Heilman, Raymond

Background. Improving both patient and graft survival after kidney transplantation are major unmet needs. The goal of this study was to assess risk factors for specific causes of graft loss to determine to what extent patients who develop either death with a functioning graft (DWFG) or graft failure (GF) have similar baseline risk factors for graft loss. Methods. We retrospectively studied all solitary renal transplants performed between January 1, 2006, and December 31, 2018, at 3 centers and determined the specific causes of DWFG and GF. We examined outcomes in different subgroups using competing risk estimates and cause-specific Cox models. Results. Of the 5752 kidney transplants, graft loss occurred in 21.6% (1244) patients, including 12.0% (691) DWFG and 9.6% (553) GF. DWFG was most commonly due to malignancy (20.0%), infection (19.7%), cardiac disease (12.6%) with risk factors of older age and pretransplant dialysis, and diabetes as the cause of renal failure. For GF, alloimmunity (38.7%), glomerular diseases (18.6%), and tubular injury (13.9%) were the major causes. Competing risk incidence models identified diabetes and older recipients with higher rates of both DWFG and nonalloimmune GF. Conclusions. These data suggest that at baseline, 2 distinct populations can be identified who are at high risk for renal allograft loss: a younger, nondiabetic patient group who develops GF due to alloimmunity and an older, more commonly diabetic population who develops DWFG and GF due to a mixture of causes—many nonalloimmune. Individualized management is needed to improve long-term renal allograft survival in the latter group.

Background. The study aims is to use the fragility index (FI) to examine the strength of evidence of randomized controlled trials (RCTs) published in the last decade on kidney transplantation. Methods. We searched MEDLINE for studies on kidney transplantation. We included the RCTs that compared 2 groups with 1:1 randomization and reported significant P values (<0.05) for a dichotomous outcome and were published in the top 10 transplant journals. We calculated the FI; a calculation used to determine the minimum number of subjects needed to change from a nonevent to an event to make the study results nonsignificant (P ≥ 0.05). Results. Fifty-seven RCTs met our inclusion criteria. The median sample size was 100 participants in each arm, the median number of events was 16 (interquartile range, 8–30) in the intervention group. Among the included trials, 79% were industry-funded, 93% involved medications, and the majority were open label. The median FI was 3 (interquartile range, 1–11). In 43% of the trials, the number of patients reported lost to follow-up was higher than or equal to the FI. Only 4% of the RCTs imputed a value for the missing dichotomous outcome. Furthermore, the median number of subjects who discontinued the trial because of adverse effects was 21, which was greater than the FI in 60% of the RCTs. Conclusions. The arbitrary classification of results into “significant” and “nonsignificant” based on P value <0.05 should perhaps be interpreted with the help of other statistical parameters and FI is one of them.

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.

Background Cardiovascular disease (CVD) is an important driver of mortality after kidney transplantation. Its broader impact on posttransplant health care utilization in US hospitals is unknown. Methods We used administrative claims data from the Nationwide Inpatient Sample and the American Hospital Association Annual Survey to identify hospitalizations for kidney transplant patients with a cardiovascular diagnosis from 2005 to 2011. CVD hospitalizations were stratified by transplant hospital status to characterize patterns in inpatient health care utilization and outcomes. Based on these analyses, the domestic burden of treatment for posttransplant CVD (myocardial infarction, stroke, congestive heart failure, dysrhythmia, cardiac arrest, malignant hypertension) was estimated. Results The total domestic burden of post-kidney transplant hospitalization between 2005 and 2011 is estimated at 389 138 of which 26.5% of episodes were related to CVD (n = 103 118). CVD was responsible for a growing proportion of post-transplant hospitalizations over time (24.4%-30.4%, P < 0.001). Compared with nontransplant hospitals, transplant hospitals had similar length of stay (median length of stay, 3.7 days), higher median costs per hospitalization (US $10 364 vs US $8606, overall US $9324), and lower adjusted mortality (3.2% vs 3.9%, overall 3.6%; P = 0.003). Conclusions Inpatient CVD care is increasing over time for kidney transplant patients, accounting for 30% of all post-transplant hospitalizations. Variation exists in the inpatient care, outcomes, and costs between by hospital type. Further studies are needed to better understand the mechanisms behind these phenomena.