First-Year Waitlist Hospitalization and Subsequent Waitlist and Transplant Outcome

Predicting wait time for pediatric kidney transplant: a novel index

BACKGROUND

Over one thousand pediatric kidney transplant candidates are added to the waitlist annually, yet the prospective time spent waiting is unknown for many. Our study fills this gap by identifying variables that impact waitlist time and by creating an index to predict the likelihood of a pediatric candidate receiving a transplant within 1 year of listing. This index could be used to guide patient management by giving clinicians a potential timeline for each candidate's listing based on a unique combination of risk factors.

METHODS

A retrospective analysis of 3757 pediatric kidney transplant candidates from the 2014 to 2020 OPTN/UNOS database was performed. The data was randomly divided into a training set, comprising two-thirds of the data, and a testing set, comprising one-third of the data. From the training set, univariable and multivariable logistic regressions were used to identify significant predictive factors affecting wait times. A predictive index was created using variables significant in the multivariable analysis. The index's ability to predict likelihood of transplantation within 1 year of listing was validated using ROC analysis on the training set. Validation of the index using ROC analysis was repeated on the testing set.

RESULTS

A total of 10 variables were found to be significant. The five most significant variables include the following: blood group, B (OR 0.65); dialysis status (OR 3.67); kidney disease etiology, SLE (OR 0.38); and OPTN region, 5 (OR 0.54) and 6 (OR 0.46). ROC analysis of the index on the training set yielded a c-statistic of 0.71. ROC analysis of the index on the testing set yielded a c-statistic of 0.68.

CONCLUSIONS

This index is a modest prognostic model to assess time to pediatric kidney transplantation. It is intended as a supplementary tool to guide patient management by providing clinicians with an individualized prospective timeline for each candidate. Early identification of candidates with potential for prolonged waiting times may help encourage more living donation including paired donation chains.

Unmet Questions About Frailty in Kidney Transplant Candidates

Frailty occurs frequently among patients with advanced chronic kidney disease, especially among women. Assessing frailty in kidney transplant (KT) candidates is crucial for informing them about associated risks. However, there is poor agreement between frailty scales and research on their correlation with transplant outcomes. Being prefrail significantly impacts both graft and patient survival, often beginning with just 1 Fried criterion. Rather than viewing frailty as a categorical state, it should be regarded as a spectrum ranging from 1 to 5 criteria, with the risk of adverse outcomes escalating as frailty worsens. Frailty status fluctuates during the waiting period for KT; hence, a 1-time frailty evaluation is insufficient to determine risks and implement strategies for improving functional status. Further research should investigate the components of frailty that most frequently change during this waiting period and establish strategies to prevent or reverse frailty. Although careful evaluation of frail KT candidates is necessary to prevent early complications and mortality, exclusion based solely on a frailty score is unwarranted. Instead, efforts should focus on timely interventions to enhance their condition before transplantation. Although evidence is limited, exercise programs appear feasible and yield positive results. A pretransplant clinical framework encompassing multimodal prehabilitation-comprising physical therapy, nutritional measures, and psychological support-during the waiting list period may help alleviate the effects of frailty and poor fitness after KT, ultimately improving key outcomes. Despite logistical challenges, there is a pressing need for interventional trials in this area.

Old Age and Frailty in Deceased Organ Transplantation and Allocation-A Plea for Geriatric Assessment and Prehabilitation

Due to demographic ageing and medical progress, the number and proportion of older organ donors and recipients is increasing. At the same time, the medical and ethical significance of ageing and old age for organ transplantation needs clarification. Advanced age is associated with the frailty syndrome that has a negative impact on the success of organ transplantation. However, there is emerging evidence that frailty can be modified by suitable prehabilitation measures. Against this backdrop, we argue that decision making about access to the transplant waiting list and the allocation of donor organs should integrate geriatric expertise in order to assess and manage frailty and impairments in functional capacity. Prehabilitation should be implemented as a new strategy for pre-operative conditioning of older risk patients' functional capacity. From an ethical point of view, advanced chronological age per se should not preclude the indication for organ transplantation and the allocation of donor organs.

Predicting Kidney Transplant Recipient Cohorts' 30-Day Rehospitalization Using Clinical Notes and Electronic Health Care Record Data

Introduction

Rehospitalization after kidney transplant is costly to patients and health care systems and is associated with poor outcomes. Few prediction model studies have examined whether inclusion of clinical notes data from the electronic medical record (EMR) enhances prediction of rehospitalization.

Methods

In a retrospective, observational study of first-time, adult kidney transplant recipients at a large, urban hospital in southeastern United States (2005-2015), we examined 30-day rehospitalization (30DR) using structured EMR and unstructured (i.e., clinical notes) data. We used natural language processing (NLP) methods on 8 types of clinical notes and included terms in predictive models using unsupervised machine learning approaches. Both the area under the receiver operating curve and precision-recall curve (ROC and PRC, respectively) were used to determine and compare model accuracy, and 5-fold cross-validation tested model performance.

Results

Among 2060 kidney transplant recipients, 30.7% were readmitted within 30 days. Predictive models using clinical notes did not meaningfully improve performance over previous models using structured data alone (ROC 0.6821; 95% confidence interval [CI]: 0.6644, 0.6998). Predictive models built using solely clinical notes performed worse than models using both clinical notes and structured data. The data that contributed to the top performing models were not identical but both included structured data and progress notes (ROC 0.6902; 95% CI: 0.6699, 0.7105).

Conclusions

Including new features from clinical notes in risk prediction models did not substantially increase predictive accuracy for 30DR for kidney transplant recipients. Future research should consider pooling data from multiple institutions to increase sample size and avoid overfitting models.

Outcomes of Frail Patients While Waiting for Kidney Transplantation: Differences between Physical Frailty Phenotype and FRAIL Scale

Frailty is associated with poorer outcomes among patients waiting for kidney transplantation (KT). Several different tools to measure frailty have been used; however, their predictive value is unknown. This is a prospective longitudinal study of 449 KT candidates evaluated for frailty by the Physical Frailty Phenotype (PFP) and the FRAIL scale. During the study period, 296 patients received a KT, while 153 remained listed. Patients who did not get receive a transplant were more frequently frail according to PFP (16.3 vs. 7.4%, p = 0.013). Robust patients had fewer hospital admissions during the 1st year after listing (20.8% if PFP = 0 vs. 43.4% if ≥1, and 27.1% if FRAIL = 0 vs. 48.9% if ≥1) and fewer cardiovascular events (than FRAIL ≥ 1) or major infectious events (than PFP ≥ 1). According to PFP, scoring 1 point had an impact on patient survival and chance of transplantation in the univariate analysis. The multivariable analysis corroborated the result, as candidates with PFP ≥ 3 had less likelihood of transplantation (HR 0.45 [0.26–0.77]). The FRAIL scale did not associate with any of these outcomes. In KT candidates, pre-frailty and frailty according to both the PFP and the FRAIL scale were associated with poorer results while listed. The PFP detected that frail patients were less likely to receive a KT, while the FRAIL scale did not.

Frailty among chronic kidney disease patients on the kidney transplant waiting list: the sex–frailty paradox

Background

Frailty is defined as decreased physiologic reserve and resistance to stressors that predisposes patients towards poor health results. Its prevalence in chronic kidney disease (CKD) patients who are kidney transplant (KT) candidates is high. Frailty is associated with a higher rate of complications and mortality after transplant. It is unknown whether frailty phenotype differs depending on sex in this population.

Methods

This was a prospective longitudinal study of 455 KT candidates evaluated for frailty by physical frailty phenotype at the time of inclusion on the KT waiting list. Pre-frailty was defined as the presence of two criteria and frailty as three or more criteria. Univariate and multivariate analyses searched for associations of frailty status, frailty components and gender differences.

Results

Thirty percent of the total cohort resulted to be pre-frail (20%) or frail (10.3%), but disparities were observed between sexes, with 22.5% of men and 47.2% of women falling into one of these categories. Among frailty criteria, women presented with a higher percentage of exhaustion (39.6% versus 17%) and slowness (22.2% versus 9.6%) compared with men. Comorbidity burden was higher among frail men, whereas social factors were poorer between frail women. Disability was common among those patients who were frail, both men and women.

Conclusions

Frailty is twice as frequent in advanced CKD women as men. Frailty criteria distribution and phenotype seem to differ among sexes, which might have implications in terms of specific and individualized interventions to improve their status before transplantation.

A retrospective case-control study exploring pre-transplant predictors for loss of kidney transplant function or death among Indigenous kidney transplant recipients

A retrospective case-control study was conducted, to identify risk factors for loss of kidney transplant function or death among the Indigenous kidney transplant recipients, beyond the information available from Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry.

METHODS

Cases were defined as all Australian Indigenous kidney transplant recipients from 1st January 2005 to 31 December 2015 from the major hospitals in the Northern Territory (NT) and South Australia (SA) who experienced graft loss (including patient death) up to two-years post-transplant. Controls (matched 4:1) were defined as all Indigenous kidney transplant recipients during the same period with functioning transplants at two-years post-transplant operation. Matching was done on gender and diabetes status. Regression analysis adjusted for age was used for comparing cases and controls.

RESULTS

There were 17 cases and 68 matched controls. Among cases, the odds ratio for more than one hospital admission episode (compared to ≤1 episode) in the two years pre-transplant period was 6.2 (95% CI, 1.2-32.5). However, there were no significant differences in the frequency of comorbidities at renal replacement therapy start, cardiovascular intervention pre-transplant, pre-transplant infection screening, age and gender of the donors, frequency of admission episodes where an infection was documented, the total length of inpatient stay or admission to intensive care unit during pre-transplant hospital admission between cases and controls.

CONCLUSION

Early graft loss was associated with a higher frequency of hospital admissions in the two-years pre-transplant period. In contrast, other measured factors in the pre-transplant period did not predict these adverse outcomes. This article is protected by copyright. All rights reserved.

Frailty in Pancreas Transplantation

There are a variety of definitions and criteria used in clinical practice to define frailty. In the absence of a gold-standard definition, frailty has been operationally defined as meeting 3 out of 5 phenotypic criteria indicating compromised function: low grip strength, low energy, slowed walking speed, low physical activity, and unintentional weight loss. Frailty is a common problem in solid organ transplant candidates who are in the process of being listed for a transplant, as well as after transplantation. Patients with diabetes or chronic kidney disease (CKD) are known to be at increased risk of being frail. As pancreas transplantation is exclusively performed among patients with diabetes and the majority of them also have CKD, pancreas transplant candidates and recipients are at high risk of being frail. Sarcopenia, fatigue, low walking speed, low physical activity, and unintentional weight loss, which are some of the phenotypes of frailty, are very prevalent in this population. In various solid organs, frail patients are less likely to be listed or transplanted and have high waitlist mortality. Even after a transplant, they have increased risk of prolonged hospitalization, readmission, and delayed graft function. Given the negative impact of frailty on solid organ transplants, we believe that frailty would have a similar or even worse impact on pancreas transplantation. Due to the paucity of data specifically among pancreas transplant recipients, here we include frailty data from patients with CKD, diabetes, and various solid organ transplant recipients.

Incidence and Causes of Late Hospital Readmissions After Living Donor Renal Transplant: A Retrospective Study

OBJECTIVES

Our primary aim was to find the incidence, causes, and factors responsible for late hospital readmissions.

MATERIALS AND METHODS

There were 185 patients included in the study. The patients were divided into 2 groups: those with late readmission after discharge and those with no late readmission. Inpatient records and charts were assessed for the medical status of the patients, cause of chronic kidney disease, comorbidities, vintage and modality of dialysis, and hospital admissions 3 months before transplant. Collected patient data included recipient age, sex, height, weight, body mass index, hepatitis C status, donor age, methods of immunosuppression and induction, duration of hospital stay, postoperative complications and secondary procedures, number, duration, and causes of hospital readmission after transplant, and methods of evaluation and management during readmission.

RESULTS

There were 80 patients who received 127 late hospital readmissions. The most common cause of late hospital readmission was infection, which led to 45 admissions (35.43%). Of 45 admissions for infections, 18 were caused by urinary tract infections. Other reasons for admission were pneumonia (10 admissions), cytomegalovirus infection (11 admissions), and tuberculosis (6 admissions). The second most common cause of readmission was infectious or noninfectious diarrhea, which led to 29 admissions (22.88%). There were 28 late hospital readmissions (22.4%) for the evaluation or management of graft dysfunction. Newonset diabetes after transplant and febrile illness were causes of late hospital readmission in 8 cases each (6.9%), with 9 late hospital readmissions (7.08%) the result of other causes.

CONCLUSIONS

Incidence of late hospital readmission is high (43.2%), and the most common cause is infection, particularly urinary tract infections. Age of the recipient and early hospital readmission are predictive factors for late hospital readmission.

An overview of frailty in kidney transplantation: measurement, management and future considerations

The construct of frailty was first developed in gerontology to help identify older adults with increased vulnerability when confronted with a health stressor. This article is a review of studies in which frailty has been applied to pre- and post-kidney transplantation (KT) populations. Although KT is the optimal treatment for end-stage kidney disease (ESKD), KT candidates often must overcome numerous health challenges associated with ESKD before receiving KT. After KT, the impacts of surgery and immunosuppression represent additional health stressors that disproportionately impact individuals with frailty. Frailty metrics could improve the ability to identify KT candidates and recipients at risk for adverse health outcomes and those who could potentially benefit from interventions to improve their frail status. The Physical Frailty Phenotype (PFP) is the most commonly used frailty metric in ESKD research, and KT recipients who are frail at KT (~20% of recipients) are twice as likely to die as nonfrail recipients. In addition to the PFP, many other metrics are currently used to assess pre- and post-KT vulnerability in research and clinical practice, underscoring the need for a disease-specific frailty metric that can be used to monitor KT candidates and recipients. Although frailty is an independent risk factor for post-transplant adverse outcomes, it is not factored into the current transplant program risk-adjustment equations. Future studies are needed to explore pre- and post-KT interventions to improve or prevent frailty.

Kidney After Liver Transplantation Matched-pair Analysis: Are Kidneys Allocated to Appropriate Patients to Maximize Their Survival?

BACKGROUND

Kidney after liver transplantation (KALT) is the best therapeutic option for patients with end-stage renal disease after orthotopic liver transplantation (OLT). New allocation policies prioritize kidneys to patients in renal failure within the first year following OLT. There is little data on how kidney quality, measured by kidney donor profile index (KDPI), impacts KALT survival outcomes.

METHODS

The United Network for Organ Sharing database was queried for adult KALT recipients from 1988 to 2015 and compared to their paired kidney transplant alone (KTA) recipients. Seven hundred forty-five pairs were stratified into 3 KDPI subgroups and compared patient survival, graft survival, and death-censored graft survival among matched-paired recipients.

RESULTS

Overall, KTA recipients had superior patient and graft survival compared with the KALT group. KTA patient survival was superior for all 3 KDPI subgroups analysis. KTA graft survival was superior compared with KALT recipients of KDPI 21%-85% kidneys. Inferior graft half-life was observed in KALT versus KTA recipients with KDPI 21%-85% and >85%.

CONCLUSIONS

From a utilitarian perspective, it is important that kidneys are allocated to recipients that are able to maximize their benefit from the full life of the organ. In KTA recipients, graft quality correlates directly to graft survival. However, in KALT patients receiving the matched-pair kidneys of the KTA recipients, patient mortality, rather than kidney quality, dictates graft survival significantly. As allocation practices continue developing, utilization of expanded criteria kidneys that better match anticipated patient and graft survival should be strongly considered to maximize the benefits of limited resources for the greatest number of patients.

Association of Physical Function and Survival in Older-Adult Renal Transplant Recipients

There is an increase in older-adult renal transplant recipients in United States. The objective of this study was to assess the association between physical function (PF) and patient survival in renal transplant recipients who are aged 65 years or older. Using United Network for Organ Sharing (UNOS) data from 2007 to 2016, renal transplant recipients aged 65 years or older were included. Multivariable Cox regression was used to assess associations between survival and functional status adjusted for age, sex, race, donor quality, diabetes, and dialysis vintage. The study identified 26,721 patients. Patient survival was significantly higher in recipients who needed no assistance and lowest in patients in need of total assistance (P < .0001). In deceased donor (DD) transplants, the relative risk for mortality was 2.06 (1.74-2.43) for total assistance and 1.17 (1.08-1.28) for moderate assistance compared to no assistance (P < .0001). In living donor (LD) transplants, the relative risk of mortality was 1.38 (0.78-2.42) for patients needing total assistance and 1.37 (1.14-1.65) for patients needing moderate assistance compared to patients who did not need assistance (0.003). PF is an independent predictor of post-transplant mortality. Assessment of older potential renal transplant recipients should include assessment and standardization of functional status to counsel about post-transplant survival.

Long-term outcomes among Medicare patients readmitted in the first year of hemodialysis: a retrospective cohort study

Background

Readmission within 30 days of hospital discharge is common and costly among end-stage renal disease (ESRD) patients. Little is known about long-term outcomes after readmission. We estimated the association between hospital admissions and readmissions in the first year of dialysis and outcomes in the second year.

Methods

Data on incident dialysis patients with Medicare coverage were obtained from the United States Renal Data System (USRDS). Readmission patterns were summarized as no admissions in the first year of dialysis (Admit-), at least one admission but no readmissions within 30 days (Admit+/Readmit-), and admissions with at least one readmission within 30 days (Admit+/Readmit+).We used Cox proportional hazards models to estimate the association between readmission pattern and mortality, hospitalization, and kidney transplantation, accounting for demographic and clinical covariates.

Results

Among the 128,593 Medicare ESRD patients included in the study, 18.5% were Admit+/Readmit+, 30.5% were Admit+/Readmit-, and 51.0% were Admit-. Readmit+/Admit+ patients had substantially higher long-term risk of mortality (HR = 3.32 (95% CI, 3.21–3.44)), hospitalization (HR = 4.46 (95% CI, 4.36–4.56)), and lower likelihood of kidney transplantation (HR = 0.52 (95% CI, 0.44–0.62)) compared to Admit- patients; these associations were stronger than those among Admit+/Readmit- patients.

Conclusions

Patients with readmissions in the first year of dialysis were at substantially higher risk of poor outcomes than either patients who had no admissions or patients who had hospital admissions but no readmissions. Identifying strategies to both prevent readmission and mitigate risk among patients who had a readmission may improve outcomes among this substantial, high-risk group of ESRD patients.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1473-0) contains supplementary material, which is available to authorized users.

Assessing Predictors of Early and Late Hospital Readmission After Kidney Transplantation

Supplemental Digital Content is available in the text.

Background.

A better understanding of the risk factors of posttransplant hospital readmission is needed to develop accurate predictive models.

Methods.

We included 40 461 kidney transplant recipients from United States renal data system (USRDS) between 2005 and 2014. We used Prentice, Williams and Peterson Total time model to compare the importance of various risk factors in predicting posttransplant readmission based on the number of the readmissions (first vs subsequent) and a random forest model to compare risk factors based on the timing of readmission (early vs late).

Results.

Twelve thousand nine hundred eighty-five (31.8%) and 25 444 (62.9%) were readmitted within 30 days and 1 year postdischarge, respectively. Fifteen thousand eight hundred (39.0%) had multiple readmissions. Predictive accuracies of our models ranged from 0.61 to 0.63. Transplant factors remained the main predictors for early and late readmission but decreased with time. Although recipients’ demographics and socioeconomic factors only accounted for 2.5% and 11% of the prediction at 30 days, respectively, their contribution to the prediction of later readmission increased to 7% and 14%, respectively. Donor characteristics remained poor predictors at all times. The association between recipient characteristics and posttransplant readmission was consistent between the first and subsequent readmissions. Donor and transplant characteristics presented a stronger association with the first readmission compared with subsequent readmissions.

Conclusions.

These results may inform the development of future predictive models of hospital readmission that could be used to identify kidney transplant recipients at high risk for posttransplant hospitalization and design interventions to prevent readmission.

Implications of Frailty for Peritransplant Outcomes in Kidney Transplant Recipients

Purpose of Review

Research over the past few decades points to the importance of frailty, or the lack of physiologic reserve, in the natural history of chronic diseases and in modifying the impact of potential interventions. End-stage kidney disease (ESKD) and the intervention of kidney transplantation are no exception. We review the recent epidemiologic and cohort-based evidence on the association between frailty and kidney transplant outcomes and provide a framework of questions with which to approach future research endeavors and clinical practice.

Recent Findings

Frailty in kidney transplant candidates can be measured in numerous ways, including descriptive phenotype, description scores, functional testing, and surrogate measures. Regardless of the metric, the presence of frailty is strongly associated with inferior pre- and posttransplant outcomes compared to the absence of frailty. However, some frail patients with ESKD can benefit from transplant over chronic dialysis. Evidence-based approaches for identifying frail ESKD patients who can benefit from transplant over dialysis, with acceptable posttransplant outcomes, are lacking. Interventional trials to improve frailty and physical function before transplant (prehabilitation) and after transplant (rehabilitation) are also lacking.

Conclusion

Frailty is increasingly recognized as highly relevant to peritransplant outcomes, but more work is needed to: 1) tailor management to the unique needs of frail patients, both pre- and posttransplant; 2) define phenotypes of frail patients who are expected to benefit from transplant over dialysis; and 3) develop interventions to reverse frailty, both pre- and post-transplant.

Recent History of Serious Fall Injuries and Posttransplant Outcomes Among US Kidney Transplant Recipients

BACKGROUND

Serious fall injuries are associated with poor outcomes among dialysis patients, but whether these associations hold in patients with a history of serious fall injury before kidney transplantation is unknown.

METHODS

In national administrative data, 22 474 US adults receiving a first kidney transplant in 2011-2014 with at least 1 year of follow-up before transplant were identified. Serious fall injuries in the year before transplant were identified using diagnostic codes for falls and simultaneous fractures, dislocations, or head trauma in inpatient or outpatient claims. We used multivariable Cox proportional hazards models to estimate associations of incident posttransplant outcomes with serious fall injury in the year before transplant.

RESULTS

A total of 620 (2.8%) recipients had serious fall injuries before transplant and were more likely to be white, female, and have more comorbid conditions than those without a fall injury. Although posttransplant recipient survival did not differ by recent serious fall injuries (hazard ratio [HR], 1.03; 95% confidence interval [CI], 0.78-1.36), these injuries were associated with 33% higher rates of graft failure (HR, 1.33; 95% CI, 1.03-1.72). Patients with serious fall injuries spent 12.1% of posttransplant follow-up hospitalized, a 3.3-fold higher rate than those without a fall, and had nearly 2-fold higher rates of skilled nursing facility utilization (HR, 1.98; 95% CI, 1.52-2.57).

CONCLUSIONS

Serious fall injuries are independently associated with significantly greater resource requirements and lower graft survival. Further study is needed to delineate the relationship between falls and adverse outcomes in transplant and reduce the incidence and deleterious effects of these events.

Association of Serious Fall Injuries among United States End Stage Kidney Disease Patients with Access to Kidney Transplantation

BACKGROUND AND OBJECTIVES

Serious fall injuries in the setting of ESKD may be associated with poor access to kidney transplant. We explored the burden of serious fall injuries among patients on dialysis and patients on the deceased donor waitlist and the associations of these fall injuries with waitlisting and transplantation.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Our analytic cohorts for the outcomes of (1) waitlisting and (2) transplantation included United States adults ages 18-80 years old who (1) initiated dialysis (n=183,047) and (2) were waitlisted for the first time (n=37,752) in 2010-2013. Serious fall injuries were determined by diagnostic codes for falls plus injury (fracture, joint dislocation, or head trauma) in inpatient and emergency department claims; the first serious fall injury after cohort entry was included as a time-varying exposure. Follow-up ended at the specified outcome, death, or the last date of follow-up (September 30, 2014). We used multivariable Cox proportional hazards models to determine the independent associations between serious fall injury and waitlisting or transplantation.

RESULTS

Overall, 2-year cumulative incidence of serious fall injury was 6% among patients on incident dialysis; with adjustment, patients who had serious fall injuries were 61% less likely to be waitlisted than patients who did not (hazard ratio, 0.39; 95% confidence interval, 0.35 to 0.44). Among incident waitlisted patients (4% 2-year cumulative incidence), those with serious fall injuries were 29% less likely than their counterparts to be subsequently transplanted (hazard ratio, 0.71; 95% confidence interval, 0.63 to 0.80).

CONCLUSIONS

Serious fall injuries among United States patients on dialysis are associated with substantially lower likelihood of waitlisting for and receipt of a kidney transplant.

Mortality in Elderly Waiting-List Patients Versus Age-Matched Kidney Transplant Recipients: Where is the Risk?

The number of elderly patients on the waiting list (WL) for kidney transplantation (KT) has risen significantly in recent years. Because KT offers a better survival than dialysis therapy, even in the elderly, candidates for KT should be selected carefully, particularly in older waitlisted patients. Identification of risk factors for death in WL patients and prediction of both perioperative risk and long-term post-transplant mortality are crucial for the proper allocation of organs and the clinical management of these patients in order to decrease mortality, both while on the WL and after KT. In this review, we examine the clinical results in studies concerning: a) risk factors for mortality in WL patients and KT recipients; 2) the benefits and risks of performing KT in the elderly, comparing survival between patients on the WL and KT recipients; and 3) clinical tools that should be used to assess the perioperative risk of mortality and predict long-term post-transplant survival. The acknowledgment of these concerns could contribute to better management of high-risk patients and prophylactic interventions to prolong survival in this particular population, provided a higher mortality is assumed.

Hospitalization Among Individuals Waitlisted For Kidney Transplant

BACKGROUND

For patients waitlisted for a deceased-donor kidney, hospitalization is associated with a lower likelihood of transplantation and worse posttransplant outcomes. However, individual-, neighborhood-, and regional-level risk factors for hospitalization throughout the waitlist period and specific causes of hospitalization in this population are unknown.

METHODS

We used United States Renal Data System Medicare-linked data on patients waitlisted between 2005 and 2013 with continuous enrollment in Medicare parts A and B (n = 53 810) to examine the association between annual hospitalization rate and a variety of demographic, clinical, and social factors. We used multilevel multivariable ordinal logistic regression to estimate odds ratios.

RESULTS

Factors associated with significantly increased hospitalization rates among waitlisted individuals included older age, female sex, more years on dialysis before waitlisting, tobacco use, panel-reactive antibody greater than 0, public insurance or no insurance at end-stage renal disease diagnosis, more regional acute care hospital beds, and urban residence (all P < 0.05). Among patients dialysis-dependent when waitlisted, individuals with arteriovenous fistulas were significantly less likely than individuals with indwelling catheters or grafts to be hospitalized (odds ratios, 0.79 and 0.82, respectively, both P < 0.001). The most common causes of hospitalization were complications related to devices, implants, and grafts; hypertension; and sepsis.

CONCLUSIONS

Individual- and regional-level variables were significantly associated with hospitalization while waitlisted, suggesting that personal, health system, and geographic factors may impact patients' risk. Conditions related to dialysis access and comorbidities were common hospitalization causes, underscoring the importance proper access management and care for additional chronic health conditions.