft survival: Influence of proteinuria. Transplantation Proceedings, 37(3), 1433-1434.
Fleiner, F., Fritsche, L., Glander, P., Neumayer, H.H., & Budde, K. (2006). Reporting of rejection after renal transplantation in large immunosuppressive trials: Biopsyproven, clinical, presumed, or treated rejection? Transplantation, 81(5), 655-659.
Giedd, J.N., Blumenthal, J., Jeffries, N.O., Castellanos, F.X., Liu, H., Zijdenbos, A., ... Rapoport, J.L. (1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2(10), 861-863.
Harden, P.N., Walsh, G., Bandler, N., Bradley, S., Lonsdale, D., Taylor, J., & Marks, S.D. (2012). Bridging the gap: An integrated paediatric to adult clinical service for young adults with kidney failure. BMJ, 344, e3718. doi:10. 1136/bmj.e3718
Hariharan, S., McBride, M.A., Cherikh, W.S., Tolleris, C.B., Bresnahan, B.A., & Johnson, C.P. (2002). Post-transplant renal function in the first year predicts long-term kidney transplant survival. Kidney International, 62(1), 311-318.
Helal, I., Abderrahim, E., Ben Hamida, E, Ounissi, M., Essine, S., Hedri, H., ... Kheder, A. (2009). The first year renal function as a predictor of long-term graft survival after kidney transplantation. Transplantation Proceedings, 41(2), 648-650.
Hollen, P.J. (2000). A clinical profile to predict decision making, risk behaviors, clinical status, and health-related quality of life for cancer-surviving adolescents: Part 2. Cancer Nursing, 23(5), 337-343.
Hollen, P.J., Hobbie, W.L., & Finley, S.M. (1999). Testing the effects of a decisionmaking and risk-reduction program for cancer-surviving adolescents. Oncology Nursing Forum, 26(9), 1475-1486.
Hollen, P.J., Tyc, V.L., Shannon, S.V., Donnangelo, S.F., Hobbie, W.L., Hudson, M.M., ... Petroni, G.R. (2013). Factors related to decision making and substance use in adolescent survivors of childhood cancer: A presenting clinical profile. Journal of Cancer Survivorship, 7(3), 500-510. doi: 10.1007/ s11764-013-0287-5
Hsu, D.T. (2005). Biological and psychological differences in the child and adolescent transplant recipient. Pediatric Transplantation, 5(3), 416-421.
Institute of Medicine (IOM) & National Research Council Committee on the Science of Adolescence. (2011). The science of adolescent risk-taking: Workshop report. Washington DC: The National Academies Press, doi: 10.17226/12961
Johnson, S.B., Blum, R.W., & Giedd, J.N. (2009). Adolescent maturity and the brain: The promise and pitfalls of neuroscience research in adolescent health policy. Journal of Adolescent Health, 45(3), 216-221.
Johnson, S.R., Cherikh, W.S., Kauffman, H.M, Pavlakis, M, & Hanto, D.W. (2006). Retransplantation after post-transplant lymphoproliferative disorders: An OPTN/UNOS database analysis. American Journal of Transplantation, 6(11), 2743-2749.
Keith, D.S., Cantarovich, M., Paraskevas, S., & Tchervenkov, J. (2006). Recipient age and risk of chronic allograft nephropathy in primary deceased donor kidney transplant. Transplant International, 73(8), 649-656.
Koshy, S.M., Hebert, D., Lam, K., Stukel, T.A., & Guttmann, A. (2009). Renal allograft loss during transition to adult healthcare services among pediatric renal transplant patients. Transplantation, 57(11), 1733-1736. doi:10.1097/TP. 0b013e3181a63ed9
Luna, B., Thulborn, K.R., Munoz, D.P., Merriam, E.P., Carver, K.E, Minshew, N.J., ... Sweeney, J.A. (2001). Maturation of widely distributed brain function subserves cognitive development. Neurolmage, 13(5), 786-793.
Matas, A.J. (2000). Impact of acute rejection on development of chronic rejection in pediatric renal transplant recipients. Pediatric Transplantation, 4(2), 92-99.
Meier-Kriesche, H.U., Schold J.D., Srinivas, T.R., & Kaplan, B. (2004). Lack of improvement in renal allograft survival despite a marked decrease in acute rejection rates over the most recent era. American Journal of Transplantation, 4(3), 378-383
North American Pediatric Renal Trials and Collaborative Studies (NAPRTCS). (2008). 2008 annual report. Rockville, MD: EMMES Corportaion.
O'Laughlen, M.C., Hollen, P.J., Rance, K., Rovnyak, V., Hinton, I., Hellems, M.A., & Radecki, L. (2015). A health-related quality of life measure for older adolescents with asthma: Child Health Survey for Asthma-T (teen version). Journal of Pediatric Health Care, 29(5), 402-412. doi: 10.1016/j.pedhc.2015.01. 003
Organ Procurement and Transplantation Network (OPTN). (2016). National data. Retrieved from https://optn.trans plant.hrsa.gov/data/view-datareports/ national-data/#
Pabst, S., Bertram, A., Zimmermann, T., Schiffer, M., & de Zwaan, M. (2015). Physician reported adherence to immunosuppressants in renal transplant patients: Prevalence, agreement, and correlates. Journal of Psychosomatic Research, 79(5), 364-371. doi: 10.1016/ j.jpsychores.2015.09.001
Parada, B., Figueiredo, A., Nunes, P., Moreira, P., Rolo, F., & Mota, A. (2006). PD-09.08: Graft loss during the first year after renal transplantation. Urology, 68(Suppl.1), 33.
Pote, L.A., Trofe, J., Wade, E.H., Baluarte, J., Doyle, A., Coral, S., ... Bloom, R.D. (2008). High rate of graft loss in pediatric kidney recipients who transition to an adult transplant program; roles of nonadherence and late referral. [Abstract], Retrieved from https:// www.researchgate.net/publication/ 295197549_High_rate_of_graft_loss_ in_pediatric_kidney_recipients_who_ transition_to_an_adult_transplant_ program_Roles_of_nonadherence_ and_late_referral
Prestidge, C., Romann, A., Djurdjev, O., & Matsuda-Abedini, M. (2012). Utility and cost of a renal transplant transition clinic. Pediatric Nephrology, 27(2), 295-302.
Remorino, R., & Taylor, J. (2006). Smoothing things over: The transition from pediatric to adult care for kidney transplant recipients. Progress in Transplantation, 16(4), 303-308.
Rosen, D.S., Blum, R.W., Britto, M., Sawyer, S.M., & Siegel, D.M.; for the Society for Adolescent Medicine (2003). Transition to adult health care for adolescents and young adults with chronic conditions: Position paper of the society for adolescent medicine. Journal of Adolescent Health, 33(4), 309-311.
Samuel, S.M., Nettel-Aguirre, A., Hemmelgarn, B.R., Tonelli, M.A., Soo, A., Clark, C., & Alexander, R.T.; for the Pediatric Renal Outcomes Canada Group. (2011). Graft failure and adaptation period to adult healthcare centers in pediatric renal transplant patients. Transplantation, 37(12), 1380-1385. doi:10.1097/TP.0b013e3 1821b2f4b
Scientific Registry of Transplant Recipients (SRTR). (2017). Data that describe development. Retrieved from https://www. srtr.org/ about-the-data/the-srtr-data base/
Shemesh, E., Shneider, B.L., Savitzky, J.K., Amott, L., Gondolesi, G.E., Krieger, N.R., ... Emre, S. (2004). Medication adherence in pediatric and adolescent liver transplant recipients. Pediatrics, 113(4), 825-832.
Tejani, A., Ho, P.L., Emmett, L., Stablein, D.M.; for the North American Pediatric Renal Transplant Cooperative Study (NAPRTCS). (2002). Reduction in acute rejections decreases chronic rejection graft failure in children: A report of the North American Pediatric Renal Transplant Cooperative Study (NAPRTCS). American Journal of Transplantation, 2(2), 142-147.
Tercyak, K.P., Britto, M.T., Hanna, K.M., Hollen, P.J., & Hudson, M.M. (2008). Prevention of tobacco use among medically at-risk children and adolescents: Clinical and research opportunities in the interest of public health. Journal of Pediatric Psychology, 33(2), 119-132. doi: 10.1093/jpepsy/jsm132
van den Heuvel, M.E., van der Lee, J.H., Cornelissen, E.A., Bemelman, F.J., Hoitsma, A., Geskus, R.B., ... Groothoff, J.W. (2010). Transition to the adult nephrologist does not induce acute renal transplant rejection. Nephrology Dialysis Transplantation, 25(5), 1662-1667.
Viner, R. (1999). Transition from paediatric to adult care, bridging the gaps or passing the buck? Archives of Disease in Childhood, 81(3), 271-275.
Warady, B.A., Mudge, C., Wiser, B., Wiser, M., & Rader, B. (1996). Transplant allograft loss in the adolescent patient. Advances in Renal Replacement Therapy, 3(2), 154-165.
Watson, A.R. (2000). Non-compliance and transfer from paediatric to adult transplant unit. Pediatric Nephrology, 74(6), 469-472.
Watson, A.R. (2005). Problems and pitfalls of transition from paediatric to adult renal care. Pediatric Nephrology, 20(2), 113-117.
Wolff, G., Strecker, K., Vester, U., Latta, K., & Ehrich, J.H. (1998). Non-compliance following renal transplantation in children and adolescents. Pediatric Nephrology, 72(9), 703-708.
Caption: Figure 1 CONSORT Diagram
Table 1 Patient Characteristics at the Time of Transfer of Care Characteristic n (%) (n = 250) Age at transfer (years) M (SD) 19.5 (2.0) Age at transplant (years) M (SD) 15.1 (3.4) Time since transplant (years) M (SD) 4.4 (3.2) Serum creatinine at transfer (a) M (SD) 1.6 (0.6) Medication nonadherence at transfer n (%) Yes 12 (5%) No 176 (70%) Missing 62 (25%) Acute rejection at transfer n (%) Yes 11 (4%) No 133 (53%) Missing 106 (42%) Sex n (%) Male 148 (59%) Female 102 (41%) Race/ethnicity (b) n (%) White 151 (60%) Hispanic/Latino 43 (17%) Black/African American 43 (17%) Other 13 (6%) Donor type n (%) Deceased donor 108 (43%) Living donor 142 (57%) Cause of renal failure n (%) Glomerulonephritis 92 (37%) Congenital anomaly 79 (32%) Other/missing 76 (30%) (a) Serum creatinine values from 1 and 2 years prior to transfer were averaged for use as creatinine at the time of transfer. (b) Race/dthnicity categories are presented as they are listed in the SRTR dataset. Source: Coyne, Hollen, Yan, & Brayman, 2016. Used with permission. Table 2 Frequency and Percent of Predictors by Year Post-Transfer 1 Year Predictors At Transfer (a) Post-Transfer Medication n (%) nonadherence Yes 12 (5.0%) 14 (5.6%) No 176 (70.0%) 94 (37.6%) Unknown/missing 62 (25.0%) 142 (56.8%) Acute rejection n (%) Yes 11 (4.0%) 11 (4.4%) No 133 (53.0%) 108 (43.2%) Unknown/missing 106 (42.0%) 131 (52.4%) Serum creatinine (a,b) M (SD) 1.7 ([+ or -] 0.7) 1.9 ([+ or -] 1.3) Change by year M (SD) 0.26 ([+ or -] 1.0) Change from transfer M (SD) 0 (0%) % change by year M (SD) 16.3 ([+ or -] 48.0) % change from transfer M (SD) 0 (0%) Missing n (%) 100 (0%) 126 (50.4%) Graft loss n (%) Yes 16 (6.4%) No 234 (93.6%) 2 Years 3 Years Predictors Post-Transfer Post-Transfer Medication nonadherence Yes 21 (8.4%) 29 (11.6%) No 82 (32.8%) 64 (25.6%) Unknown/missing 147 (58.8%) 157 (62.8%) Acute rejection Yes 21 (8.4%) 27 (10.8%) No 103 (41.2%) 66 (26.4%) Unknown/missing 126 (50.4%) 157 (62.8%) Serum creatinine (a,b) 1.8 ([+ or -] 1.0) 1.9 ([+ or -] 1.4) Change by year 0.25 ([+ or -] 0.9) 0.19 ([+ or -] 0.9) Change from transfer 0.27 ([+ or -] 0.9) 0.35 ([+ or -] 1.1) % change by year 15.0 ([+ or -] 44.1) 12.8 ([+ or -] 63.5) % change from transfer 19.3 ([+ or -] 51.3) 27.8 ([+ or -] 95.6) Missing 69 (28.0%) 137 (55.0%) Graft loss Yes 38 (15.2%) 61 (24.4%) No 212 (84.8%) 189 (75.6%) (a) Serum creatinine values were averaged from 2 years prior to transfer and used as serum creatinine at transfer. (b) In mg/dl. Table 3 Studies Reporting Outcomes after Transfer of Care Citation Concept Measured Measurement of Concept Annunziata et Nonadherence Standard deviation al., 2007 (a) of tacrolimus levels Acute rejection Biopsy confirmed acute rejection episodes Graft loss Re-transplantation Patient death Reported patient death Chaturvedi, Jones, Acute rejection Biopsy confirmed Walker, & Sawyer, acute rejection 2009 Kidney function Change in serum creatinine Hospitalizations Number of inpatient days Graft loss Return to dialysis Lost to follow-up Clinic attendance rates Koshy, Hebert, Acute rejection Biopsy confirmed Lam, Stukel, & acute rejection Guttmann, 2009 Hospitalizations Hospitalizations for rejection or biopsy Graft loss Death, or return to dialysis, or re-transplantation Pote et al., 2008 Nonadherence Provider report of nonadherence Graft loss Graft loss Prestidge, Romann, Kidney function Change in serum Djurdjev, & creatinine Matsuda-Abedini, 2012 Graft loss Return to dialysis or re-transplantation Patient death Patient reported death Remorino & Taylor, Nonadherence Subjective 2006 assessment by provider Kidney function Change in serum creatinine Acute rejection Number of acute rejections Hospitalizations Number of inpatient days Lost to follow-up Missed clinic appointments Samuel et al., 2011 Graft failure Graft loss van den Heuvel Acute rejection Number of biopsy et al., 2010 confirmed acute rejection episodes Kidney function Change in serum creatinine Graft loss Return to dialysis Patient death Report patient death Watson, 2000 Nonadherence Cyclosporine levels less than 25 ng/mL Kidney function Patient report Graft loss Change in serum creatinine Death, or return to dialysis, or re-transplantation (a) Liver transplant recipients. Table 4 Recommended Clinical Profile for Monitoring Adolescent/Young Adult Renal Transplant Recipients During the First Three Years after Transfer of Care 1. Self-report of nonadherence and related behaviors (medication adherence, any substance abuse, and impact of peer pressure). 2. Objective medication nonadherent behavior monitoring (using tacrolimus levels). 3. Number of episodes of acute rejection. 4. Serum creatinine as a proxy for kidney function (change in greater than 0.3 mg/dL over six months). 5. Monitoring for missed clinic appointments and/or laboratory studies. 6. Number and type of hospitalizations.
|Printer friendly Cite/link Email Feedback|
|Author:||Coyne, Bethany; Hollen, Patricia J.; Yan, Guofen; Barcia, John; Brayman, Kenneth|
|Publication:||Nephrology Nursing Journal|
|Date:||Mar 1, 2017|
|Previous Article:||Caring for ourselves.|
|Next Article:||Preventing intradialytic hypotension: translating evidence into practice.|