Faculty Bibliography

In the United States, kidney donation from international (noncitizen/nonresident) living kidney donors (LKDs) is permitted; however, given the heterogeneity of healthcare systems, concerns remain regarding the international LKD practice and recipient outcomes. We studied a US cohort of 102 315 LKD transplants from 2000-2016, including 2088 international LKDs, as reported to the Organ Procurement and Transplantation Network. International LKDs were more tightly clustered among a small number of centers than domestic LKDs (Gini coefficient 0.76 vs 0.58, P < .001). Compared with domestic LKDs, international LKDs were more often young, male, Hispanic or Asian, and biologically related to their recipient (P < .001). Policy-compliant donor follow-up was substantially lower for international LKDs at 6, 12, and 24 months postnephrectomy (2015 cohort: 45%, 33%, 36% vs 76%, 71%, 70% for domestic LKDs, P < .001). Among international LKDs, Hispanic (aOR = _0.23 0.36_0.56 , P < .001) and biologically related (aOR = _0.39 0.59_0.89 , P < .01) donors were more compliant in donor follow-up than white and unrelated donors. Recipients of international living donor kidney transplant (LDKT) had similar graft failure (aHR = _0.78 0.89_1.02 , P = .1) but lower mortality (aHR = _0.53 0.62_0.72 , P < .001) compared with the recipients of domestic LDKT after adjusting for recipient, transplant, and donor factors. International LKDs may provide an alternative opportunity for living donation. However, efforts to improve international LKD follow-up and engagement are warranted.

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)/UNASSIGNED:DERR1-10.2196/11000.

The number of live kidney donors has declined since 2005. This decline parallels the evolving knowledge of risk for biologically related, black, and younger donors. To responsibly promote donation, we sought to identify declining low-risk donor subgroups that might serve as targets for future interventions. We analyzed a national registry of 77 427 donors and quantified the change in number of donors per 5-year increment from 2005 to 2017 using Poisson regression stratified by donor-recipient relationship and race/ethnicity. Among related donors aged <35, 35 to 49, and ≥50 years, white donors declined by 21%, 29%, and 3%; black donors declined by 30%, 31%, and 12%; Hispanic donors aged <35 and 35 to 49 years declined by 18% and 15%, and those aged ≥50 increased by 10%. Conversely, among unrelated donors aged <35, 35 to 49, and ≥50 years, white donors increased by 12%, 4%, and 24%; black donors aged <35 and 35 to 49 years did not change but those aged ≥50 years increased by 34%; Hispanic donors increased by 16%, 21%, and 46%. Unlike unrelated donors, related donors were less likely to donate in recent years across race/ethnicity. Although this decline might be understandable for related younger donors, it is less understandable for lower-risk related older donors (≥50 years). Biologically related older individuals are potential targets for interventions to promote donation.

The Johns Hopkins University School of Medicine organized 2 multistakeholder symposia on February 2, 2018 and January 11, 2019 to address the problem of high graft failure in adolescent and young adult (AYA) solid organ transplant (SOT) recipients. Participants included international experts in transplantation, behavioral psychology, patient/parent advocacy, and technology. The objectives of the symposia were as follows: (1) to identify and discuss the barriers to and facilitators of effective transfer of care for AYA SOT recipients; (2) to actively explore strategies and digital solutions to promote their successful transfer of care; and (3) to develop meaningful partnerships for the successful development, evaluation, implementation, and dissemination of these digital solutions. Additionally, data were collected from 152 AYA SOT recipients demonstrating a substantial gap in how this population uses technologies for health-related activities, alongside an increased interest in an app to help them manage their transplant.

BACKGROUND:United States transplant centers are required to report follow-up data for living kidney donors for 2 years post-donation. However, living kidney donor (LKD) follow-up is often incomplete. Mobile health (mHealth) technologies could ease data collection burden but have not yet been explored in this context. METHODS:We conducted semi-structured in-depth interviews with a convenience sample of 21 transplant providers and thought leaders about challenges in LKD follow-up, and the potential role of mHealth in overcoming these challenges. RESULTS:Participants reported challenges conveying the importance of follow-up to LKDs, limited data from international/out-of-town LKDs, and inadequate staffing. They believed the 2-year requirement was insufficient, but expressed difficulty engaging LKDs for even this short time and inadequate resources for longer-term follow-up. Participants believed an mHealth system for post-donation follow-up could benefit LKDs (by simplifying communication/tasks and improving donor engagement) and transplant centers (by streamlining communication and decreasing workforce burden). Concerns included cost, learning curves, security/privacy, patient language/socioeconomic barriers, and older donor comfort with mHealth technology. CONCLUSIONS:Transplant providers felt that mHealth technology could improve LKD follow-up and help centers meet reporting thresholds. However, designing a secure, easy to use, and cost-effective system remains challenging.

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.

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.

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.

BACKGROUND:Neighborhood poverty has been associated with worse outcomes after live donor kidney transplantation (LDKT), and prior work suggests that women with kidney disease may be more susceptible to the negative influence of poverty than men. As such, our goal was to examine whether poverty differentially affects women in influencing LDKT outcomes. METHODS:Using data from the Scientific Registry of Transplant Recipients and US Census, we performed multivariable Cox regression to compare outcomes among 18 955 women and 30 887 men who received a first LDKT in 2005-2014 with follow-up through December 31, 2016. RESULTS:Women living in poor (adjusted hazard ratio [aHR], 1.30; 95% confidence interval [CI], 1.13-1.50) and middle-income (aHR, 1.26; 95% CI, 1.14-1.40) neighborhoods had higher risk of graft loss than men, but there were no differences in wealthy areas (aHR, 1.07; 95% CI, 0.88-1.29). Women living in wealthy (aHR, 0.71; 95% CI, 0.59-0.87) and middle-income (aHR, 0.82; 95% CI, 0.74-0.92) neighborhoods incurred a survival advantage over men, but there were no statistically significant differences in mortality in poor areas (aHR, 0.85; 95% CI, 0.72-1.01). CONCLUSIONS:Given our findings that poverty is more strongly associated with graft loss in women, targeted efforts are needed to specifically address mechanisms driving these disparities in LDKT outcomes.

BACKGROUND:The purpose of this study is to quantify the relationship between social media use and the dissemination of research across nontraditional channels. METHODS:Between June and August of 2016, the authors identified 10 plastic surgery journals with the highest impact factor and their 10 most widely circulated articles. Article age; journal impact factor; "distinguished" article designation; and social media metadata of the first authors, last authors, and journals were incorporated into a multivariate regression model to predict the Altmetric Attention Score, a quantitative measure of popularity across Web-based media platforms. RESULTS:A total of 100 articles, 181 authors, and 10 journals were identified. Older articles tended to be less popular. The article's popularity was associated with the journal's audience size, but not with the author's social media activity. For each 1000 additional Twitter followers of the journal of publication, the Altmetric score is greater by a factor of 1.72 (95 percent CI, 1.076 to 2.749), which is the equivalent of 72 percent more Tweets. There is also a small but statistically significant negative association between the author's social media audience size and the popularity of his or her articles: for every 1000 additional followers, the Altmetric score is lower by a factor of 0.822 (95 percent CI, 0.725 to 0.932), which is the equivalent of 17.8 percent fewer Tweets. CONCLUSION:The popularity of an article across social media platforms is associated with the journal's audience on social media, not with the magnitude of the author's social media activity.