Alvin G. Thomas

Shipping living donor kidneys and transplant recipient outcomes

Kidney paired donation (KPD) is an important tool to facilitate living donor kidney transplantation (LDKT). Concerns remain over prolonged cold ischemia times (CIT) associated with shipping kidneys long distances through KPD. We examined the association between CIT and delayed graft function (DGF), allograft survival, and patient survival for 1267 shipped and 205 nonshipped/internal KPD LDKTs facilitated by the National Kidney Registry in the United States from 2008 to 2015, compared to 4800 unrelated, nonshipped, non‐KPD LDKTs. Shipped KPD recipients had a median CIT of 9.3 hours (range = 0.25‐23.9 hours), compared to 1.0 hour for internal KPD transplants and 0.93 hours for non‐KPD LDKTs. Each hour of CIT was associated with a 5% increased odds of DGF (adjusted odds ratio: 1.05, 95% confidence interval [CI], 1.02‐1.09, P < .01). However, there was not a significant association between CIT and all‐cause graft failure (adjusted hazard ratio [aHR]: 1.01, 95% CI: 0.98‐1.04, P = .4), death‐censored graft failure ( [aHR]: 1.02, 95% CI, 0.98‐1.06, P = .4), or mortality (aHR 1.00, 95% CI, 0.96‐1.04, P > .9). This study of KPD‐facilitated LDKTs found no evidence that long CIT is a concern for reduced graft or patient survival. Studies with longer follow‐up are needed to refine our understanding of the safety of shipping donor kidneys through KPD.

Incidence, risk factors, and sequelae of post-kidney transplant delirium

Background Frail kidney transplant (KT) recipients may be particularly vulnerable to surgical stressors, resulting in delirium and subsequent adverse outcomes. We sought to identify the incidence, risk factors, and sequelae of post-KT delirium.Methods We studied 125,304 adult KT recipients (1999-2014) to estimate delirium incidence in national registry claims. Additionally, we used a validated chart abstraction algorithm to identify post-KT delirium in 893 adult recipients (2009-2017) from a cohort study of frailty. Delirium sequelae were identified using adjusted logistic regression (length of stay ≥2 weeks and institutional discharge [skilled nursing or rehabilitation facility]) and adjusted Cox regression (death-censored graft loss and mortality).Results Only 0.8% of KT recipients had a delirium claim. In the cohort study, delirium incidence increased with age (18-49 years old: 2.0%; 50-64 years old: 4.6%; 65-75 years old: 9.2%; and ≥75 years old: 13.8%) and frailty (9.0% versus 3.9%); 20.0% of frail recipients aged ≥75 years old experienced delirium. Frailty was independently associated with delirium (odds ratio [OR], 2.05; 95% confidence interval [95% CI], 1.02 to 4.13; P=0.04), but premorbid global cognitive function was not. Recipients with delirium had increased risks of ≥2-week length of stay (OR, 5.42; 95% CI, 2.76 to 10.66; P<0.001), institutional discharge (OR, 22.41; 95% CI, 7.85 to 63.98; P<0.001), graft loss (hazard ratio [HR], 2.73; 95% CI, 1.14 to 6.53; P=0.03), and mortality (HR, 3.12; 95% CI, 1.76 to 5.54; P<0.001).Conclusions Post-KT delirium is a strong risk factor for subsequent adverse outcomes, yet it is a clinical entity that is often missed.

Design and Implementation of a Community Health Worker HIV Treatment and Prevention Intervention in an HIV Hot Spot Fishing Community in Rakai, Uganda

Innovative approaches are needed to increase engagement in HIV treatment and prevention services, particularly in HIV hot spots. Here, we detail our design, training approach, and early implementation experiences of a community-based HIV intervention called “health scouts.” The intervention, utilizing a novel, theory-based approach, trained 10 community residents in an HIV hot spot fishing community to use motivational interviewing strategies and a mobile phone–based counseling application. During the first 3 months, 771 residents (median 82/health scout, range 27-160) were counseled. A directly observed Motivational Interviewing Treatment Integrity scale–based evaluation found adequate performance (median score 20/25, range 11-23). The health scout intervention was feasible to implement in a high HIV-prevalence fishing community, and its impact on HIV care outcomes will be evaluated in an ongoing cluster randomized trial. If found to be effective, it may be an important strategy for responding to HIV in high-burden settings.

Cognitive Impairment and Graft Loss in Kidney Transplant Recipients

Background Cognitive impairment is common in end-stage renal disease patients and impairs adherence to complex treatment regimens. Given the need for post-transplant immunosuppression, we hypothesized that cognitive impairment at the time of transplant is associated with an increased risk of all-cause graft loss (ACGL) among kidney transplant (KT) recipients. Methods Using the Modified Mini-Mental State (3MS) examination, we measured global cognitive function in a prospective cohort of 864 KT candidates (8/2009-7/2016) as part of a multi-center, prospective cohort study. We estimated the association between pre-KT cognitive impairment and ACGL using Cox regression adjusting for recipient, donor, and transplant factors. We then estimated the national prevalence of cognitive impairment in US KT recipients using multiple imputation by chained equations and predictive mean matching. Results The prevalences of impairment (3MS<80) and severe impairment (3MS<60) were 6.6% and 3.3%, respectively, among living donor KT (LDKT) recipients and 12.4% and 2.6%, respectively, among deceased donor KT (DDKT) recipients. Projected nationally, 11.7% (8.5-14.9%) of all KT recipients had cognitive impairment during the study period (Table 1). LDKT recipients with impairment had higher ACGL risk than recipients without impairment (5-year ACGL: 45.5% vs. 10.6%, p<0.01; aHR impairment: 1.785.4016.34, p<0.01; aHR severe impairment: 1.295.5724.00, p=0.02) (Table 2, Figure 1). DDKT recipients with severe impairment had higher ACGL risk than recipients without severe impairment (5-year ACGL: 53.0% vs. 24.2%, p=0.04; aHR severe impairment: 1.132.927.50, p=0.03) (Figure 2). Conclusion Given the prevalence of cognitive impairment and the associated higher ACGL risk, pre-KT screening for impairment is warranted to identify higher-risk KT recipients. Figure. No caption available. Figure. No caption available. Figure. No caption available. National Institute of Diabetes and Digestive and Kidney Disease (NIDDK) and the National Institute on Aging (NIA); grant numbers K01AG043501 (PI: Mara McAdams-DeMarco), R01AG055781 (PI: Mara McAdams-DeMarco), F30DK116658 (PI: Ashton Shaffer), F32AG053025? (PI: Christine Haugen), K01AG050699 (PI: Alden Gross), K24DK101828 (PI: Dorry Segev), and R01DK096008 (PI: Dorry Segev). Additionally, Jessica Ruck and Dorry Segev are supported by a Doris Duke Charitable Foundation Clinical Research Mentorship grant.

Frailty, Inflammation, and Waitlist Mortality among Patients with End-Stage Renal Disease on the Kidney Transplant Waitlist

Background Among community-dwelling older adults, frailty is associated with heightened inflammation and subsequent mortality. Although frailty is common among patients on the KT waitlist, the role of frailty and inflammation in this population remains unclear. We quantified the association between frailty, inflammation, and mortality in ESRD patients on the KT waitlist, and tested whether frailty and/or inflammation improves risk prediction beyond clinical factors available in registry-based models. Methods We studied 1,975 prevalent ESRD patients on the KT waitlist (11/1/09-2/28/17) in a multi-center cohort study of measured frailty in patients undergoing transplant evaluation; serum inflammatory markers (interleukin-6 [IL-6], soluble tumor necrosis factor-a receptor-1 [sTNFR1], and C-reactive protein [CRP]) were analyzed in 605 of these participants. We compared the C-statistic of an established registry-based prediction model adding frailty and/or inflammation (1SD change in log IL-6, sTNFR1, CRP, or an aggregate inflammatory index). Results The mean age was 53.7 and 18.4% were frail. Frail candidates had elevated serum IL-6 (P<0.001), sTNFR1 (P=0.02), CRP (P=0.01), and a higher inflammatory index (P<0.001). The registry-based model had moderate predictive ability (C-statistic=0.655). Frailty was associated with increased waitlist mortality risk (frail HR=2.19, 95%CI:1.26-3.79) (Figure) but did not improve mortality risk prediction (C-statistic=0.646; P=0.65) (Table). Like frailty, IL-6 (HR=2.13, 95%CI:1.41-3.22), sTNFR1 (HR=1.70, 95%CI:1.12-2.59), CRP (HR=1.68, 95%CI:1.06-2.67), and the inflammatory index (HR=2.09, 95%CI:1.38-3.16) were all associated with increased waitlist mortality risk. But unlike frailty, adding IL-6 (C-statistic=0.777; P=0.02), CRP (C-statistic=0.728; P=0.02), or the inflammatory index (C-statistic=0.777; P=0.02) substantially improved mortality risk prediction. Conclusions Among adult ESRD patients on the KT waitlist, frailty and inflammation were associated with increased waitlist mortality risk, but only inflammatory markers significantly improved mortality risk prediction. Heightened inflammation may be the biological link between frailty and mortality in KT candidates. This study was supported by NIH grant R01AG042504 (PI: Dorry Segev), R01AG055781 (PI: McAdams-DeMarco) and K24DK101828 (PI: Dorry Segev). Mara McAdams-DeMarco was also supported by the Johns Hopkins University Claude D. Pepper Older Americans Independence Center (P30AG021334), National Institute on Aging (K01AG043501). Christine Haugen was supported by the National Institute on Aging (F32AG053025). Ashton Shaffer was supported by the National Institute of General Medical Sciences (5T32GM007309). Figure. No caption available. Figure. No caption available.

Landscape of Living Multi-organ Donation in the United States: A Registry-Based Cohort Study

BACKGROUND The donation of multiple allografts from a single living donor is a rare practice, and the patient characteristics and outcomes associated with these procedures are not well described. METHODS Using the Scientific Registry of Transplant Recipients, we identified 101 living multiorgan donors and their 133 recipients. RESULTS The 49 sequential (donations during separate procedures) multiorgan donors provided grafts to 81 recipients: 21 kidney-then-liver, 15 liver-then-kidney, 5 lung-then-kidney, 3 liver-then-intestine, 3 kidney-then-pancreas, 1 lung-then-liver, and 1 pancreas-then-kidney. Of these donors, 38% donated 2 grafts to the same recipient and 15% donated 2 grafts as non-directed donors. Compared to recipients from first-time, single organ living donors, recipients from second-time living donors had similar graft and patient survival. The 52 simultaneous (multiple donations during one procedure) multiorgan donors provided 2 grafts to 1 recipient each: 48 kidney-pancreas and 4 liver-intestine. Donors had median of 13.4 years (interquartile range, 8.3-18.5 years) of follow-up. There was one reported death of a sequential donor (2.5 years after second donation). Few postdonation complications were reported over a median of 116 days (interquartile range, 0-295 days) of follow-up; however, routine living donor follow-up data were sparse. Recipients of kidneys from second-time living donors had similar graft (P = 0.2) and patient survival (P = 0.4) when compared with recipients from first-time living donors. Similarly, recipients of livers from second-time living donors had similar graft survival (P = 0.9) and patient survival (P = 0.7) when compared with recipients from first-time living donors. CONCLUSIONS Careful documentation of outcomes is needed to ensure ethical practices in selection, informed consent, and postdonation care of this unique donor community.Background The donation of multiple allografts from a single living donor is a rare practice, and the patient characteristics and outcomes associated with these procedures are not well described. Methods Using the Scientific Registry of Transplant Recipients, we identified 101 living multiorgan donors and their 133 recipients. Results The 49 sequential (donations during separate procedures) multiorgan donors provided grafts to 81 recipients: 21 kidney-then-liver, 15 liver-then-kidney, 5 lung-then-kidney, 3 liver-then-intestine, 3 kidney-then-pancreas, 1 lung-then-liver, and 1 pancreas-then-kidney. Of these donors, 38% donated 2 grafts to the same recipient and 15% donated 2 grafts as non-directed donors. Compared to recipients from first-time, single organ living donors, recipients from second-time living donors had similar graft and patient survival. The 52 simultaneous (multiple donations during one procedure) multiorgan donors provided 2 grafts to 1 recipient each: 48 kidney-pancreas and 4 liver-intestine. Donors had median of 13.4 years (interquartile range, 8.3-18.5 years) of follow-up. There was one reported death of a sequential donor (2.5 years after second donation). Few postdonation complications were reported over a median of 116 days (interquartile range, 0-295 days) of follow-up; however, routine living donor follow-up data were sparse. Recipients of kidneys from second-time living donors had similar graft (P = 0.2) and patient survival (P = 0.4) when compared with recipients from first-time living donors. Similarly, recipients of livers from second-time living donors had similar graft survival (P = 0.9) and patient survival (P = 0.7) when compared with recipients from first-time living donors. Conclusions Careful documentation of outcomes is needed to ensure ethical practices in selection, informed consent, and postdonation care of this unique donor community.

Trends in Transplantation with Older Liver Donors in the United States

As the United States population ages, older liver donors (OLDs) represent a potential expansion of the donor pool. Historically, grafts from OLDs have been associated with poor outcomes and higher rates of discard. We sought to evaluate trends in demographics, discard, and outcomes of OLDs. Methods We identified 4127 OLDs (aged≥70) and 3350 liver-only OLD graft recipients using data from the Scientific Registry of Transplant Recipients in the United States (1/1/2003-12/31/2016). We studied temporal changes in OLD graft characteristics, utilization, and recipient characteristics. Modified Poisson regression was used to estimate the annual discard rate. Cuzick test of trend was used to compare changes in OLD transplants performed over the study period. Kaplan-Meier methods were also used to create unadjusted cumulative incidence curves of mortality and all-cause graft loss. Cox proportional hazards models were used to estimate mortality and graft loss for OLD graft recipients. Results From 2003 to 2016, the discard of OLDs increased from 11.6% to 15.4% with the highest discard rate in 2008 at 24.5%. Discarded OLDs were more likely to become younger (74.3 years in 2013-2016 vs. 75.6 years in 2003-2006, p=0.004), have a higher BMI (28.7 vs. 26.7, p=0.008), and less likely to be Caucasian (73.7 vs. 80.8, p=0.03). Since 2003 the percentage of OLD transplants performed out of all adult liver transplants has decreased from 6.0% to 3.2% (p=0.001). The average age of OLD recipients increased from 55.9 years in 2003 to 59.8 years in 2016 (p<0.001). Since 2003, the indication for liver transplant in recipients of OLD grafts has changed. OLD recipients became more likely to have non-alcoholic steatohepatitis (16.9% in 2013-2016 vs 4.1% in 2003-2006) or HCC (22.6% vs 10.6%) as their indication for LT. Also, the average cold ischemia time decreased from 7.7 hours in 2003-2006 to 5.7 hours in 2013-2016 (p<0.001). Graft and patient survival for OLD graft recipients improved since 2003: OLD graft recipients from 2013-2016, mortality was 60% lower (aHR:0.40,95%CI:0.31-0.52,p<0.001) and all-cause graft loss was 55% lower (aHR:0.45,95%CI:0.36-0.57,p<0.001) than between 2003-2006. Conclusion Up to 25% of OLDs are discarded annually across the US, and the number of OLD transplants performed has decreased. However, there is a significant improvement in graft and patient survival for OLD recipients since 2003. Particularly in the setting of an aging population, these trends in improved outcomes can guide OLD use and decrease OLD discard to possibly expand the donor pool. National Institutes of Health. Figure. No caption available. Figure. No caption available. Figure. No caption available. Figure. No caption available.

Assessing the Attitudes and Perceptions Regarding the Use of Mobile Health Technologies for Living Kidney Donor Follow-Up: Survey Study

Background In 2013, the Organ Procurement and Transplantation Network began requiring transplant centers in the United States to collect and report postdonation living kidney donor follow-up data at 6 months, 1 year, and 2 years. Despite this requirement, <50% of transplant centers have been able to collect and report the required data. Previous work identified a number of barriers to living kidney donor follow-up, including logistical and administrative barriers for transplant centers and cost and functional barriers for donors. Novel smartphone-based mobile health (mHealth) technologies might reduce the burden of living kidney donor follow-up for centers and donors. However, the attitudes and perceptions toward the incorporation of mHealth into postdonation care among living kidney donors are unknown. Understanding donor attitudes and perceptions will be vital to the creation of a patient-oriented mHealth system to improve living donor follow-up in the United States. Objective The goal of this study was to assess living kidney donor attitudes and perceptions associated with the use of mHealth for follow-up. Methods We developed and administered a cross-sectional 14-question survey to 100 living kidney donors at our transplant center. All participants were part of an ongoing longitudinal study of long-term outcomes in living kidney donors. The survey included questions on smartphone use, current health maintenance behaviors, accessibility to health information, and attitudes toward using mHealth for living kidney donor follow-up. Results Of the 100 participants surveyed, 94 owned a smartphone (35 Android, 58 iPhone, 1 Blackberry), 37 had accessed their electronic medical record on their smartphone, and 38 had tracked their exercise and physical activity on their smartphone. While 77% (72/93) of participants who owned a smartphone and had asked a medical question in the last year placed the most trust with their doctors, nurses, or other health care professionals regarding answering a health-related question, 52% (48/93) most often accessed health information elsewhere. Overall, 79% (74/94) of smartphone-owning participants perceived accessing living kidney donor information and resources on their smartphone as useful. Additionally, 80% (75/94) perceived completing some living kidney donor follow-up via mHealth as useful. There were no significant differences in median age (60 vs 59 years; P=.65), median years since donation (10 vs 12 years; P=.45), gender (36/75, 36%, vs 37/75, 37%, male; P=.57), or race (70/75, 93%, vs 18/19, 95%, white; P=.34) between those who perceived mHealth as useful for living kidney donor follow-up and those who did not, respectively. Conclusions Overall, smartphone ownership was high (94/100, 94.0%), and 79% (74/94) of surveyed smartphone-owning donors felt that it would be useful to complete their required follow-up with an mHealth tool, with no significant differences by age, sex, or race. These results suggest that patients would benefit from an mHealth tool to perform living donor follow-up.

Improving Living Kidney Donor Follow-up Using Mobile Health: A Pilot Randomized Control Trial (Preprint)

Background Every year, more than 5500 healthy people in the United States donate a kidney for the medical benefit of another person. The Organ Procurement and Transplantation Network (OPTN) requires transplant hospitals to monitor living kidney donors (LKDs) for 2 years postdonation. However, the majority (115/202, 57%) of transplant hospitals in the United States continue to fail to meet nationally mandated requirements for LKD follow-up. A novel method for collecting LKD follow-up is needed to ease both the transplant hospital-level and patient-level burden. We built mKidney—a mobile health (mHealth) system designed specifically to facilitate the collection and reporting of OPTN-required LKD follow-up data. The mKidney mobile app was developed on the basis of input elicited from LKDs, transplant providers, and thought leaders. Objective The primary objective of this study is to evaluate the impact of the mKidney smartphone app on LKD follow-up rates. Methods We will conduct a two-arm randomized controlled trial (RCT) with LKDs who undergo LKD transplantation at Methodist Specialty and Transplant Hospital in San Antonio, Texas. Eligible participants will be recruited in-person by a study team member at their 1-week postdonation clinical visit and randomly assigned to the intervention or control arm (1:1). Participants in the intervention arm will receive the mHealth intervention (mKidney), and participants in the control arm will receive the current standard of follow-up care. Our primary outcome will be policy-defined complete (all components addressed) and timely (60 days before or after the expected visit date) submission of LKD follow-up data at required 6-month, 1-year, and 2-year visits. Our secondary outcome will be hospital-level compliance with OPTN reporting requirements at each visit. Data analysis will follow the intention-to-treat principle. Additionally, we will collect quantitative and qualitative process data regarding the implementation of the mKidney system. Results We began recruitment for this RCT in May 2018. We plan to enroll 400 LKDs over 2 years and follow participants for the 2-year mandated follow-up period. Conclusions This pilot RCT will evaluate the impact of the mKidney system on rates of LKD and hospital compliance with OPTN-mandated LKD follow-up at a large LKD transplant hospital. It will provide valuable information on strategies for implementing such a system in a clinical setting and inform effect sizes for future RCT sample size calculations. International Registered Report Identifier (IRRID) DERR1-10.2196/11000

The first 9 years of kidney paired donation through the National Kidney Registry: Characteristics of donors and recipients compared with National Live Donor Transplant Registries

The practice of kidney paired donation (KPD) is expanding annually, offering the opportunity for live donor kidney transplant to more patients. We sought to identify if voluntary KPD networks such as the National Kidney Registry (NKR) were selecting or attracting a narrower group of donors or recipients compared with national registries. For this purpose, we merged data from the NKR database with the Scientific Registry of Transplant Recipients (SRTR) database, from February 14, 2008, to February 14, 2017, encompassing the first 9 years of the NKR. Compared with all United Network for Organ Sharing (UNOS) live donor transplant patients (49 610), all UNOS living unrelated transplant patients (23 319), and all other KPD transplant patients (4236), the demographic and clinical characteristics of NKR transplant patients (2037) appear similar to contemporary national trends. In particular, among the NKR patients, there were a significantly (P < .001) greater number of retransplants (25.6% vs 11.5%), hyperimmunized recipients (22.7% vs 4.3% were cPRA >80%), female recipients (45.9% vs 37.6%), black recipients (18.2% vs 13%), and those on public insurance (49.7% vs 41.8%) compared with controls. These results support the need for greater sharing and larger pool sizes, perhaps enhanced by the entry of compatible pairs and even chains initiated by deceased donors, to unlock more opportunities for those harder‐to‐match pairs.