Early hospital readmission after kidney transplantation: patient and center-level associations

Diabetes mellitus and blood glucose variability increases the 30-day readmission rate after kidney transplantation

INTRODUCTION

Inpatient hyperglycemia is an established independent risk factor among several patient cohorts for hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission.

METHODS

Data on first-time solitary kidney transplantations were retrieved between September 2015 and December 2018. Information was linked to the electronic health records to determine diagnosis of diabetes mellitus and extract glucometric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on bootstrapped partitions of the data to ensure statistical significance.

RESULTS

The cohort included 1036 patients who received kidney transplantation; 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average area under the receiver operator curve (AUC) of 78% with (76.1%, 79.9%) 95% confidence interval (CI). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia, the recipient and donor body mass index (BMI) values, presence of delayed graft function, and African American race as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed.

CONCLUSIONS

Suboptimal glucose metrics during hospitalization after kidney transplantation are associated with an increased risk for 30-day hospital readmission. Optimizing hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Outcomes of early hospital readmission after kidney transplantation: Perspectives from a Canadian transplant centre

BACKGROUND

Early hospital readmissions (EHRs) after kidney transplantation range in incidence from 18%-47% and are important and substantial healthcare quality indicators. EHR can adversely impact clinical outcomes such as graft function and patient mortality as well as healthcare costs. EHRs have been extensively studied in American healthcare systems, but these associations have not been explored within a Canadian setting. Due to significant differences in the delivery of healthcare and patient outcomes, results from American studies cannot be readily applicable to Canadian populations. A better understanding of EHR can facilitate improved discharge planning and long-term outpatient management post kidney transplant.

AIM

To explore the burden of EHR on kidney transplant recipients (KTRs) and the Canadian healthcare system in a large transplant centre.

METHODS

This single centre cohort study included 1564 KTRs recruited from January 1, 2009 to December 31, 2017, with a 1-year follow-up. We defined EHR as hospitalizations within 30 d or 90 d of transplant discharge, excluding elective procedures. Multivariable Cox and linear regression models were used to examine EHR, late hospital readmissions (defined as hospitalizations within 31-365 d for 30-d EHR and within 91-365 d for 90-d EHR), and outcomes including graft function and patient mortality.

RESULTS

In this study, 307 (22.4%) and 394 (29.6%) KTRs had 30-d and 90-d EHRs, respectively. Factors such as having previous cases of rejection, being transplanted in more recent years, having a longer duration of dialysis pretransplant, and having an expanded criteria donor were associated with EHR post-transplant. The cumulative probability of death censored graft failure, as well as total graft failure, was higher among the 90-d EHR group as compared to patients with no EHR. While multivariable models found no significant association between EHR and patient mortality, patients with EHR were at an increased risk of late hospital readmissions, poorer kidney function throughout the 1st year post-transplant, and higher hospital-based care costs within the 1st year of follow-up.

CONCLUSION

EHRs are associated with suboptimal outcomes after kidney transplant and increased financial burden on the healthcare system. The results warrant the need for effective strategies to reduce post-transplant EHR.

Effect of Recipient Body Mass Index on Kidney Transplantation Outcomes: A Systematic Review and Meta-analysis by the Transplant Committee from the French Association of Urology

CONTEXT

The impact of recipient obesity on kidney transplantation (KT) outcomes remains unclear.

OBJECTIVE

The aim of this study was to perform a systematic review and meta-analysis to appraise all available evidence on the outcomes of KT in obese patients (body mass index [BMI] ≥30 kg/m2) versus nonobese patients (BMI <30 kg/m2).

EVIDENCE ACQUISITION

A systematic review and meta-analysis was performed. Search was conducted in the MEDLINE OvidSP, Web of Science, Google Scholar, Embase, and Cochrane databases to identify all studies reporting the outcomes of KT in obese versus nonobese recipients.

EVIDENCE SYNTHESIS

Fifty-two articles met the inclusion criteria. Delayed graft function and surgical complications were significantly higher in obese recipients (delayed graft function: relative risk [RR]: 1.44, 95% confidence interval [CI]: 1.32-1.57, p < 0.01; surgical complications: RR: 1.74, 95% CI: 1.36-2.22, p < 0.0001). Five-year patient survival (RR: 0.96, 95% CI: 0.92-1.00, p = 0.01), 10-yr patient survival (RR: 0.90, 95% CI: 0.84-0.97, p = 0.006), and 10-yr graft survival (RR: 0.87, 95% CI: 0.79-0.96, p = 0.01) were significantly inferior in the obese group.

CONCLUSIONS

KT in obese recipients was associated with lower patient and graft survival, and higher delayed graft function, acute rejection, and medical and surgical complications than nonobese recipients. In the current situation of organ shortage and increasing prevalence of obesity, ways to optimize KT in this setting should be investigated.

PATIENT SUMMARY

Compared with nonobese population, kidney transplantation in obese recipients has inferior patient and graft survival, and higher medical and surgical complications.

Racial Disparities in Hospitalization Rates During Long-Term Follow-Up After Deceased-Donor Kidney Transplantation

OBJECTIVE

To compare hospitalization rates between African American (AA) and European American (EA) deceased-donor (DD) kidney transplant (KT) recipients during over a10-year period.

METHOD

Data from the Scientific Registry of Transplant Recipients and social determinants of health (SDoH), measured by the Social Deprivation Index, were used. Hospitalization rates were estimated for kidney recipients from AA and EA DDs who had one kidney transplanted into an AA and one into an EA, leading to four donor/recipient pairs (DRPs): AA/AA, AA/EA, EA/AA, and EA/EA. Poisson-Gamma models were fitted to assess post-transplant hospitalizations.

RESULT

Unadjusted hospitalization rates (95% confidence interval) were higher among all DRP involving AA, 131.1 (122.5, 140.3), 134.8 (126.3, 143.8), and 102.4 (98.9, 106.0) for AA/AA, AA/EA, and EA/AA, respectively, compared to 97.1 (93.7, 100.6) per 1000 post-transplant person-years for EA/EA pairs. Multivariable analysis showed u-shaped relationships across SDoH levels within each DRP, but findings varied depending on recipients' race, i.e., AA recipients in areas with the worst SDoH had higher hospitalization rates. However, EA recipients in areas with the best SDoH had higher hospitalization rates than their counterparts.

CONCLUSIONS

Relationship between healthcare utilization and SDoH depends on DRP, with higher hospitalization rates among AA recipients living in areas with the worst SDoH and among EA recipients in areas with the best SDoH profiles. SDoH plays an important role in driving disparities in hospitalizations after kidney transplantation.

The impact of universal induction therapy on early hospital readmission of kidney transplant recipients

BACKGROUND

Early hospital readmission (EHR) is associated with worse outcomes. The use of anti-thymocyte globulin (rATG) induction therapy is associated with increased efficacy in preventing acute rejection, although safety concerns still exist.

METHODS

This retrospective single-center study compared the incidence, causes of EHR, and one-year clinical outcomes of patients receiving a kidney transplant between August 18, 2011 and December 31, 2012 (old era), in which only high-risk patients received 5 mg/kg rATG, with those transplanted between August 18, 2014 and December 31, 2015 (new era), in which all patients received a single 3 mg/kg dose of rATG.

RESULTS

There were 788 patients from the Old Era and 800 from the New Era. The EHR incidence in the old era patients was 26.4% and in the new era patients, 22.5% (p = 0.071). The main cause of EHR in both eras was infection (67% vs. 68%). The incidence of acute rejection episodes was lower (22.7% vs 3.5%, p < 0.001) and the one-year patient survival was higher (95.6% vs. 98.1%, vs. p = 0.004) in new era patients.

CONCLUSION

The universal use of 3 mg/kg rATG single-dose induction therapy in the new era was associated with a trend towards reduced EHR and a reduction in the incidence of acute rejection and mortality.

Early readmissions post kidney transplantation: lessons learned

INTRODUCTION

Kidney transplantation (KT) is the gold standard treatment for end-stage renal disease (ESRD) patients. Hospital readmissions post-transplant is a common complication and can be considered an indication of avoidable morbidity and hospital quality, and there is a significant correlation between EHR and adverse patient outcomes. This study aimed to assess the readmission rate following kidney transplants, the underlying causes, and possible ways to prevent it.

MATERIAL AND METHODS

We retrospectively reviewed the medical records of recipients from January 2016 to December 2021 in a single center. The primary objective of this study is to find the readmission rate for kidney transplants and the variables that contribute to readmission. Post-transplant complications that were resulted in the readmission categorized into surgical complications, graft-related complications, infections, DVT, and other medical complications.

RESULTS

Four hundred seventy-four renal allograft recipients met our inclusion criteria and were included in the study. 248 (52.3%) of the allograft recipients had at least one readmission during the first 90 days after the transplantation. 89 (18.8%) allograft recipients had more than one readmission episode in the first 90 days post-transplant. The perinephric fluid collection was the most common surgical complication (52.4%), and UTI was the most common infection (50%), causing readmission in the first 90 days post-transplant. The readmission odd ratio was significantly higher in patients above 60 years old and in kidneys with KDPI ≥ 85, and in recipients with DGF.

CONCLUSION

Early hospital readmission (EHR) following a kidney transplant is a common complication. Identifying the causes not only helps the transplant centers to take further steps to prevent some incidents and help to improve the patients' morbidities and mortalities, but also it can reduce the unnecessary costs of readmissions.

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.

Delayed graft function: current status and future directions

PURPOSE OF REVIEW

Delayed graft function is a common early posttransplant event predictive of adverse outcomes including hospital readmission, impaired long-term graft function, and decreased graft and patient survival. The purpose of this review is to summarize recent literature describing delayed graft function in hopes of better understanding and managing this condition.

RECENT FINDINGS

Recent research efforts have been garnered towards risk factor modification, prevention, and earlier detection of delayed graft function. In this review, we aim to summarize current innovative approaches and future directions.

SUMMARY

Delayed graft function portends worse graft and patient outcomes. Continued research to prevent, and detect early perturbations in allograft function, and more optimally manage this disease will hopefully improve graft function, along with graft/patient survival.

Analysis of individual components of frailty: Pre-transplant grip strength is the strongest predictor of post kidney transplant outcomes

Frailty is commonly assessed during kidney transplant recipient (KTR) evaluation. However, individual frailty components may have varying impact on post-transplant outcomes. In this single-center study of 825 KTRs, we determined the association between the individual components of a modified Fried frailty score and delayed graft function (DGF), early hospital readmission (EHR), cardiovascular (CV) events, acute rejection (AR), death censored graft failure (DCGF), and death. Sum frailty ≥3 was significantly associated with EHR (aOR = 3.62; 95% CI: 1.21-10.80). Among individual components, only grip strength was significantly associated with EHR (aOR = 1.54; 95% CI: 1.03-2.31). The addition of grip strength to a model with the other four components resulted in Net Reclassification Improvement (NRI) of 20.51% (p = .01). Similarly, only grip strength was significantly associated with CV events (aOR = 1.79; 95% CI: 1.12-2.86). The addition of grip strength to a model with the other four components resulted in NRI of 27.37% (p = .006). No other frailty components were associated with the outcomes of interest. Based on our findings, handgrip strength may be an important tool while assessing frailty, mainly predicting early readmission and cardiovascular events post-transplant.

O impacto da terapia de indução universal na readmissão hospitalar precoce de receptores de transplante renal

Resumo Histórico: A Readmissão Hospitalar Precoce (RHP) está associada a piores desfechos. O uso de terapia de indução com globulina antitimócito (rATG, por sua sigla em inglês) está associado ao aumento da eficácia na prevenção de rejeição aguda, embora ainda existam preocupações quanto à segurança. Métodos: Este estudo retrospectivo de centro único comparou a incidência, as causas da RHP e os desfechos clínicos de um ano de pacientes que receberam transplante renal entre 18 de Agosto de 2011 e 31 de Dezembro de 2012 (Antiga Era), em que apenas pacientes de alto risco receberam 5 mg/kg de rATG, com aqueles transplantados entre 18 de Agosto de 2014 e 31 de Dezembro de 2015 (Nova Era), em que todos os pacientes receberam uma única dose de 3 mg/kg de rATG. Resultados: Houve 788 pacientes da Antiga Era e 800 da Nova Era. A incidência de RHP nos pacientes da antiga era foi de 26,4% e nos pacientes da nova era, 22,5% (p = 0,071). A principal causa de RHP em ambas as eras foi infecção (67% vs. 68%). A incidência de episódios de rejeição aguda foi menor (22,7% vs. 3,5%; p < 0,001) e a sobrevida do paciente em um ano foi maior (95,6% vs. 98,1%; vs. p = 0,004) em pacientes da nova era. Conclusão: O uso universal de terapia de indução de 3 mg/kg de rATG em dose única na nova era foi associado a uma tendência à redução da RHP e a uma redução na incidência de rejeição aguda e mortalidade.

Incidence, predictors, and outcomes of early hospital readmissions after kidney transplantation: Systemic review and meta-analysis

BACKGROUND

Early hospital readmission (EHR) within 30 days after kidney transplantation is a significant quality indicator of transplant centers and patient care. This meta-analysis aims to evaluate the incidence, predictors, and outcomes of EHR after kidney transplantation.

METHODS

We comprehensively searched the databases, including PubMed, Cochrane CENTRAL, and Embase, from inception until December 2021 to identify studies that assessed incidence, risk factors, and outcome of EHR. The outcomes included death-censored graft failure and mortality. Data from each study were combined using the random effect to calculate the pooled incidence, mean difference (MD), odds ratio (OR), and hazard ratio (HR) with 95% confidence interval (CI).

RESULTS

A total of 17 studies were included. The pooled EHR incidence after kidney transplant was 24.4% (95% CI 21.7-27.3). Meta-analysis showed that recipient characteristics, including older recipient age (MD 2.05; 95% CI 0.90-3.20), Black race (OR 1.31; 95% CI 1.11, 1.55), diabetes (OR 1.32; 95% CI 1.22-1.43), and longer dialysis duration (MD 0.85; 95% CI 0.41, 1.29), donor characteristics, including older donor age (MD 2.02; 95% CI 0.93-3.11), and transplant characteristics, including delayed graft function (OR 1.75; 95% CI 1.42-2.16) and longer length of hospital stay during transplantation (MD 1.93; 95% CI 0.59-3.27), were significantly associated with the increased risk of EHR. EHR was significantly associated with the increased risk of death-censored graft failure (HR 1.70; 95% CI 1.43-2.02) and mortality (HR 1.46; 95% CI 1.27-1.67) within the first year after transplantation.

CONCLUSION

Almost one-fourth of kidney transplant recipients had EHR within 30 days after transplant, and they had worse post-transplant outcomes. Several risk factors for EHR were identified. This calls for future research to develop and implement for management strategies to reduce EHR in high-risk patients.

Burden of early hospitalization after simultaneous liver-kidney transplantation: Results from the US Multicenter SLKT Consortium

The burden of early hospitalization (within 6 months) following simultaneous liver-kidney transplant (SLKT) is not known. We examined risk factors associated with early hospitalization after SLKT and their impact on patient mortality conditional on 6-month survival. We used data from the US Multicenter SLKT Consortium cohort study of all adult SLKT recipients between 2002 and 2017 who were discharged alive following SLKT. We used Poisson regression to model rates of early hospitalizations after SLKT. Cox regression was used to identify risk factors associated with mortality conditional on survival at 6 months after SLKT. Median age (N = 549) was 57.7 years (interquartile range [IQR], 50.6-63.9) with 63% males and 76% Whites; 33% had hepatitis C virus, 20% had non-alcohol-associated fatty liver disease, 23% alcohol-associated liver disease, and 24% other etiologies. Median body mass index (BMI) and Model for End-Stage Liver Disease-sodium scores were 27.2 kg/m2 (IQR, 23.6-32.2 kg/m2 ) and 28 (IQR, 23-34), respectively. Two-thirds of the cohort had at least one hospitalization within the first 6 months of SLKT. Age, race, hospitalization at SLKT, diabetes mellitus, BMI, and discharge to subacute rehabilitation (SAR) facility after SLKT were independently associated with a high incidence rate ratio of early hospitalization. Number of hospitalizations within the first 6 months did not affect conditional survival. Early hospitalizations after SLKT were very common but did not affect conditional survival. Although most of the risk factors for early hospitalization were nonmodifiable, discharge to SAR after initial SLKT was associated with a significantly higher incidence rate of early hospitalization. Efforts and resources should be focused on identifying SLKT recipients at high risk for early hospitalization to optimize their predischarge care, discharge planning, and long-term follow-up.

Feasibility and Acceptability of a mHealth Self-Management Intervention for Pediatric Transplant Families

Families of pediatric solid organ transplant recipients need ongoing education and support in the first 30 days following hospital discharge for the transplantation. The purpose of this report is to describe the feasibility, acceptability, and preliminary efficacy of a mHealth family-self management intervention, (myFAMI), designed to improve post-discharge outcomes of coping, family quality of life, self-efficacy, family self-management, and utilization of health care resources. We enrolled 46 primary family members. myFAMI was feasible and acceptable; 81% (n=17/21) of family members completed the app at least 24/30 days (goal 80% completion rate). Family members generated 134 trigger alerts and received a nurse response within the goal timeframe of < 2 h 99% of the time. Although there were no significant differences between groups, primary outcomes were in the expected direction. The intervention was well received and is feasible for future post-discharge interventions for families of children who receive an organ transplant.

Re-Hospitalization in First Six Months After Live Related Renal Transplantation: Risk Factors, Burden, Causes and Outcomes

Objective

The aim of our study was to evaluate the incidence, causes, risk factors, outcomes, and cost of hospital readmission after live related renal transplantation (LRRT).

Methods

We conducted a cross-sectional study and followed patients’ re-admissions for six months whose LRRT was done in our center between September 2019 and June 2020.

Results

We recruited 53 patients, 40 (75.5%) were male. The mean age was 36.9 ± 11.9 years. Donor gender was similar, and their mean age was 31.6 ± 9.2 years. The mean length of hospital stay after LRRT was 14 ± 2.2 days. A total of 81.1% were readmitted after LRRT within the first six months, with a total of 113 readmissions. The median time of readmission after LRRT was 66 days. The median readmission hospital stay was four days. The causes of readmission were surgical in 11 (9.7%), medical in 89 (78.8%), and combined medical and surgical in 13 (11.5%). Infection was the most common medical cause, followed by rejection. Statistically significant difference between readmission and non-readmission groups was found in estimated glomerular filtration rate (eGFR) at six month 61.3 ± 25.9 vs. 84.3 ± 36.1 mL/min/1.73 m² respectively (p = 0.02). The median cost of readmission was PKR 40629, equivalent to USD 261.

Conclusion

Over three-fourths of the patients were readmitted after LRRT within the first six months. The most common causes were infection and rejection. Readmissions after LRRT are associated with lower graft function at six months and a significant cost burden on the health system.

Outcomes and Health Care Utilization After Early Hospital Dismissal in Kidney Transplantation: An Analysis of 1001 Consecutive Cases

OBJECTIVE

To understand whether reduced lengths of stay after kidney transplantation were associated with excess health care utilization in the first 90 days or long-term graft and patient survival outcomes.

BACKGROUND

Reducing length of stay after kidney transplant has an unknown effect on post-transplant health care utilization. We studied this association in a cohort of 1001 consecutive kidney transplants.

METHODS

We retrospectively reviewed 2011-2015 data from a prospectively-maintained kidney transplant database from a single center.

RESULTS

A total of 1001 patients underwent kidney transplant, and were dismissed from the hospital in 3 groups: Early [≤2 days] (19.8%), Normal [3-7 days] (79.4%) and Late [>7 days] (3.8%). 34.8% of patients had living donor transplants (Early 51%, Normal 31.4%, Late 18.4%, P < 0.001). Early patients had lower delayed graft function rates (Early 19.2%, Normal 32%, Late73.7%, P = 0.001). By the hospital dismissal group, there were no differences in readmissions or emergency room visits at 30 or 90 days. Glomerular filtration rate at 12 months and rates of biopsy-proven acute rejection were also similar between groups. The timing of hospital dismissal was not associated with the risk-adjusted likelihood of readmission. Early and Normal patients had similar graft and patient survival. Late dismissal patients, who had higher rates of cardiovascular complications, had significantly higher late mortality versus Normal dismissal patients in unadjusted and risk-adjusted models.

CONCLUSION

Dismissing patients from the hospital 2 days after kidney transplant is safe, feasible, and improves value. It is not associated with excess health care utilization or worse short or long-term transplant outcomes.

Risk Factors and Outcomes of Early Hospital Readmission in Canadian Kidney Transplant Recipients: A Population-Based Multi-Center Cohort Study

Background:

Early hospital readmissions (EHRs) occur commonly in kidney transplant recipients. Conflicting evidence exists regarding risk factors and outcomes of EHRs.

Objective:

To determine risk factors and outcomes associated with EHRs (ie, hospitalization within 30 days of discharge from transplant hospitalization) in kidney transplant recipients.

Design:

Population-based cohort study using linked, administrative health care databases.

Setting:

Ontario, Canada.

Patients:

We included 5437 kidney transplant recipients from 2002 to 2015.

Measurements:

Risk factors and outcomes associated with EHRs. We assessed donor, recipient, and transplant risk factors. We also assessed the following outcomes: total graft failure, death-censored graft failure, death with a functioning graft, mortality, and late hospital readmission.

Methods:

We used multivariable logistic regression to examine the association of each risk factor and the odds of EHR. To examine the relationship between EHR status (yes vs no [reference]) and the outcomes associated with EHR (eg, total graft failure), we used a multivariable Cox proportional hazards model.

Results:

In all, 1128 kidney transplant recipients (20.7%) experienced an EHR. We found the following risk factors were associated with an increased risk of EHR: older recipient age, lower income quintile, several comorbidities, longer hospitalization for initial kidney transplant, and older donor age. After adjusting for clinical characteristics, compared to recipients without an EHR, recipients with an EHR had an increased risk of total graft failure (adjusted hazard ratio [aHR]: 1.46, 95% CI: 1.29, 1.65), death-censored graft failure (aHR: 1.62, 95% CI: 1.36, 1.94), death with graft function (aHR: 1.34, 95% CI: 1.13, 1.59), mortality (aHR: 1.41, 95% CI: 1.22, 1.63), and late hospital readmission in the first 0.5 years of follow-up (eg, 0 to <0.25 years: aHR: 2.11, 95% CI: 1.85, 2.40).

Limitations:

We were not able to identify which readmissions could have been preventable and there is a potential for residual confounding.

Conclusions:

Results can be used to identify kidney transplant recipients at risk of EHR and emphasize the need for interventions to reduce the risk of EHRs.

Trial registration:

This is not applicable as this is a population-based cohort study and not a clinical trial.

Design and development of myFAMI application framework: a mHealth self-management intervention for family members of pediatric transplant recipients

Background

Solid-organ transplantation is the treatment of choice for children with end-stage organ failure. Ongoing recovery and medical management at home after transplant are important for recovery and transition to daily life. Smartphones are widely used and hold the potential for aiding in the establishment of mobile health (mHealth) protocols. Health care providers, nurses, and computer scientists collaboratively designed and developed mHealth family self-management intervention (myFAMI), a smartphone-based intervention app to promote a family self-management intervention for pediatric transplant patients’ families.

Objective

This paper presents outcomes of the design stages and development actions of the myFAMI app framework, along with key challenges, limitations, and strengths.

Methods

The myFAMI app framework is built upon a theory-based intervention for pediatric transplant patients, with aid from the action research (AR) methodology. Based on initially defined design motivation, the team of researchers collaboratively explored 4 research stages (research discussions, feedback and motivations, alpha testing, and deployment and release improvements) and developed features required for successful inauguration of the app in the real-world setting.

Results

Deriving from app users and their functionalities, the myFAMI app framework is built with 2 primary components: the web app (for nurses’ and superadmin usage) and the smartphone app (for participant/family member usage). The web app stores survey responses and triggers alerts to nurses, when required, based on the family members’ response. The smartphone app presents the notifications sent from the server to the participants and captures survey responses. Both the web app and the smartphone app were built upon industry-standard software development frameworks and demonstrate great performance when deployed and used by study participants.

Conclusions

The paper summarizes a successful and efficient mHealth app-building process using a theory-based intervention in nursing and the AR methodology in computer science. Focusing on factors to improve efficiency enabled easy navigation of the app and collection of data. This work lays the foundation for researchers to carefully integrate necessary information (from the literature or experienced clinicians) to provide a robust and efficient solution and evaluate the acceptability, utility, and usability for similar studies in the future.

International Registered Report Identifier (IRRID)

RR2-10.1002/nur.22010

Remote Mobile Outpatient Monitoring in Transplant (Reboot) 2.0: Protocol for a Randomized Controlled Trial

Background

The number of solid organ transplants in Canada has increased 33% over the past decade. Hospital readmissions are common within the first year after transplant and are linked to increased morbidity and mortality. Nearly half of these admissions to the hospital appear to be preventable. Mobile health (mHealth) technologies hold promise to reduce admission to the hospital and improve patient outcomes, as they allow real-time monitoring and timely clinical intervention.

Objective

This study aims to determine whether an innovative mHealth intervention can reduce hospital readmission and unscheduled visits to the emergency department or transplant clinic. Our second objective is to assess the use of clinical and continuous ambulatory physiologic data to develop machine learning algorithms to predict the risk of infection, organ rejection, and early mortality in adult heart, kidney, and liver transplant recipients.

Methods

Remote Mobile Outpatient Monitoring in Transplant (Reboot) 2.0 is a two-phased single-center study to be conducted at the University Health Network in Toronto, Canada. Phase one will consist of a 1-year concealed randomized controlled trial of 400 adult heart, kidney, and liver transplant recipients. Participants will be randomized to receive either personalized communication using an mHealth app in addition to standard of care phone communication (intervention group) or standard of care communication only (control group). In phase two, the prior collected data set will be used to develop machine learning algorithms to identify early markers of rejection, infection, and graft dysfunction posttransplantation. The primary outcome will be a composite of any unscheduled hospital admission, visits to the emergency department or transplant clinic, following discharge from the index admission. Secondary outcomes will include patient-reported outcomes using validated self-administered questionnaires, 1-year graft survival rate, 1-year patient survival rate, and the number of standard of care phone voice messages.

Results

At the time of this paper’s completion, no results are available.

Conclusions

Building from previous work, this project will aim to leverage an innovative mHealth app to improve outcomes and reduce hospital readmission in adult solid organ transplant recipients. Additionally, the development of machine learning algorithms to better predict adverse health outcomes will allow for personalized medicine to tailor clinician-patient interactions and mitigate the health care burden of a growing patient population.

Trial Registration

ClinicalTrials.gov NCT04721288; https://www.clinicaltrials.gov/ct2/show/NCT04721288

International Registered Report Identifier (IRRID)

PRR1-10.2196/26816

Ambient air pollution and posttransplant outcomes among kidney transplant recipients

Fine particulate matter (PM2.5 ), a common form of air pollution which can induce systemic inflammatory response, is a risk factor for adverse health outcomes. Kidney transplant (KT) recipients are likely vulnerable to PM2.5 due to comorbidity and chronic immunosuppression. We sought to quantify the association between PM2.5 and post-KT outcomes. For adult KT recipients (1/1/2010-12/31/2016) in the Scientific Registry of Transplant Recipients, we estimated annual zip-code level PM2.5 concentrations at the time of KT using NASA's SEDAC Global PM2.5 Grids. We determined the associations between PM2.5 and delayed graft function (DGF) and 1-year acute rejection using logistic regression and death-censored graft failure (DCGF) and mortality using Cox proportional hazard models. All models were adjusted for sociodemographics, recipient, transplant, and ZIP code level confounders. Among 87 233 KT recipients, PM2.5 was associated with increased odds of DGF (OR = 1.59; 95% CI: 1.48-1.71) and 1-year acute rejection (OR = 1.31; 95% CI: 1.17-1.46) and increased risk of all-cause mortality (HR = 1.15; 95% CI: 1.07-1.23) but not DCGF (HR = 1.05; 95% CI: 0.97-1.51). In conclusion, PM2.5 was associated with higher odds of DGF and 1-year acute rejection and elevated risk of mortality among KT recipients. Our study highlights the importance of considering environmental exposure as risk factors for post-KT outcomes.

Kidney Transplantation Confers Survival Benefit for Candidates With Pulmonary Hypertension

Kidney transplantation (KT) is controversial in patients with pretransplant pulmonary hypertension (PtPH). We aimed to quantify post-KT graft and patient survival as well as survival benefit in recipients with PtPH.

Methods

Using UR Renal Data System (2000-2018), we studied 90 819 adult KT recipients. Delayed graft function, death-censored graft failure, and mortality were compared between recipients with and without PtPH using inverse probability weighted logistic and Cox regression. Survival benefit of KT was determined using stochastic matching and stabilized inverse probability treatment Cox regression.

Results

Among 90 819 KT recipients, 2641 (2.9%) had PtPH. PtPH was associated with higher risk of delayed graft function (odds ratio, 1.23; 95% CI, 1.10-1.36; P < 0.01), death-censored graft failure (hazard ratio [HR], 1.23; 95% CI, 1.11-1.38; P < 0.01), and mortality (HR, 1.56; 95% CI, 1.44-1.69; P < 0.01). However, patients with PtPH who received a KT had a 46% reduction in mortality (HR, 0.54; 95% CI, 0.48-0.61; P < 0.01) compared with those who remained on the waitlist.

Conclusions

Although PtPH is associated with inferior post-KT outcomes, KT is associated with better survival compared with remaining on the waitlist. Therefore, KT is a viable treatment modality for appropriately selected patients with PtPH.

Definition and Analysis of Textbook Outcome: A Novel Quality Measure in Kidney Transplantation

BACKGROUND

"Textbook outcome" (TO) is a novel composite quality measure that encompasses multiple postoperative endpoints, representing the ideal "textbook" hospitalization for complex surgical procedures. We defined TO for kidney transplantation using a cohort from a high-volume institution.

METHODS

Adult patients who underwent isolated kidney transplantation at our institution between 2016 and 2019 were included. TO was defined by clinician consensus at our institution to include freedom from intraoperative complication, postoperative reintervention, 30-day intensive care unit or hospital readmission, length of stay > 75th percentile of kidney transplant patients, 90-day mortality, 30-day acute rejection, delayed graft function, and discharge with a Foley catheter. Recipient, operative, financial characteristics, and post-transplant patient, graft, and rejection-free survival were compared between patients who achieved and failed to achieve TO.

RESULTS

A total of 557 kidney transplant patients were included. Of those, 245 (44%) achieved TO. The most common reasons for TO failure were delayed graft function (N = 157, 50%) and hospital readmission within 30 days (N = 155, 50%); the least common was mortality within 90 days (N = 6, 2%). Patient, graft, and rejection-free survival were significantly improved among patients who achieved TO. On average, patients who achieved TO incurred approximately $50,000 less in total inpatient charges compared to those who failed TO.

CONCLUSIONS

TO in kidney transplantation was associated with favorable post-transplant outcomes and significant cost-savings. TO may offer transplant centers a detailed performance breakdown to identify aspects of perioperative care in need of process improvement.

Donor type and 3-month hospital readmission following kidney transplantation: results from the Netherlands organ transplant registry

BACKGROUND

Hospital readmission after transplantation is common in kidney transplant recipients (KTRs). In this study, we aim to compare the risk of 3-month hospital readmission after kidney transplantation with different donor types in the overall population and in both young (< 65 years) and elderly (≥65 years) KTRs.

METHODS

We included all first-time adult KTRs from 2016 to 2018 in the Netherlands Organ Transplant Registry. Multivariable logistic regression models were used to estimate the effect while adjusting for baseline confounders.

RESULTS

Among 1917 KTRs, 615 (32.1%) had at least one hospital readmission. Living donor kidney transplantation (LDKT) recipients had an adjusted OR of 0.76 (95%CI, 0.61 to 0.96; p = 0.02) for hospital readmission compared to deceased donor kidney transplantation (DDKT) recipients. In the young and elderly, the adjusted ORs were 0.69 (95%CI, 0.52 to 0.90, p = 0.01) and 0.93 (95%CI, 0.62 to 1.39, p = 0.73) and did not differ significantly from each other (p-value for interaction = 0.38). In DDKT, the risk of hospital readmission is similar between recipients with donation after cardiac death (DCD) or brain death (DBD) and the risk was similar between the young and elderly.

CONCLUSION

A lower risk of post-transplant 3-month hospital readmission was found in recipients after LDKT compared to DDKT, and this benefit of LDKT might be less dominant in elderly patients. In DDKT, having either DCD or DBD donors is not associated with post-transplant 3-month hospital readmission, regardless of age. Tailored patient management is needed for recipients with DDKT and elderly KTRs.

What Are the Burden, Causes, and Costs of Early Hospital Readmissions After Kidney Transplantation?

Introduction:

Kidney transplant recipients are at risk for complications resulting in early hospital readmission. This study sought to determine the incidences, risk factors, causes, and financial costs of early readmissions.

Design:

This single-centre cohort study included 1461 kidney recipients from 1 Jul 2004 to 31 Dec 2012, with at least 1-year follow-up. Early readmission was defined as hospitalization within 30 or 90-days postdischarge from transplant admission. Associations between various parameters and 30 and 90-days posttransplant were determined using multivariable Cox proportional hazards models. The hospital-associated costs of were assessed.

Results:

The rates of early readmission were 19.4% at 30 days and 26.8% at 90 days posttransplant. Mean cost per 30-day readmission was 11 606 CAD. Infectious complications were the most common reasons and resulted in the greatest cost burden. Factors associated with 30 and 90-days in multivariable models were recipient history of chronic lung disease (hazard ratio or HR 1.78 [95%CI: 1.14, 2.76] and HR 1.68 [1.14, 2.48], respectively), median time on dialysis (HR 1.07 [95% CI: 1.01, 1.13]and HR 1.06 [95% CI: 1.01, 1.11], respectively), being transplanted preemptively (HR 1.75 [95% CI: 1.07, 2.88] and HR 1.66 [95% CI: 1.07, 2.57], respectively), and having a transplant hospitalization lasting of and more than 11 days (HR 1.52 [95% CI: 1.01, 2.27] and HR 1.65 [95% CI: 1.16, 2.34], respectively).

Discussion:

Early hospital readmission after transplantation was common and costly. Strategies to reduce the burden of early hospital readmissions are needed for all patients.

Clinical outcomes of a nurse-led post-discharge education program for heart-transplant recipients: A retrospective cohort study

BACKGROUND

Advances in immunosuppressive therapeutics and medical technology have improved survival rates after heart transplantation. Although there is a rigorous schedule of outpatient visits and testing to detect early signs of rejection and other complications in the first year after transplantation, repeated unplanned readmissions of heart transplant recipients remains a challenge.

OBJECTIVE

This study aimed to compare the effects of specialized nurse-led discharge education, including continuous post-transplant education and counselling, on heart transplant recipients' clinical outcomes, with the effects of existing discharge education.

METHODS

Participants were 136 heart transplantation recipients at a university-affiliated hospital in South Korea from November 1, 1994, to November 30, 2018. Participants' electronic medical records were retrospectively analyzed. Participants were grouped according to usual care (n = 25), nurse-led program (n = 66), and nurse-led program with post-discharge education (n = 45). We assessed the number of outpatient visits with clinical problems and days to first unplanned rehospitalization within one year after transplantation.

RESULTS

The nurse-led program with post-discharge education was associated with significantly reduced outpatient visits with clinical problems, compared to usual care and the existing nurse-led program. We also found a significantly longer time until first unplanned rehospitalization in the nurse-led program with post-discharge education group, compared to the usual care group.

CONCLUSION

This study identified the heart transplantation-specialized nurse-led discharge and subsequent post-discharge education as an effective strategy for positive clinical outcomes within one year after heart transplantation.

Renal transplantation outcomes in obese patients: a French cohort-based study

Background

Whilst there are a number of publications comparing the relationship between body mass index (BMI) of kidney transplant recipients and graft/patient survival, no study has assessed this for a French patient cohort.

Methods

In this study, cause-specific Cox models were used to study patient and graft survival and several other time-to-event measures. Logistic regressions were performed to study surgical complications at 30 days post-transplantation as well as delayed graft function.

Results

Among the 4691 included patients, 747 patients were considered obese with a BMI level greater than 30 kg/m². We observed a higher mortality for obese recipients (HR = 1.37, p = 0.0086) and higher risks of serious bacterial infections (HR = 1.24, p = 0.0006) and cardiac complications (HR = 1.45, p < 0.0001). We observed a trend towards death censored graft survival (HR = 1.22, p = 0.0666) and no significant increased risk of early surgical complications.

Conclusions

We showed that obesity increased the risk of death and serious bacterial infections and cardiac complications in obese French kidney transplant recipients. Further epidemiologic studies aiming to compare obese recipients versus obese candidates remaining on dialysis are needed to improve the guidelines for obese patient transplant allocation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02278-1.

Clinical Outcomes of Older Kidney Transplant Recipients

BACKGROUND

Older kidney transplant recipients (OKTR) are vulnerable to infections and AKI, often prompting hospitalization. This study elucidates etiology of hospitalizations, AKI, and outcomes in OKTR.

METHODS

Retrospective study of 500 patients age ≥ 60, who underwent kidney transplantation from 2005-2015. Demographic, transplant, and outcomes data were collected.

RESULTS

OKTR had mean age 66 years; 59% males and 50% African Americans. 62% had at least one hospitalization post-transplant. Predictors of hospitalization were DGF, DM, panel reactive antibodies (PRA), dialysis duration. Hospitalization was mostly due to infection and surgical complications. Average length of stay was 6.4 days. OKTR with at least one hospitalization had 84% higher risk for graft loss (p=0.001). 56% of older kidney transplant recipients had at least one AKI episode post-transplant. Predictors of AKI included DGF, older, African American donor, and tacrolimus variability. The most common etiologies for AKI were infection, dehydration, and GI complications. OKTR with at least one AKI episode had 2.6-fold higher risk for graft loss (p<0.001).

CONCLUSIONS

Post-transplant hospitalization and AKI in OKTR significantly impact graft survival. Addressing comorbidities and risks in the pre-transplant and outpatient setting may help alleviate burden of hospitalization and risk of AKI in OKTR and improve graft outcomes.

KDIGO Clinical Practice Guideline on the Evaluation and Management of Candidates for Kidney Transplantation

The 2020 Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline on the Evaluation and Management of Candidates for Kidney Transplantation is intended to assist health care professionals worldwide who evaluate and manage potential candidates for deceased or living donor kidney transplantation. This guideline addresses general candidacy issues such as access to transplantation, patient demographic and health status factors, and immunological and psychosocial assessment. The roles of various risk factors and comorbid conditions governing an individual's suitability for transplantation such as adherence, tobacco use, diabetes, obesity, perioperative issues, causes of kidney failure, infections, malignancy, pulmonary disease, cardiac and peripheral arterial disease, neurologic disease, gastrointestinal and liver disease, hematologic disease, and bone and mineral disorder are also addressed. This guideline provides recommendations for evaluation of individual aspects of a candidate's profile such that each risk factor and comorbidity are considered separately. The goal is to assist the clinical team to assimilate all data relevant to an individual, consider this within their local health context, and make an overall judgment on candidacy for transplantation. The guideline development process followed the Grades of Recommendation Assessment, Development, and Evaluation (GRADE) approach. Guideline recommendations are primarily based on systematic reviews of relevant studies and our assessment of the quality of that evidence, and the strengths of recommendations are provided. Limitations of the evidence are discussed with differences from previous guidelines noted and suggestions for future research are also provided.

Antithymocyte induction dosing and incidence of opportunistic viral infections using steroid-free maintenance immunosuppression

BACKGROUND

Currently, there is limited literature evaluating rATG induction dosing and incidence of opportunistic viral infections when using steroid-free maintenance immunosuppression.

METHODS

This single-center, retrospective, study compared high rATG (>4.5 mg/kg) versus low (<4.5 mg/kg) induction dosing and the overall incidence of early opportunistic viral infection at 180 days in the setting of maintenance immunosuppression consisting of tacrolimus, mycophenolate, rapid steroid withdrawal, and a tiered antiviral prevention strategy based on donor-recipient Cytomegalovirus (CMV) serostatus.

RESULTS

A total of 209 patients were included; 76 patients received low-dose and 133 patients received high-dose rATG. Incidence of overall opportunistic viral infection occurred more frequently in patients who received high compared to low dose (29.8% vs 25% p = .030). Incidence of CMV infection was also significantly increased in the high-dose group (31.6% vs 18.4% p = .039). In a multivariable model, rATG dose, as a continuous variable, remained a significant independent predictor of infection along with CMV risk (OR 1.46, 95% CI 1.02-2.09) controlling for age and CMV risk. There were no differences in graft-related outcomes at 180 days.

CONCLUSION

Higher cumulative rATG induction dose was associated with increased incidence of opportunistic viral infections, in the setting of a steroid-free maintenance immunosuppression in the early post-transplant period.

Unplanned hospital readmissions after kidney transplantation among patients in Hefei, China: Incidence, causes and risk factors

Objectives

Unplanned readmissions severely affect a patient's physical and mental well-being after kidney transplantation (KT), which is also independently associated with morbidity. A retrospective study was conducted to identify the incidence, causes and risk factors for unplanned readmission after KT among Chinese patients.

Methods

Patients who underwent KT were admitted to the organ transplant center of the Affiliated Hospital of University of Science and Technology of China (2017-2018). Medical records for these patients were obtained through the hospital information system (HIS).

Results

In 518 patients, the incidence of unplanned readmissions within 30 days (n = 9) was 1.74%, and 90 days (n = 64) was 12.35%. The one-year unplanned readmission rate was 22.59% (n = 122). Overall, 122 patients were readmitted because of infection, renal events, metabolic disturbances, surgical complications, etc. Hemodialysis (OR = 10.462, 95% CI: 1.355-80.748), peritoneal dialysis (OR = 8.746, 95% CI: 1.074-71.238) and length of stay (OR = 1.023, 95% CI: 1.006-1.040) were independent risk factors for unplanned readmissions.

Conclusion

Unplanned readmission rates increased with time after KT. Certain risk factors related to unplanned readmissions should be deeply excavated. Targeted interventions for controllable factors to alleviate the rate of unplanned readmissions should be identified.

Early and recurrent hospitalization after kidney transplantation: Analysis of a contemporary canadian cohort of kidney transplant recipients

Hospital readmission is a common occurrence following kidney transplantation, but less is known about the predictors of early and recurrent hospitalization. We analyzed a cohort of adult kidney transplant recipients in Nova Scotia, Canada, from January 2010 to December 2015. Readmission rates for 30 days, 6 months, and 1 year were calculated as a proportion of total transplants. Factors independently associated with early readmission were investigated using multivariable Cox hazards models with multivariable Anderson-Gill Cox models being used for factors independently associated with recurrent readmission. Of the 213 patients included, 41 (19.2%), 78 (36.6%), and 88 (41.3%) were readmitted to hospital within 30 days, 6 months, and 1 year, respectively. On multivariable analyses, a history of congestive heart failure (HR 1.741, 95% CI 1.039-2.918), peptic ulcer disease (HR 2.290, 95% CI 1.054-4.973), and liver disease (HR 2.492, 95% CI 1.162-5.344) was associated with higher risk of first rehospitalization. Recurrent hospital admission was associated with initial hospital duration ≥ 8 days (HR 2.140, 95% CI 1.265-3.618), congestive heart failure (HR 1.366, 95% CI 1.044-1.787), and liver disease (HR 1.785, 95% CI 1.257-2.534). Increasing duration of initial hospitalization, congestive heart failure, and liver disease are important to consider when evaluating a patient's risk for recurrent readmission following kidney transplant.

The effects of a transitional care program on discharge readiness, transitional care quality, health services utilization and satisfaction among Chinese kidney transplant recipients: A randomized controlled trial

BACKGROUND

Kidney transplantation is the major treatment for end-stage renal disease (ESRD). However, kidney transplant recipients (KTRs) face severe challenges during the transition period from hospital discharge to home, increasing the risk of early hospital readmission (EHR) and affecting patient safety. Nevertheless, knowledge of effective transitional care for KTRs is limited in China.

OBJECTIVE

To evaluate the effectiveness of an innovative transitional care program in improving discharge readiness, transitional care quality, health services utilization and patient satisfaction among KTRs in China.

DESIGN

A prospective randomized controlled trial.

SETTINGS AND PARTICIPANTS

Patients admitted to undergo kidney transplantation were recruited in a general tertiary hospital in Chengdu, China.

METHODS

A total of 220 eligible patients were recruited and randomly assigned to the intervention and control groups. Participants in the intervention group received a transitional care intervention developed by the research team, including a risk assessment for early readmission, health education from admission to predischarge, individualized discharge planning, and a telephone follow-up once per week for one month and WeChat follow-up postdischarge. The control group received routine care of comparable length and follow-up contact. A trained research assistant collected all patients' baseline data on admission (T0), evaluated the discharge readiness (by the Readiness for Hospital Discharge Scale) on the day of discharge (T1), collected data on transitional care quality (by the Care Transition Measure-15) and patients' satisfaction with transitional care services (by a self-developed patient satisfaction scale) on the 30th day postdischarge (T2), and collected data on hospital readmission, unscheduled outpatient department visits, and emergency room visits on the 30th and 90th days (by a self-developed health services utilization record table) (T3) postdischarge. Intervention effects were analyzed using independent samples t-tests, Wilcoxon-Mann-Whitney U tests, Chi-square tests or Fisher's exact test.

RESULTS

Compared with the control group, the intervention group showed significantly better discharge readiness (personal status, P<0.001; knowledge, P = 0.010; coping ability, P<0.001; expected support, P = 0.007; total score, P<0.001), better transitional care quality (importance of preferences, P<0.001; management preparation, P<0.001; critical understanding, P = 0.003; written and understandable care plan, P = 0.012; total score, P<0.001), lower readmission rate at T2 (P = 0.033) and at T3 (P = 0.013), lower emergency room visit rate at T3 (P = 0.014), and better satisfaction with transitional care services (P<0.001).

CONCLUSIONS

This study provides evidence that an innovative transitional care program is effective in promoting KTRs' discharge readiness, transitional care quality, reducing hospital readmission and emergency room visits, and improving their satisfaction with transitional care services.

TRIAL REGISTRATION

Clinical Trials ChiCTR1800014971.

Determinants of Poor Glycemic Control in Patients with Kidney Transplants: A Single-Center Retrospective Cohort Study in Canada

Background:

Kidney transplant immunosuppressive medications are known to impair glucose metabolism, causing worsened glycemic control in patients with pre-transplant diabetes mellitus (PrTDM) and new onset of diabetes after transplant (NODAT).

Objectives:

To determine the incidence, risk factors, and outcomes of both PrTDM and NODAT patients.

Design:

This is a single-center retrospective observational cohort study.

Setting:

The Ottawa Hospital, Ontario, Canada.

Participant:

A total of 132 adult (>18 years) kidney transplant patients from 2013 to 2015 were retrospectively followed 3 years post-transplant.

Measurements:

Patient characteristics, transplant information, pre- and post-transplant HbA1C and random glucose, follow-up appointments, complications, and readmissions.

Methods:

We looked at the prevalence of poor glycemic control (HbA1c >8.5%) in the PrTDM group before and after transplant and compared the prevalence, follow-up appointments, and rate of complications and readmission rates in both the PrTDM and NODAT groups. We determined the risk factors of developing poor glycemic control in PrTDM patients and NODAT. Student t-test was used to compare means, chi-squared test was used to compare percentages, and univariate analysis to determine risk factors was performed by logistical regression.

Results:

A total of 42 patients (31.8%) had PrTDM and 12 patients (13.3%) developed NODAT. Poor glycemic control (HbA1c >8.5%) was more prevalent in the PrTDM (76.4%) patients compared to those with NODAT (16.7%; P < .01). PrTDM patients were more likely to receive follow-up with an endocrinologist (P < .01) and diabetes nurse (P < .01) compared to those with NODAT. There were no differences in the complication and readmission rates for PrTDM and NODAT patients. Receiving a transplant from a deceased donor was associated with having poor glycemic control, odds ratio (OR) = 3.34, confidence interval (CI = 1.08, 10.4), P = .04. Both patient age, OR = 1.07, CI (1.02, 1.3), P < .01, and peritoneal dialysis prior to transplant, OR = 4.57, CI (1.28, 16.3), P = .02, were associated with NODAT.

Limitations:

Our study was limited by our small sample size. We also could not account for any diabetes screening performed outside of our center or follow-up appointments with family physicians or community endocrinologists.

Conclusion:

Poor glycemic control is common in the kidney transplant population. Glycemic targets for patients with PrTDM are not being met in our center and our study highlights the gap in the literature focusing on the prevalence and outcomes of poor glycemic control in these patients. Closer follow-up and attention may be needed for those who are at risk for worse glycemic control, which include older patients, those who received a deceased donor kidney, and/or prior peritoneal dialysis.

Uncontrolled donation after circulatory death improves access to kidney transplantation: A decision analysis

AIM

Uncontrolled donation after cardiac death (uDCD) remains an underutilized source of kidney allografts in the United States. The objective of this study was to estimate the impact of the implementation of a uDCD program on transplantation rates and long-term survival for patients with end-stage renal disease (ESRD) in the United States.

METHODS

A decision-analytic Markov state transition model was created using medical decision-making software (DATA 3.5; TreeAge Software, Inc) to estimate the impact of an uDCD program on transplantation rates and patient survival. Additionally, sensitivity analysis of uDCD donor pool increase was modeled. All model statistic parameters were extracted from the literature.

RESULTS

A uDCD program increased the rate of transplant at 10 years (37.8%, Accept uDCD group, vs 35.9%, Reject uDCD group). At 10 years, overall survival for Accept uDCD was 55.6% compared to 54.8% in the Reject uDCD.

CONCLUSIONS

Uncontrolled DCD improves access to transplant for ESRD patients on the kidney transplant waitlist, thereby improving long-term survival.

Early Hospital Readmission (EHR) in kidney transplantation: a review article

Early hospital readmission (EHR), defined as all readmissions within 30 days of initial hospital discharge, is a health care quality measure. It is influenced by the demographic characteristics of the population at risk, the multidisciplinary approach for hospital discharge, the access, coverage, and comprehensiveness of the health care system, and reimbursement policies. EHR is associated with higher morbidity, mortality, and increased health care costs. Monitoring EHR enables the identification of hospital and outpatient healthcare weaknesses and the implementation of corrective interventions. Among kidney transplant recipients in the USA, EHR ranges between 18 and 47%, and is associated with one-year increased mortality and graft loss. One study in Brazil showed an incidence of 19.8% of EHR. The main causes of readmission were infections and surgical and metabolic complications. Strategies to reduce early hospital readmission are therefore essential and should consider the local factors, including socio-economic conditions, epidemiology and endemic diseases, and mobility.

Rehospitalization Following Pediatric Heart Transplantation: Incidence, Indications, and Risk Factors

Rehospitalization following pediatric heart transplantation is common. However, existing data remain somewhat limited. Using a novel linkage between administrative and clinical databases, pediatric heart transplant (HT) recipients from 29 centers who survived to discharge were retrospectively reviewed to determine the frequency, timing of, and indication for all-cause rehospitalizations in the year following transplant discharge. Of 2870 pediatric HT recipients, 1835 (63.9%) were rehospitalized in the first year post-discharge (5429 total readmissions). Rehospitalization rates varied significantly across centers (46% to 100%) and were inversely correlated to center transplant volume (r² 0.25, p < 0.01). The median number of rehospitalizations per patient was 2 (IQR 1-4) and the median time to first rehospitalization was 29 days (IQR 9-99 days). Independent risk factors for rehospitalization included younger age at HT (HR 0.99, 95% CI 0.97-0.99), congenital heart disease (HR 1.2, 95% CI 1.1-1.4), listing status 1B at transplant (HR 1.3, 95% CI 1.1-1.5), and post-transplant complications including rejection prior to discharge (HR 1.5 95% CI 1.3-1.8) and chylothorax (HR 1.3, 95% CI 1.0-1.6). Cardiac diagnoses were the most common indication for rehospitalization (n = 1600, 29.5%), followed by infection (n = 1367, 25.2%). These findings may serve to guide the development of interventions aimed at reducing post-HT hospitalizations.

"Early" and "Late" Hospital readmissions in the first year after kidney transplant at a single center

BACKGROUND

Hospital readmission (HR) after surgery is considered a quality metric.

METHODS

Data on 2371 first-time adult kidney transplant (KT) recipients were collected to analyze the "early" (≤30 days) and "late" (31-365 days) HR patterns after KT at a single center over a 12-year time span (2002-2013).

RESULTS

30-day, 90-day, and 1-year HR were 31%, 41%, and 53%, respectively. Risk factors for HR included age >50, female sex, black race, BMI >30, transplant LOS >5 days, and pre-transplant time on dialysis >765 days. Indications for early (n = 749) and late (n = 508) HR were similar. Early HR (OR: 3.80, P = .007) and black race (OR: 2.38, P = .009) were associated with higher odds of 1-year graft failure while frequency (1-2, 3-4, 5+) of HR (ORs: 4.68, 8.36, 9.44, P < .001) and age > 50 (OR: 2.11, P = .007) were associated with higher odds of 1-year mortality. Transplant LOS > 5 days increased both odds of 1-year graft failure (OR: 3.51, P = .001) and mortality (OR: 2.05, P = .006). One-year graft and recipient survival were 96.7% and 94.8%, respectively.

CONCLUSIONS

Hospital readmission was associated with reduced graft and patient survival; however, despite a relatively high and consistent HR rate after KT, overall 1-year graft and patient survival was high.

Incidence of and Risk Factors for Multiple Readmissions after Kidney Transplantation

Unplanned readmission is often used as a surgical quality metric. A subset of kidney transplant recipients undergos multiple readmissions (MRs), although the incidence and risk factors are not well described. The aim of this study was to evaluate risk factors for MR after deceased donor kidney transplantation. All patients undergoing deceased donor kidney transplantation at a single center over a three-year period were analyzed via retrospective chart review for factors associated with MR. P values <0.05 were considered significant. Of 141 patients, the 30-day readmission rate was 26.2 per cent. MR occurred in 43 (30.5%) patients. Age, race, gender, initial organ function, and dialysis vintage were not associated with MR. Diabetic recipients, those who received basiliximab induction, those with acute rejection, and those with unplanned reoperations were at increased risk for MR. Infection was the most common reason for initial readmission in patients with MR (23.3%). One-year patient survival and death-censored graft survival were reduced for patients with MR. MRs are required for 30 per cent of kidney transplant recipients, primarily because of infection and immunologic causes. Recipients with diabetes and those who have acute rejection are at greatest risk.

Pilot study protocol of a mHealth self-management intervention for family members of pediatric transplant recipients

Solid-organ transplantation is the treatment of choice for end-stage organ failure. Parents of pediatric transplant recipients who reported a lack of readiness for discharge had more difficulty coping and managing their child's medically complex care at home. In this paper, we describe the protocol for the pilot study of a mHealth intervention (myFAMI). The myFAMI intervention is based on the Individual and Family Self-Management Theory and focuses on family self-management of pediatric transplant recipients at home. The purpose of the pilot study is to test the feasibility of the myFAMI intervention with family members of pediatric transplant recipients and to test the preliminary efficacy on postdischarge coping through a randomized controlled trial. The sample will include 40 family units, 20 in each arm of the study, from three pediatric transplant centers in the United States. Results from this study may advance nursing science by providing insight for the use of mHealth to facilitate patient/family-nurse communication and family self-management behaviors for family members of pediatric transplant recipients.

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department

OBJECTIVE

To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated factors including natural language elements to predict the medical imaging utilization at pediatric ED.

METHODS

Pediatric patients' data from the 2012-2016 United States National Hospital Ambulatory Medical Care Survey was included to build the models to predict the use of imaging in children presenting to the ED. Multivariable logistic regression models were built with structured variables such as temperature, heart rate, age, and unstructured variables such as reason for visit, free text nursing notes and combined data available at triage. NLP techniques were used to extract information from the unstructured data.

RESULTS

Of the 27,665 pediatric ED visits included in the study, 8394 (30.3%) received medical imaging in the ED, including 6922 (25.0%) who had an X-ray and 1367 (4.9%) who had a computed tomography (CT) scan. In the predictive model including only structured variables, the c-statistic was 0.71 (95% CI: 0.70-0.71) for any imaging use, 0.69 (95% CI: 0.68-0.70) for X-ray, and 0.77 (95% CI: 0.76-0.78) for CT. Models including only unstructured information had c-statistics of 0.81 (95% CI: 0.81-0.82) for any imaging use, 0.82 (95% CI: 0.82-0.83) for X-ray, and 0.85 (95% CI: 0.83-0.86) for CT scans. When both structured variables and free text variables were included, the c-statistics reached 0.82 (95% CI: 0.82-0.83) for any imaging use, 0.83 (95% CI: 0.83-0.84) for X-ray, and 0.87 (95% CI: 0.86-0.88) for CT.

CONCLUSIONS

Both CT and X-rays are commonly used in the pediatric ED with one third of the visits receiving at least one. Patients' socioeconomic, demographic and clinical factors presented at ED triage period were associated with the medical imaging utilization. Predictive models combining structured and unstructured variables available at triage performed better than models using structured or unstructured variables alone, suggesting the potential for use of NLP in determining resource utilization.

Socioeconomic Status and Kidney Transplant Outcomes in a Universal Healthcare System: A Population-based Cohort Study

BACKGROUND

Conflicting evidence exists regarding the relationship between socioeconomic status (SES) and outcomes after kidney transplantation.

METHODS

We conducted a population-based cohort study in a publicly funded healthcare system using linked administrative healthcare databases from Ontario, Canada to assess the relationship between SES and total graft failure (ie, return to chronic dialysis, preemptive retransplantation, or death) in individuals who received their first kidney transplant between 2004 and 2014. Secondary outcomes included death-censored graft failure, death with a functioning graft, all-cause mortality, and all-cause hospitalization (post hoc outcome).

RESULTS

Four thousand four hundred-fourteen kidney transplant recipients were included (median age, 53 years; 36.5% female), and the median (25th, 75th percentile) follow-up was 4.3 (2.1-7.1) years. In an unadjusted Cox proportional hazards model, each CAD $10000 increase in neighborhood median income was associated with an 8% decline in the rate of total graft failure (hazard ratio [HR], 0.92; 95% confidence interval [CI], 0.87-0.97). After adjusting for recipient, donor, and transplant characteristics, SES was not significantly associated with total or death-censored graft failure. However, each CAD $10000 increase in neighborhood median income remained associated with a decline in the rate of death with a functioning graft (adjusted (a)HR, 0.91; 95% CI, 0.83-0.98), all-cause mortality (aHR, 0.92; 95% CI, 0.86-0.99), and all-cause hospitalization (aHR, 0.95; 95% CI, 0.92-0.98).

CONCLUSIONS

In conclusion, in a universal healthcare system, SES may not adversely influence graft health, but SES gradients may negatively impact other kidney transplant outcomes and could be used to identify patients at increased risk of death or hospitalization.

Outcomes in patients with solid organ transplants undergoing cardiac surgery

OBJECTIVE

Long-term outcomes after cardiac surgery in solid organ transplant recipients are limited in the contemporary literature. The objective of this study is to evaluate postoperative outcomes in these patients, including variables associated with mortality and readmissions.

METHODS

All adults undergoing isolated coronary artery bypass grafting, isolated valve, or coronary artery bypass grafting + valve cardiac surgical procedures from 2011 to 2018 were included in this study. Patients with solid organ transplants undergoing cardiac surgery were studied. Primary outcomes included operative (30-day) and 5-year mortality.

RESULTS

A total of 11,190 patients underwent isolated coronary artery bypass grafting, isolated valve, or coronary artery bypass grafting + valve operations at our institution from 2011 to 2018. Of these, 129 patients (1%) had solid organ transplants and underwent isolated coronary artery bypass grafting (n = 84), isolated valve (n = 30), or coronary artery bypass grafting + valve (n = 15). Type of organ transplant included 84 patients (65%) with kidney, 27 patients (21%) with liver, 9 patients (7%) with heart, and 9 patients (7%) with lung transplants. The median Society of Thoracic Surgeons Predicted Risk Of Mortality for the cohort was 2.73 (Q1-Q3: 1.67-6.33). Three patients (2%) had an operative (30-day) mortality. Significant variables associated with 5-year mortality on multivariable Cox regression analysis included chronic obstructive pulmonary disease (hazard ratio, 2.44; 1.01-5.90; P = .048) and congestive heart failure (hazard ratio, 4.45; 1.81-10.9; P = .001). Significant variables associated with 5-year readmissions included chronic obstructive pulmonary disease, dialysis dependence, and concomittant valve surgery with coronary artery bypass grafting. Five-year readmission rate was 88%, and patients with valve operations (± coronary artery bypass grafting) had significantly lower (P = .009) freedom from readmission (6%).

CONCLUSIONS

Cardiac surgery can be performed with low operative mortality and good long-term survival in patients with solid organ transplants. Five-year hospital readmissions are common, with significantly more readmissions in patients who had valve procedures.

Evaluation of the Renal Transplant Recipient in the Emergency Department

Renal transplants are becoming more and more frequent in the United States and worldwide. Studies demonstrate that these patients inevitably end up visiting an emergency department. In addition to typical medical and surgical problems encountered in the general population, this group of patients has unique problems arising from their immunocompromised state and also due to side effects of the medications required. This article discusses these risks and management decisions that the emergency department physician should be aware of in order to prevent adverse outcomes for the patient and transplanted kidney.

Association Between Weight Loss Before Deceased Donor Kidney Transplantation and Posttransplantation Outcomes

RATIONALE & OBJECTIVE

There is debate on whether weight loss, a hallmark of frailty, signals higher risk for adverse outcomes among recipients of deceased donor kidney transplantation (DDKT).

STUDY DESIGN

Retrospective cohort study.

SETTING & PARTICIPANTS

Using national Organ Procurement and Transplantation Network data, we included all DDKT recipients in the United States between December 4, 2004, and December 3, 2014, who were adults (aged ≥ 18 years) when listed for DDKT.

EXPOSURES

Relative pre-DDKT weight change as a continuous predictor and categorized as <5% weight change from listing to DDKT, ≥5% to <10% weight loss, ≥10% weight loss, ≥5% to <10% weight gain, and ≥10% weight gain.

OUTCOMES

We examined 3 post-DDKT outcomes: (1) transplant hospitalization length of stay (LOS) in days, (2) all-cause graft failure, and (3) mortality.

ANALYTIC APPROACH

Unadjusted fractional polynomial methods, multivariable log-gamma models, and multivariable Cox proportional hazards models.

RESULTS

Among 94,465 recipients of DDKT, median pre-DDKT weight change was 0 (interquartile range, -3.5 to +3.9) kg. There were nonlinear unadjusted associations between relative pre-DDKT weight loss and longer transplant hospitalization LOS, higher all-cause graft loss, and higher mortality. Compared with recipients with <5% pre-DDKT weight change (n = 49,366; 52%), recipients who lost ≥10% of their listing weight (n = 10,614; 11%) had 0.66 (95% CI, 0.23-1.09) days longer average transplant hospitalization LOS (P = 0.003), 1.11-fold higher graft loss (adjusted HR [aHR], 1.11; 95% CI, 1.06-1.17; P < 0.001), and 1.18-fold higher mortality (aHR, 1.18; 95% CI, 1.11-1.25; P < 0.001) independent of recipient, donor, and transplant factors. Pre-DDKT dialysis exposure, listing body mass index category, and waiting time modified the association of pre-DDKT weight change with hospital LOS (interaction P < 0.10), but not with all-cause graft loss and mortality.

LIMITATIONS

Unmeasured confounders and inability to identify volitional weight change. Also, the higher significance level set to increase the power of detecting interactions with the fixed sample size may have resulted in increased risk for type 1 error.

CONCLUSIONS

DDKT recipients with ≥10% pre-DDKT weight loss are at increased risk for adverse outcomes and may benefit from augmented support post-DDKT.

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.

Perceptions, Barriers, and Experiences With Successful Aging Before and After Kidney Transplantation: A Focus Group Study

BACKGROUND

End-stage kidney disease (ESKD) patients are living longer, often into older age, and commonly pursue kidney transplantation. Successful aging, a multidimensional construct of physical and social wellbeing, has been expanded and adapted for patients with chronic disease. However, perceptions of, barriers to, and experiences with successful aging among adults with ESKD are unclear and likely differ based on whether they have received a kidney transplant.

METHODS

Ten focus groups were held with 39 total ESKD patients aged ≥50 years (19 transplant candidates, 20 transplant recipients). Transcriptions were analyzed thematically by 2 independent coders using an inductive, constant comparative approach.

RESULTS

The mean age was 64.8 (SD = 7.5); 51% were African American and 64% were males. Six themes were identified: familiarity with successful aging, perceptions of successful aging after ESKD diagnosis, barriers to successful aging, experiences with successful aging among transplant candidates, experiences with successful aging among transplant recipients, and suggested interventions. While all participants sought to achieve successful aging while living with ESKD, experiences with successful aging differed between candidates and recipients. Candidates struggled with the limitations of dialysis; some viewed transplantation as an opportunity to age successfully, while others were resigned to the drawbacks of dialysis. In contrast, transplant recipients were optimistic about their ability to age successfully, believing their transplant facilitated successful aging. Participants believed support groups for adults with ESKD and more thoughtful health care for aging adults would promote successful aging.

CONCLUSIONS

Adults with ESKD may benefit from discussions with their clinicians and caregivers about goals, barriers, and strategies regarding successful aging.