Early hospital readmissions post-kidney transplantation are associated with inferior clinical outcomes

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.

Renal Transplantation in the Elderly: Are They All the Same? A Multicenter, Comorbidity-Based Study

INTRODUCTION

The age for kidney transplantation (KT) is no longer a limitation and several studies have shown benefits in the survival of elderly patients. The aim of this study was to examine the relationship of the baseline Charlson comorbidity index (CCI) score to morbidity and mortality after transplantation.

METHODS

In this multicentric observational retrospective cohort study, we included patients older than 60 years admitted on the waiting list (WL) for deceased donor KT from January 01, 2006, to December 31, 2016. The CCI score was calculated for each patient at inclusion on the WL.

RESULTS

Data for analysis were available of 387 patients. The patients were divided in tertiles of CCI: group 1 (CCI: 1-2) n = 117, group 2 (CCI: 3-4) n = 158, and group 3 (CCI: ≥5) n = 112. Patient survival was significantly different between CCI groups at 1, 3, and 5 years, respectively: 90%, 88%, and 84% for group 1, 88%, 80%, and 72% for group 2, and 87%, 75%, and 63% for group 3 (p < 0.0001). Variables associated with mortality were CCI score (p < 0.0001), HLA mismatch (p = 0.014), length of hospital stay (p < 0.0001), surgical complications (p = 0.048).

CONCLUSION

Individualized strategies to modify these variables may improve patient's morbidity and mortality after KT.

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.

Association of DGF and Early Readmissions on Outcomes Following Kidney Transplantation

Concerns regarding outcomes and early resource utilization are potential deterrents to broader use of kidneys at risk for delayed graft function (DGF). We assessed outcomes specific to kidneys with DGF that required early readmission following transplant. Three groups were identified: 1) recipients with DGF not requiring readmission, 2) recipients with DGF having an isolated readmission, and 3) recipients with DGF requiring ≥2 readmissions. Most recipients either required a single readmission (26.8%, n = 247) or no readmission (56.1%, n = 517); 17.1% (n = 158), had ≥2 readmissions. Recipients requiring ≥2 readmissions were likely to be diabetic (53.8%, p = 0.04) and have longer dialysis vintage (p = 0.01). Duration of DGF was longer with increasing number of readmissions (p < 0.001). There were no differences in patient survival for those with DGF and 0, 1 and ≥2 readmissions (p = 0.13). Graft survival, however, was lower for those with ≥2 readmissions (p < 0.0001). This remained true when accounting for death-censored graft loss (p = 0.0012). Additional subgroup analysis was performed on mate kidneys with and without DGF and mate kidneys, both with DGF, with and without readmissions. For these subgroups, there were no differences in patient or graft survival. As a whole, patients with DGF have excellent outcomes, however, patients with DGF requiring ≥2 readmissions have lower graft survival. A better understanding of recipient variables contributing to multiple readmissions may allow for improvements in the utilization of DGF at-risk kidneys.

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.

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.

Higher Frequency of Acute Occupational Therapy Services Is Associated With Reduced Hospital Readmissions

IMPORTANCE

Hospital readmissions are associated with poor patient outcomes, including higher risk for mortality, nutritional concerns, deconditioning, and higher costs.

OBJECTIVE

To evaluate how acute occupational therapy service delivery factors affect readmission risk.

DESIGN

Cross-sectional, retrospective study.

SETTING

Single academic medical center.

PARTICIPANTS

Medicare inpatients with a diagnosis included in the Hospital Readmissions Reduction Program (HRRP; N = 17,618). Data were collected from medical records at a large urban hospital in southeastern Wisconsin. Outcomes and Measures: Logistic regression models were estimated to examine the association between acute occupational therapy service delivery factors and odds of readmission. In addition, the types of acute occupational therapy services for readmitted versus not-readmitted patients were compared.

RESULTS

Patients had significantly higher odds of readmission if they received occupational therapy services while hospitalized (odds ratio [OR] = 1.18, 95% confidence interval [CI] [1.07, 1.31]). However, patshients who received acute occupational therapy services had significantly lower odds of readmission if they received a higher frequency (OR = 0.99, 95% CI [0.99,1.00]) of acute occupational therapy services. A significantly higher proportion of patients who were not readmitted, compared with patients who were readmitted, received activities of daily living (ADL) or self-care training (p < .01).

CONCLUSIONS AND RELEVANCE

For patients with HRRP-qualifying diagnoses who received acute occupational therapy services, higher frequency of acute occupational therapy services was linked with lower odds of readmission. Readmitted patients were less likely to have received ADL or self-care training while hospitalized. What This Article Adds: Identifying factors of acute occupational therapy services that reduce the odds of readmission for Medicare patients may help to improve patient outcomes and further define occupational therapy's role in the U.S. quality-focused health care system.

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.

Re-hospitalization after pediatric kidney transplant: A single-center study

BACKGROUND

Little data exist on re-hospitalization rates in pediatric kidney recipients (KTx) particularly with the evolution of transplant immunosuppression.

METHODS

In a single-center, retrospective study of pediatric KTx between 2006 and 2016, we assessed re-hospitalization after KTx admission, stratified by whether the re-admit was early (<30 days post-KTx discharge) or late (>30 days), and compared two different immunosuppression eras (one with and one without steroids).

RESULTS

Of 197 KTx, 156 (79%) patients were re-hospitalized in 1st year, 85 (56%) within 30 days of discharge (total 490 1st year re-hospitalizations). Younger age was associated with early and late re-hospitalizations. African American race was associated with early re-hospitalizations. Of the 123 and 74 discharged on steroid-avoidance (maintenance immunosuppression included MMF in 95%; FK in 50%; CSA in 50%) and steroid-inclusive (AZA in 66%; MMF in 34%; FK in 30%; CSA in 70%), re-hospitalization rates, timing post-transplant, length, and number were not significantly different (P .38; .1; .56; .11). Admission diagnoses analysis demonstrated that steroid-avoidance recipients had anemia/leucopenia/thrombocytopenia, significantly more often, as one of their admission diagnoses (16% vs 4%; P < .001) and had a rejection diagnosis significantly less often (6% vs 18%; P < .001). Infection diagnoses were not statistically different between groups. Re-hospitalization, early or late, did not predict worse graft/ patient survival but predicted further hospitalizations.

CONCLUSIONS

Re-hospitalization is common after pediatric transplant discharge and predicts further hospitalization regardless of discharge on or off steroids.

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.

Does Distance to Transplant Center Affect Post Kidney Transplant Readmission Rates?

Many transplant recipients travel long distances to their transplant center with challenging access to their transplant team. As such, many centers keep recipients near to the center for a period immediately after discharge from the transplant admission. Thus far, the correlation between distance to the transplant center, readmission, and outcomes has not been described. The aim of this study was to examine this relationship. Patients undergoing deceased donor kidney transplant at a single center over a three-year period were analyzed via retrospective chart review for factors associated with distance to the transplant center and readmission. P values < 0.05 were considered significant. Of 141 patients, the overall 90-day readmission rate was 38.3 per cent, and rates were similar between nonlocal and local recipients. Nonlocal were more likely whites (66.1% vs 45.6%; P = 0.032) and from rural areas (56.5% vs 13.9%; P < 0.001). Length of stay was similar between groups, as were rates of delayed graft function. Non–death-censored graft survival was higher at one and three years for nonlocal patients (96.8% and 96.8% vs 89.7% and 78.4%; P = 0.016). This remained significant after adjusting for baseline differences between the groups (hazard ratio (HR) for graft failure = 0.195, 95%, P = 0.046). Patients who live remotely from the transplant center do not experience higher rates of readmission or worsened outcomes, and thus may be managed safely at home. Interestingly, graft survival is improved in nonlocal patients. This may reflect the urban nature of the area surrounding our transplant center, but warrants further study for conclusions to be reached.

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.

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.

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.

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.

Early hospital readmissions after ABO- or HLA- incompatible living donor kidney transplantation

Early hospital readmission (EHR) after kidney transplantation (KT) is associated with adverse outcomes and significant healthcare costs. Despite survival benefits, ABO- and HLA-incompatible (ABOi and HLAi) KTs require desensitization and potent immunosuppression that increase risk of EHR. However, little data exist regarding EHR after incompatible KT. We defined EHR as admission for any reason within 30 days of discharge from the index hospitalization. Patients who underwent living donor KT from 2010–2017 were classified into one of three groups (control, ABOi KT, or HLAi KT). Our study included 732 patients, 96 (13.1%) of who experienced EHR. HLAi KT patients had a significantly higher incidence of EHR than other groups (26.6%; P < 0.001). In addition, HLAi KT (HR, 2.26; 95% CI, 1.35–3.77; P = 0.002) and advanced age (≥60 years) (HR, 1.93; 95% CI, 1.20–3.12; P = 0.007) were independent risk factors for EHR. Patients with EHR showed 1.5 times and 3 times greater risk of late hospital readmission and death-censored graft loss, respectively, and consistently exhibited inferior renal function compared to those without EHR, regardless of immunologic incompatibilities. We recommend that KT recipients experiencing EHR or its risk factors be managed with extreme care due to their increased susceptibility to adverse outcomes.

Outcomes and challenges of a kidney transplant programme at Groote Schuur Hospital, Cape Town: A South African perspective

Introduction

Access to dialysis and transplantation in the developing world remains limited. Therefore, optimising renal allograft survival is essential. This study aimed to evaluate clinical outcomes and identify poor prognostic factors in the renal transplant programme at Groote Schuur Hospital [GSH], Cape Town.     

Method

Data were collected on all patients who underwent a kidney transplant at GSH from 1st July 2010 to the 30 June 2015. Analyses were performed to assess baseline characteristics, graft and patient survival, as well as predictors of poor outcome.    

Results

198 patients were transplanted. The mean age was 38 +/- 10.5 years, 127 (64.1%) were male, and 86 (43.4%) were of African ethnicity. Deceased donor organs were used for 130 (66.7%) patients and living donors for 65 (33.3%). There were > 5 HLA mismatches in 58.9% of transplants. Sepsis was the commonest cause of death and delayed graft function [DGF] occurred in 41 (21.4%) recipients. Patient survival was 90.4% at 1 year and 83.1% at 5 years. Graft survival was 89.4% at 1 year and 80.0% at 5 years. DGF (HR 2.83 (1.12–7.19), p value = 0.028) and recipient age > 40 years (HR 3.12 (1.26–7.77), p value = 0.014) were predictors of death.

Conclusion

Despite the high infectious burden, stratified immunosuppression and limited tissue typing this study reports encouraging results from a resource constrained transplant programme in South Africa. Renal transplantation is critical to improve access to treatment of end stage kidney disease where access to dialysis is limited.

A Retrospective Cohort Study on Rehospitalization following Expanded Criteria Donor Kidney Transplantation

Background

Expanded criteria donor (ECD) kidneys are commonly used but are associated with increased graft failure. Graft failure is in turn related to rehospitalization within thirty days post transplant. Our goal was to determine whether ECD kidneys independently lead to rehospitalization within 30 days, 1 year, and 2 years after transplant.

Methods

All adult first-time recipients of deceased donor kidneys transplanted from 2003-2012 at our center were reviewed. Models included demographics, medical comorbidities, center for disease control high-risk kidney, ECD kidney, ischemia times, cause of renal failure, immunosuppressive regimen, positive psychiatric screening, alcoholism, surgeon, year the transplant was performed, years on dialysis before transplant, and the number of inpatient hospitalizations within 6 months prior to transplant. We conducted Andersen-Gill modeling and propensity score matching followed by logistic regression. We also used multivariable linear regression to predict average length of stay during rehospitalization.

Results

More ECD patients had a rehospitalization at 1 year (70.3% versus 59%, log-rank test p=0.014). Thirty-day and 2-year time marks were not significant. Andersen-Gill models predicting successive hospitalizations yielded HR of 1.42 (p=0.002) and 1.32 (p=0.015) for ECD patients at 1 and 2 years of after transplantation, respectively. Propensity score matching and logistic regression showed a significant relative risk of 1.630 at one year (p=0.033) and 1.313 at two years (p=0.268). There was no significant association between ECD and subsequent lengths of hospital stay.

Conclusion

Receiving an ECD kidney is independently associated with multiple readmissions within 2 years of transplant but unrelated to length of stay.

[Strategic plan for reduction of hospital stay in renal transplantation]

Since January 2015 we have carried out a multiple-intervention strategic plan to reduce hospital stay in renal transplant recipients. The main objective of this study is to compare results of renal transplantation before and after putting into effect this plan in terms of graft and patient survival, readmissions and incidence of acute rejection during the first year post transplantation. In this retrospective analysis we included all patients 18 years of age or older who were transplanted at our institution. The strategic plan resulted in a significant reduction of hospital stay of renal recipients from 13.5 days in the pre-plan group (n=97) to 4.6 days in the post-plan group (n=62; p≤0.0001). The incidence of acute rejection during the first year was similar (pre-plan group=14.4% vs. post-plan group=16% [p=0.77]) as it was graft survival (88% vs. 90% [p=0.71]) and patient survival (95% vs. 98% [p=0.37]), respectively. The multiple-intervention strategic plan has significantly reduced the hospital stay of patients after renal transplantation without affecting graft or patient survival, which are comparable to those internationally published, and without jeopardizing patient's safety.

Is the Clinical Outcome Good or Bad in Patients Hospitalized Within 1 Year After Kidney Transplantation?

BACKGROUND

Although the hospitalization rate at early period of kidney transplantation (KT) is still high, the association between the hospitalization within 1 year after KT and graft survival is unclear. We investigated the incidence and causes of hospitalization and clinical outcome of the patients hospitalized within 1 year after KT.

METHODS

We retrospectively analyzed 174 KT recipients (KTRs) hospitalized within 1 year after KT between 2013 and 2015.

RESULTS

Among them, 84 (48%) KTRs were admitted within 1 year after KT, and the number of hospitalizations was 116. The mean time from KT to first hospitalization was 4.2 months. Seventy-eight percent of the patients were hospitalized for medical causes and 22% for surgical causes. The most common cause was cytomegalovirus infection (CMV) (23.3%), followed by acute rejection (11.2%) and urinary tract infection (10.3%). Recipients and donors in the hospitalized group were significantly older than the nonhospitalized group. The proportions of deceased donor KT, acute rejection, more than 50% panel-reactive antibody, and positive donor-specific antibody were significantly higher in the hospitalized group than in the nonhospitalized group. Graft and patient survivals were lower in the hospitalized group than in the nonhospitalized group. Deceased donor KT and acute rejection were independent risk factors for hospitalization.

CONCLUSION

The incidence of KTRs hospitalized within 1 year after KT was high. Most causes of hospitalization were CMV infection, acute rejection, and urinary tract infection. Therefore, the immunosuppression status of these patients should be closely monitored to reduce the hospitalization rate.

Emergency department use among kidney transplant recipients in the United States

Patients with end-stage renal disease use the emergency department (ED) at a 6-fold higher rate than do other US adults. No national studies have described ED use rates among kidney transplant (KTx) recipients, and the factors associated with higher ED use. We examined a cohort of 132 725 adult KTx recipients in the United States Renal Data System (2005-2013). Data on ED visits, hospitalization, and outpatient nephrology visits were obtained from Medicare claims databases. Nearly half (46.1%) of KTx recipients had at least one ED visit (1.61 ED visits/patient-year [PY]), and 39.7% of ED visits resulted in hospitalization in the first year posttransplantation. ED visit rate was high in the first 30 days (5.26 visits/PY) but declined substantially thereafter (1.81 visits/PY in months 1-3; 1.13 visits/PY in months 3-12 posttransplantation). ED visit rates were higher in the first 30 days versus rates for dialysis patients but less than half the rate thereafter. Female sex, public insurance, medical comorbidities, longer pretransplantation dialysis vintage, and delayed graft function were associated with higher ED use in the first year post-KTx. Policies and strategies addressing potentially preventable ED visits should be promoted to help improve patient care and increase efficient use of ED resources.

Impact of Early Hospital Readmissions After Kidney Transplantation on Graft Function

Early hospital readmissions are common after kidney transplantation. This single-center retrospective study investigated the relationship between early hospital readmissions and clinical outcomes. All adult patients receiving a kidney transplant at this center between March 2009 and June 2015 were included. The early hospital readmissions within the first 30 days were numbered, and the diagnosis was ascertained. The patients were divided into None and Readmission groups. Clinical outcomes and patient- and death-censored graft survival were compared. Among the 103 patients included in the study, 32 (31.1%) had 1 or more readmissions within 30 days. Surgical complications, electrolyte imbalance, and acute rejection were common causes of readmission. No differences were observed in baseline characteristics between the two groups. Patients with early readmissions exhibited low renal function at 3, 6, and 12 months postoperatively (P = .002, .020, and .013, respectively). No difference in graft function was found 12 months after transplantation between the None and Readmission groups. Five-year graft and patient survival also showed no difference between the two groups (P = .424 and .442, respectively). In conclusion, early readmission after kidney transplantation affected lower graft function until 1 year after kidney transplantation. However, the long-term effect on graft function is limited in this study.

Two-year management after renal transplantation in 2013 in France: Input from the French national health system database

The objective of this study was to describe the management of patients undergoing renal transplantation in 2013 and over the following two years on the basis of healthcare consumption data. The National Health Insurance Information System was used to identify 1876 general scheme beneficiaries undergoing a first isolated renal transplantation (median age: 53 years; men 63%). Overall, 1.2% of patients died during the transplantation hospital stay (>65 years 3.3%) and 87% of patients had a functional graft at 2 years. Thirty-three percent of patients were readmitted to hospital for 1 day or longer during the first month, 73% the first year and 55% the second year. At least 10% of patients were hospitalised for antirejection treatment during the first quarter after renal transplantation, 16% the first year and 9% the second year. The first year, 32% of patients were hospitalised for renal disease (12% the second year), 14% were hospitalised for cardiovascular disease (9% the second year), 13% for infectious disease (5% the second year) and 2% for a malignant tumour (2% the second year). Almost 80% of patients consulted their general practitioner each year (almost 50% consulted every quarter). During the second year, 83% of patients were taking antihypertensives, 45% lipid-lowering drugs, 26% antidiabetic drugs, 77% tacrolimus, 18% ciclosporin, 88% mycophenolic acid and 69% corticosteroids. This study highlights the important contribution of healthcare consumption data to a better understanding of the modalities of management of renal transplant recipients in France, allowing improvement of this management in line with guidelines.

Early Rehospitalization Post-Kidney Transplant Due to Infectious Complications: Can We Predict the Patients at Risk?

INTRODUCTION

Rehospitalization early post-kidney transplant is common and has a negative impact in morbidity, graft survival, and health costs. Infection is one the most common causes, and identifying the risk factors for early readmission due to infectious complications may guide a preventive program and improve outcome. The aim of this study was to evaluate the incidence, characterize the population, and identify the risk factors associated with early readmission for infectious complications post-kidney transplantation.

METHODS

We performed a retrospective cohort study of all the kidney transplants performed during 2015. The primary outcome was readmission in the first 3 months post-transplant due to infectious causes defined by clinical and laboratory parameters.

RESULTS

We evaluated 141 kidney transplants; 71% of subjects were men, with an overall mean age of 50.8 ± 15.4 years. Prior to transplant, 98% of the patients were dialysis dependent and 2% underwent pre-emptive living donor kidney transplant. The global readmission rate was 49%, of which 65% were for infectious complications. The most frequent infection was urinary tract infection (n = 28, 62%) and the most common agent detected by blood and urine cultures was Klebsiella pneumonia (n = 18, 40%). The risk factors significantly associated with readmission were higher body mass index (P = .03), diabetes mellitus (P = .02), older donor (P = .007), and longer cold ischemia time (P = .04). There were 3 graft losses, but none due to infectious complications.

CONCLUSION

There was a high incidence of early rehospitalization due to infectious complications, especially urinary tract infections to nosocomial agents. The risk factors identified were similar to other series.

Decreasing readmissions by focusing on complications and underlying reasons

BACKGROUND

To analyze demographics and outcomes of patients focusing on 30-day readmission status and identify procedure-specific risk factors.

METHODS

Patients undergoing abdominal colorectal surgery (2011-2013) were identified Demographics and outcomes including in-hospital complications were compared based on readmission status.

RESULTS

A total of 6637 patients were identified with a mean age of 51.2(±17.1) years. Seven hundred and seventy five(11.7%) patients were readmitted at least once within 30-day. The most common index procedures related to readmission were stoma closure (n = 127/775, 16.4%) and total colectomy (n = 105/775, 13.6%). Readmitted patients had longer length of index hospital stay (LOS)(8.2 ± 5.9 vs 7.9 ± 6.9 days,p < 0.001) and operative time(167 ± 104 vs 144 ± 95 min, p < 0.001), higher intraoperative(2% vs 1%,p = 0.04) and in-hospital complication rates(36% vs 28%,p < 0.001). Main reasons for readmissions were gastrointestinal-related causes(n = 222, 29%), small bowel obstruction (n = 133,17%), wound-related complications(n = 108,14%), and dehydration(n = 93,12%). Median readmission LOS was 4(1-71)days and 54%(n = 407) of readmissions occurred within 7 days of discharge.

CONCLUSION

Increased postoperative complications may be the main preventable underlying reason for increased risk of hospital readmission after colorectal surgery. Preventive measures to decrease complications and actions to identify high risk patients for complications would help to reduce readmissions.

Early Readmission After Kidney Transplantation: Examination of Discharge-Level Factors

BACKGROUND

Early rehospitalization after kidney transplantation (KTx) is common and is considered a quality metric. Recipient and donor risk factors for early readmission after KTx are well studied. Little data exist on discharge-level factors associated with readmission.

METHODS

We performed a single-center, retrospective cohort study between 2011 and 2015 of adult KTx recipients to examine readmission indication, risk factors, and opportunities for reduction.

RESULTS

Of 462 KTxs, 145 (31.4%) were readmitted within 30 days of discharge. The primary reason for readmission was surgery-site specific in 30 cases (20.7%). Of 115 recipients with nonsurgical indications for readmission 25 (21.7%) were related to infection, 24 (20.9%) graft dysfunction, 25 (21.7%) gastrointestinal, 25 (21.7%) metabolic, and 16 (13.9%) other reasons. On multivariate analysis significant independent predictors of early readmission were electrolyte abnormalities on the day of discharge (odds ratio [OR], 1.77; 95% confidence interval [95% CI], 1.17-2.69), 3 or more comorbidities (OR, 2.01; 95% CI, 1.04-3.86), delayed graft function at the time of discharge (OR, 1.65; 95% CI, 1.00-2.70), and post-KTx hospitalization complication (OR, 1.70; 95% CI, 1.10-2.61). Among 11.7% of patients, readmission may have been attenuated by addressing the medical issue before discharge from index hospitalization. In 28.3% of patients, readmission rates may have been reduced with continued management as an outpatient or provision of observational or same-day diagnostic resources.

CONCLUSIONS

Specific discharge level factors correlate with readmission irrespective of comorbidities and transplant complications. These findings may have important implications on discharge practice by aiding to identify which KTx recipients could be targeted for enhanced care transitions. Overall, potential opportunities for readmission reduction exist on multiple process levels.

Early Hospital Readmissions After Transplantation: Burden, Causes, and Consequences

BACKGROUND

Solid organ transplantation is the preferred treatment for patients with end-stage organ failure. Although much progress has been made over the past decade, some patients still require early readmission after their initial hospital discharge. Early hospital readmission is an important metric for health care quality. It is often measured in nontransplant medical and surgical conditions but has only recently been applied to organ transplantation.

METHODS

We performed a structured MEDLINE search to retrieve, review, and summarize original studies on the incidence, risk factors, outcomes, and prevention of early hospital readmissions after kidney, liver, and kidney-pancreas transplantation. Early hospital readmission was defined as readmission to hospital within 30 days of discharge from the transplant hospitalization.

RESULTS

The risk of early readmission varies by organ type, (highest in liver transplants and lowest in kidney transplants). Causes for early hospital readmission are most commonly due to surgical, immunologic, or infectious complications. Risk factors associated with early hospital readmission often reflect pretransplant comorbidity, and many of these factors may not be modifiable. Early hospital readmission is also associated with decreased graft and patient survival.

CONCLUSIONS

Early hospital readmission after transplantation is common and associated with adverse outcomes. The potential for preventing early hospital readmissions and the impact on patient outcomes remain unclear. Current evidence suggests that some, but not all, early hospital readmissions after transplantation may be prevented.

Predictors and outcomes of unplanned early rehospitalization in the first year following lung transplantation

Unplanned early rehospitalization (UER), defined as an unscheduled admission within 30 days of a hospital discharge, is associated with graft loss and recipient mortality in some solid organ transplants but has not been investigated in lung transplant. In this retrospective study, we collected socio-demographic and clinical factors to determine predictors and outcomes of UER in the first year following lung transplantation. There were 193 patients who underwent lung transplantation and survived to discharge during the 7.9-year study period. There were 116 (60.1%) patients with at least one UER. Infections (32.8%) and post-surgical complications (11.8%) were the most common reasons for UER. On multivariate analysis, the strongest predictor of having an UER was discharge to a long-term acute care facility (odds ratio: 3.01, 95% confidence interval [CI] 1.46-6.20; P=.003). Patients with any UER in the first year following transplantation had worse adjusted survival (hazard ratio: 1.89, 95% CI 1.02-3.50; P=.04). It is unclear, however, to what extent UERs reflect preventable outcomes. Further large-scale, prospective research is needed to identify the extent to which certain types of UER are modifiable and to define patients at high-risk for preventable UER.

Emergency Department Visits after Kidney Transplantation

BACKGROUND AND OBJECTIVES

In 2011, there were approximately 131 million visits to an emergency department in the United States. Emergency department visits have increased over time, far outpacing growth of the general population. There is a paucity of data evaluating emergency department visits among kidney transplant recipients. We sought to evaluate the incidence and risk factors for emergency department visits after initial hospital discharge after transplantation in the United States.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We identified 10,533 kidney transplant recipients from California, New York, and Florida between 2009 and 2012 using the State Inpatient and Emergency Department Databases included in the Healthcare Cost and Utilization Project. We used multivariable Poisson and Cox proportional hazard models to evaluate adjusted incidence rates and time to emergency department visits after transplantation.

RESULTS

There were 17,575 emergency department visits over 13,845 follow-up years (overall rate =126.9/100 patient-years; 95% confidence interval, 125.1 to 128.8). The cumulative incidences of emergency department visits at 1, 12, and 24 months were 12%, 40%, and 57%, respectively, with median time =19 months; 48% of emergency department visits led to hospital admission. Risk factors for higher emergency department rates included younger age, women, black and Hispanic race/ethnicity, public insurance, depression, diabetes, peripheral vascular disease, and emergency department use before transplant. There was wide variation in emergency department visits by individual transplant center (10th percentile =70.0/100 patient-years; median =124.6/100 patient-years; and 90th percentile =187.4/100 patient-years).

CONCLUSIONS

The majority of kidney transplant recipients will visit an emergency department in the first 2 years post-transplantation, with significant variation by patient characteristics and individual centers. As such, coordination of care through the emergency department is a critical component of post-transplant management, and specific acumen of transplant-related care is needed among emergency department providers. Additional research assessing best processes of care for post-transplant management and health care expenditures and outcomes associated with emergency department visits for transplant recipients are warranted.