Faculty Bibliography

BACKGROUND AND OBJECTIVES:Hypertension in older kidney donor candidates is viewed as safe. However, hypertension guidelines have evolved and long-term outcomes have not been explored. We sought to quantify the 15-year risk of ESKD and mortality in older donors (≥50 years old) with versus those without hypertension. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:A United States cohort of 24,533 older donors from 1999 to 2016, including 2265 with predonation hypertension, were linked to Centers for Medicare and Medicaid Services data and the Social Security Death Master File to ascertain ESKD development and mortality. The exposure of interest was predonation hypertension. From 2004 to 2016, hypertension was defined as documented predonation use of antihypertensive therapy, regardless of systolic BP or diastolic BP; from 1999 to 2003, when there was no documentation of antihypertensive therapy, hypertension was defined as predonation systolic BP ≥140 or diastolic BP ≥90 mm Hg. RESULTS:=0.34). CONCLUSIONS:Compared with older donors without hypertension, older donors with hypertension had higher risk of ESKD, but not mortality, for 15 years postdonation. However, the absolute risk of ESKD was small.

Information about wait-list time has been reported as one of the single most frequently asked questions by individuals awaiting a transplant but data regarding wait-list time have not been processed in a useful way for pediatric candidates. To predict chance of receiving a DDLT, we identified 6471 pediatric (<18 years), non status-1A, liver-only transplant candidates between 2006 and 2017 from the SRTR. Cox regression with shared frailty for DSA level effect was used to model the association of blood type, weight, allocation PELD and MELD, and DSA with chance of DDLT. Jackknife technique was used for validation. Median (interquartile range) wait-list time was 100 (34-309) days. Non-O Blood type, higher PELD/MELD score at listing, and DSA were associated with increased chance of DDLT, while age 1-5 years and 10-18 years was associated with lower chance of DDLT (P < 0.001 for all variables). Our model accurately predicted chance of transplant (C-statistic = 0.68) and was able to predict DDLT at specific follow-up times (eg, 3 months). This model can serve as the basis for an online tool that would provide useful information for pediatric wait-list candidates.

BACKGROUND:Despite providing survival benefit, increased risk for infectious disease (IRD) kidney offers are declined at 1.5 times the rate of non-IRD kidneys. Elucidating sources of variation in IRD kidney offer acceptance may highlight opportunities to expand use of these life-saving organs. METHODS:To explore center-level variation in offer acceptance, we studied 6765 transplanted IRD kidneys offered to 187 transplant centers between 2009 and 2017 using Scientific Registry of Transplant Recipients data. We used multilevel logistic regression to determine characteristics associated with offer acceptance and to calculate the median odds ratio (MOR) of acceptance (higher MOR indicates greater heterogeneity). RESULTS:Higher quality kidneys (per 10 units kidney donor profile index; adjusted odds ratio [aOR], 0.94; 95% confidence interval [CI], 0.92-0.95), higher yearly volume (per 10 deceased donor kidney transplants; aOR, 1.08, 95% CI, 1.06-1.10), smaller waitlist size (per 100 candidates; aOR, 0.97; 95% CI, 0.95-0.98), and fewer transplant centers in the donor service area (per center; aOR, 0.88; 95% CI, 0.85-0.91) were associated with greater odds of IRD acceptance. Adjusting for donor and center characteristics, we found wide heterogeneity in IRD offer acceptance (MOR, 1.96). In other words, if listed at a center with more aggressive acceptance practices, a candidate could be 2 times more likely to have an IRD kidney offer accepted. CONCLUSIONS:Wide national variation in IRD kidney offer acceptance limits access to life-saving kidneys for many transplant candidates.

BACKGROUND:Frail kidney transplant (KT) recipients have higher risk of adverse post-KT outcomes. Yet, there is interest in measuring frailty at KT evaluation and then using this information for post-KT risk stratification. Given long wait times for KT, frailty may improve or worsen between evaluation and KT. Patterns, predictors, and post-KT adverse outcomes associated with these changes are unclear. METHODS:Five hundred sixty-nine adult KT candidates were enrolled in a cohort study of frailty (November 2009-September 2017) at evaluation and followed up at KT. Patterns of frailty transitions were categorized as follows: (1) binary state change (frail/nonfrail), (2) 3-category state change (frail/intermediate/nonfrail), and (3) raw score change (-5 to 5). Adjusted Cox proportional hazard and logistic regression models were used to test whether patterns of frailty transitions were associated with adverse post-KT outcomes. RESULTS:Between evaluation and KT, 22.0% became more frail, while 24.4% became less frail. Black race (relative risk ratio, 1.98; 95% confidence interval [CI], 1.07-3.67) was associated with frail-to-nonfrail transition, and diabetes (relative risk ratio, 2.56; 95% CI, 1.22-5.39) was associated with remaining stably frail. Candidates who became more frail between 3-category states (hazard ratio, 2.27; 95% CI, 1.11-4.65) and frailty scores (hazard ratio, 2.36; 95% CI, 1.12-4.99) had increased risk of post-KT mortality and had higher odds of length of stay ≥2 weeks (3-category states: odds ratio, 2.02; 95% CI, 1.20-3.40; frailty scores: odds ratio, 1.92; 95% CI, 1.13-3.25). CONCLUSIONS:Almost half of KT candidates experienced change in frailty between evaluation and KT, and those transitions were associated with mortality and longer length of stay. Monitoring changes in frailty from evaluation to admission may improve post-KT risk stratification.

Impacts of the prescription opioid epidemic have not yet been examined in the context of heart transplantation. We examined a novel database in which national U.S. transplant registry records were linked to a large pharmaceutical claims warehouse (2007-2016) to characterize prescription opioid use before and after heart transplant, and associations (adjusted hazard ratio, _{95% LCL} aHR_{95% UCL} ) with death and graft loss. Among 13 958 eligible patients, 40% filled opioids in the year before transplant. Use was more common among recipients who were female, white, or unemployed, or who underwent transplant in more recent years. Of those with the highest level of pretransplant opioid use, 71% continued opioid use posttransplant. Pretransplant use had graded associations with 1-year posttransplant outcomes; compared with no use, the highest-level use (>1000 mg morphine equivalents) predicted 33% increased risk of death (aHR _1.10 1.33_1.61 ) in the year after transplant. Risk relationships with opioid use in the first year posttransplant were stronger, with highest level use predicting 70% higher mortality (aHR _1.46 1.70_1.98 ) over the subsequent 4 years (from >1 to 5 years posttransplant). While associations may, in part, reflect underlying conditions or behaviors, opioid use history is relevant in assessing and providing care to transplant candidates and recipients.

We examined a novel linkage of national US donor registry data with records from a pharmacy claims warehouse (2007-2016) to examine associations (adjusted hazard ratio, _LCL aHR_UCL ) of post-donation fills of antidiabetic medications (ADM, insulin or non-insulin agents) with body mass index (BMI) at donation and other demographic and clinical factors. In 28 515 living kidney donors (LKDs), incidence of ADM use at 9 years rose in a graded manner with higher baseline BMI: underweight, 0.9%; normal weight, 2.1%; overweight, 3.5%; obese, 8.5%. Obesity was associated with higher risk of ADM use compared with normal BMI (aHR, _3.36 4.59_6.27 ). Metformin was the most commonly used ADM and was filled more often by obese than by normal weight donors (9-year incidence, 6.87% vs 1.85%, aHR, _3.55 5.00_7.04 ). Insulin use was uncommon and did not differ significantly by BMI. Among a subgroup with BMI data at the 1-year post-donation anniversary (n = 19 528), compared with stable BMI, BMI increase >0.5 kg/m² by year 1 was associated with increased risk of subsequent ADM use (aHR, _1.03 1.48_2.14, P = .04). While this study did not assess the impact of donation on the development of obesity, these data support that among LKD, obesity is a strong correlate of ADM use.

Importance:Among liver transplant candidates, obesity and frailty are associated with increased risk of death while they are on the wait-list. However, use of body mass index (BMI) may not detect candidates at a higher risk of death owing to the fact that ascites and muscle wasting are seen across transplant candidates of all BMI measurements. Objective:To evaluate whether the association between wait-list mortality and frailty varied by BMI of liver transplant candidates. Design, Setting, and Participants:A prospective cohort study was conducted at 9 liver transplant centers in the United States from March 1, 2012, to May 1, 2018, among 1108 adult liver transplant candidates without hepatocellular carcinoma. Exposures:At outpatient evaluation, the Liver Frailty Index score was calculated (grip strength, chair stands, and balance), with frailty defined as a Liver Frailty Index score of 4.5 or more. Candidates' BMI was categorized as nonobese (18.5-29.9), class 1 obesity (30.0-34.9), and class 2 or greater obesity (≥35.0). Main Outcomes and Measures:The risk of wait-list mortality was quantified using competing risks regression by candidate frailty, adjusting for age, sex, race/ethnicity, Model for End-stage Liver Disease Sodium score, cause of liver disease, and ascites, including an interaction with candidate BMI. Results:Of 1108 liver transplant candidates (474 women and 634 men; mean [SD] age, 55 [10] years), 290 (26.2%) were frail; 170 of 670 nonobese candidates (25.4%), 64 of 246 candidates with class 1 obesity (26.0%), and 56 of 192 candidates with class 2 or greater obesity (29.2%) were frail (P = .57). Frail nonobese candidates and frail candidates with class 1 obesity had a higher risk of wait-list mortality compared with their nonfrail counterparts (nonobese candidates: adjusted subhazard ratio, 1.54; 95% CI, 1.02-2.33; P = .04; and candidates with class 1 obesity: adjusted subhazard ratio, 1.72; 95% CI, 0.99-2.99; P = .06; P = .75 for interaction). However, frail candidates with class 2 or greater obesity had a 3.19-fold higher adjusted risk of wait-list mortality compared with nonfrail candidates with class 2 or greater obesity (95% CI, 1.75-5.82; P < .001; P = .047 for interaction). Conclusions and Relevance:This study's finding suggest that among nonobese liver transplant candidates and candidates with class 1 obesity, frailty was associated with a 2-fold higher risk of wait-list mortality. However, the mortality risk associated with frailty differed for candidates with class 2 or greater obesity, with frail candidates having a more than 3-fold higher risk of wait-list mortality compared with nonfrail patients. Frailty assessments may help to identify vulnerable patients, particularly those with a BMI of 35.0 or more, in whom a clinician's visual evaluation may be less reliable to assess muscle mass and nutritional status.

Background/UNASSIGNED:Limited data are available regarding clinical implications of lower renal function after living kidney donation. We examined a novel integrated database to study associations between postdonation estimated glomerular filtration rate (eGFR) and use of antihypertensive medication (AHM) treatment after living kidney donation. Methods/UNASSIGNED:) between AHM use and postdonation eGFR levels (random effect) with fixed effects for baseline donor factors. Results/UNASSIGNED:). Conclusions/UNASSIGNED:This novel linkage illustrates the ability to identify postdonation kidney function and associate it with clinically meaningful outcomes; lower eGFR after living kidney donation is a correlate of AHM treatment requirements. Further work should define relationships of postdonation renal function, hypertension, and other morbidity measures.