Faculty Bibliography

BACKGROUND & AIMS:Frailty is associated with mortality in patients with cirrhosis. We measured frailty using 3 simple tests and calculated Liver Frailty Index (LFI) scores for patients at multiple ambulatory centers. We investigated associations between LFI scores, ascites, and hepatic encephalopathy (HE) and mortality. METHODS:Adults without hepatocellular carcinoma who were on the liver transplantation waitlist at 9 centers in the United States (N = 1044) were evaluated using the LFI; LFI scores of at least 4.5 indicated that patients were frail. We performed logistic regression analyses to assess associations between frailty and ascites or HE and competing risk regression analyses (with liver transplantation as the competing risk) to estimate sub-hazard ratios (sHRs) of waitlist mortality (death or removal from the waitlist). RESULTS:Of study subjects, 36% had ascites, 41% had HE, and 25% were frail. The odds of frailty were higher for patients with ascites (adjusted odd ratio 1.56, 95% confidence interval [CI] 1.15-2.14) or HE (odd ratio 2.45, 95% CI 1.80-3.33) than for those without these features. Larger proportions of frail patients with ascites (29%) or HE (30%) died while on the waitlist compared with patients who were not frail (17% of patients with ascites and 20% with HE). In univariable analysis, ascites (sHR 1.52, 95% CI 1.14-2.05), HE (sHR 1.84, 95% CI 1.38-2.45), and frailty (sHR 2.38, 95% CI 1.77-3.20) were associated with waitlist mortality. In adjusted models, only frailty remained significantly associated with waitlist mortality (sHR 1.82, 95% CI 1.31-2.52); ascites and HE were not. CONCLUSIONS:Frailty is a prevalent complication of cirrhosis that is observed more frequently in patients with ascites or HE and independently associated with waitlist mortality. LFI scores can be used to objectively quantify risk of death related to frailty-in excess of liver disease severity-in patients with cirrhosis.

In the past decade, there have been increasing efforts to better define and quantify the short- and long-term risks of living kidney donation. Recent studies have expanded upon the previous literature by focusing on outcomes that are important to potential and previous donors, applying unique databases and/or registries to follow large cohorts of donors for longer periods of time, and comparing outcomes with healthy nondonor controls to estimate attributable risks of donation. Leading outcomes important to living kidney donors include kidney health, surgical risks, and psychosocial effects of donation. Recent data support that living donors may experience a small increased risk of severe CKD and ESKD compared with healthy nondonors. For most donors, the 15-year risk of kidney failure is <1%, but for certain populations, such as young, black men, this risk may be higher. New risk prediction tools that combine the effects of demographic and health factors, and innovations in genetic risk markers are improving kidney risk stratification. Minor perioperative complications occur in 10%-20% of donor nephrectomy cases, but major complications occur in <3%, and the risk of perioperative death is <0.03%. Generally, living kidney donors have similar or improved psychosocial outcomes, such as quality of life, after donation compared with before donation and compared with nondonors. Although the donation process should be financially neutral, living kidney donors may experience out-of-pocket expenses and lost wages that may or may not be completely covered through regional or national reimbursement programs, and may face difficulties arranging subsequent life and health insurance. Living kidney donors should be fully informed of the perioperative and long-term risks before making their decision to donate. Follow-up care allows for preventative care measures to mitigate risk and ongoing surveillance and reporting of donor outcomes to inform prior and future living kidney donors.

BACKGROUND AND OBJECTIVES:Frailty, a syndrome distinct from comorbidity and disability, is clinically manifested as a decreased resistance to stressors and is present in up to 35% of patient with ESKD. It is associated with falls, hospitalizations, poor cognitive function, and mortality. Also, frailty is associated with poor outcomes after kidney transplant, including delirium and mortality. Frailty is likely also associated with decreased access to kidney transplantation, given its association with poor outcomes on dialysis and post-transplant. Yet, clinicians have difficulty identifying which patients are frail; therefore, we sought to quantify if frail kidney transplant candidates had similar access to kidney transplantation as nonfrail candidates. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:We studied 7078 kidney transplant candidates (2009-2018) in a three-center prospective cohort study of frailty. Fried frailty (unintentional weight loss, grip strength, walking speed, exhaustion, and activity level) was measured at outpatient kidney transplant evaluation. We estimated time to listing and transplant rate by frailty status using Cox proportional hazards and Poisson regression, adjusting for demographic and health factors. RESULTS:<0.001). CONCLUSIONS:Frailty is associated with lower chance of listing and lower rate of transplant, and is a potentially modifiable risk factor.

BACKGROUND:Many kidneys are discarded every year, with 3631 kidneys discarded in 2016 alone. Identifying kidneys at high risk of discard could facilitate "rescue" allocation to centers more likely to transplant them. The Probability of Delay or Discard (PODD) model was developed to identify marginal kidneys at risk of discard or delayed allocation beyond 36 hours of cold ischemia time. However, PODD has not been prospectively validated, and patterns of discard may have changed after policy changes such as the introduction of Kidney Donor Profile Index and implementation of the Kidney Allocation System (KAS). METHODS:We prospectively validated the PODD model using Scientific Registry of Transplant Recipients data in the KAS era (January 1, 2015, to March 1, 2018). C statistic was calculated to assess accuracy in predicting kidney discard. We assessed clustering in centers' utilization of kidneys with PODD >0.6 ("high-PODD") using Gini coefficients. Using match run data from January 1, 2015, to December 31, 2016, we examined distribution of these high-PODD kidneys offered to centers that never accepted a high-PODD kidney. RESULTS:The PODD model predicted discard accurately under KAS (C-statistic, 0.87). Compared with utilization of low-PODD kidneys (Gini coefficient = 0.41), utilization of high-PODD kidneys was clustered more tightly among a few centers (Gini coefficient, 0.84 with >60% of centers never transplanted a high-PODD kidneys). In total, 11684 offers (35.0% of all high-PODD offers) were made to centers that never accepted a high-PODD kidney. CONCLUSIONS:Prioritizing allocation of high-PODD kidneys to centers that are more likely to transplant them might help reduce kidney discard.

Deceased donor kidney transplantation (DDKT) rates for highly sensitized (HS) candidates increased early after implementation of the Kidney Allocation System (KAS) in 2014. However, this may represent a bolus effect, and a granular investigation of the current state of DDKT for HS candidates remains lacking. We studied 270 722 DDKT candidates from the SRTR from 12/4/2011 to 12/3/2014 ("pre-KAS") and 12/4/2014 to 12/3/2017 ("post-KAS"), analyzing DDKT rates for HS candidates using adjusted negative binomial regression. Post-KAS, candidates with the highest levels of sensitization had an increased DDKT rate compared with pre-KAS (cPRA 98% adjusted incidence rate ratio [aIRR]:_1.27 1.77_2.46 P = .001, cPRA 99% aIRR:_3.18 4.36_5.98 P < .001, cPRA 99.5-99.9% aIRR:_16.91 24.29_34.89 P < .001, and cPRA 99.9%+ aIRR:_8.79 11.58_15.26 P < .001). To determine whether these changes produced more equitable access to DDKT, we compared DDKT rates of HS to non-HS candidates (cPRA 0-79%). Post-KAS, cPRA, 98% candidates had an equivalent DDKT rate (aIRR:_0.65 0.94_1.36 , P = .8) to non-HS candidates, whereas 99% candidates had a higher DDKT rate (aIRR:_1.19 1.68_2.38 , P = .02). Although cPRA 99.5-99.9% candidates had an increased DDKT rate (aIRR:_2.46 3.50_4.98 , P < .001) compared to non-HS candidates, cPRA 99.9%+ candidates had a significantly lower DDKT rate (aIRR:_0.29 0.40_0.56 , P < .001). KAS has improved access to DDKT for HS candidates, although substantial imbalance exists between cPRA 99.5-99.9% and 99.9%+ candidates.

Low T cell counts and acute rejection are associated with increased cardiovascular events (CVEs); T cell-depleting agents decrease both. Thus, we aimed to characterize the risk of CVEs by using an induction agent used in kidney transplant recipients. We conducted a secondary data analysis of patients who received a kidney transplant and used Medicare as their primary insurance from 1999 to 2010. Outcomes of interest were incident CVE, all-cause mortality, CVE-related mortality, and a composite outcome of mortality and CVE. Of 47 258 recipients, 29.3% received IL-2 receptor antagonist (IL-2RA), 33.3% received anti-thymocyte globulin (ATG), 7.3% received alemtuzumab, and 30.0% received no induction. Compared with IL-2RA, there was no difference in the risk of CVE in the ATG (adjusted hazard ratio [aHR] 0.98, 95% confidence interval [CI] 0.92-1.05) and alemtuzumab group (aHR 1.01, 95% CI 0.89-1.16), but slightly higher in the no induction group (aHR 1.06, 95% CI 1.00-1.14). Acute rejection did not modify this association in the latter group but did increase CVE by 46% in the alemtuzumab group. There was no difference in the hazard of all-cause or CVE-related mortality. Only in the ATG group, a 7% lower hazard of the composite outcome of mortality and CVE was noted. Induction agents are not associated with incident CVE, although prospective trials are needed to determine a personalized approach to prevention.

A consensus conference on frailty in kidney, liver, heart, and lung transplantation sponsored by the American Society of Transplantation (AST) and endorsed by the American Society of Nephrology (ASN), the American Society of Transplant Surgeons (ASTS), and the Canadian Society of Transplantation (CST) took place on February 11, 2018 in Phoenix, Arizona. Input from the transplant community through scheduled conference calls enabled wide discussion of current concepts in frailty, exploration of best practices for frailty risk assessment of transplant candidates and for management after transplant, and development of ideas for future research. A current understanding of frailty was compiled by each of the solid organ groups and is presented in this paper. Frailty is a common entity in patients with end-stage organ disease who are awaiting organ transplantation, and affects mortality on the waitlist and in the posttransplant period. The optimal methods by which frailty should be measured in each organ group are yet to be determined, but studies are underway. Interventions to reverse frailty vary among organ groups and appear promising. This conference achieved its intent to highlight the importance of frailty in organ transplantation and to plant the seeds for further discussion and research in this field.

BACKGROUND:There is concern that the metrics currently used to regulate transplant centers, one-year patient and graft survival, may have adverse consequences including decreasing higher risk donor organ acceptance and transplant volume. This raises questions about whether alternative measures would be more appropriate. METHODS:We surveyed American Society of Transplant Surgeons (ASTS) and American Society of Transplantation (AST) members (n = 270) to characterize perceptions of several metrics that are used for regulation, are publicly reported, or have been suggested elsewhere, regarding their effectiveness, amenability to risk adjustment, and predicted effects on volume, mortality, and waitlist size. RESULTS:Respondents rated one-year patient and graft survival the most effective measure of quality of care (mean scores = 7.44, 7.31, respectively, out of 10) and most amenable to risk adjustment (mean scores = 6.26, 6.13, respectively). Most respondents believed alternative metrics would not impact their center's volume, waitlist size, or one-year transplant mortality. However, some did predict unintended consequences; for example, some believed using one-year waitlist mortality, one-year mortality of patients listed, or one-year mortality of patients referred for transplant would decrease the number of transplants performed (48.6%, 46.7%, and 48.3% of respondents, respectively). DISCUSSION:Despite previously published concerns with existing regulatory metrics, most participants did not believe any metrics would outperform one-year patient and graft survival.

BACKGROUND:Social media platforms are increasingly used in surgery and have shown promise as effective tools to promote deceased donation and expand living donor transplantation. There is a growing need to understand how social media-driven communication is perceived by providers in the field of transplantation. METHODS:We surveyed 299 members of the American Society of Transplant Surgeons about their use of, attitudes toward, and perceptions of social media and analyzed relationships between responses and participant characteristics. RESULTS:Respondents used social media to communicate with: family and friends (76%), surgeons (59%), transplant professionals (57%), transplant recipients (21%), living donors (16%), and waitlisted candidates (15%). Most respondents (83%) reported using social media for at least 1 purpose. Although most (61%) supported sharing information with transplant recipients via social media, 42% believed it should not be used to facilitate living donor-recipient matching. Younger age (P = 0.02) and fewer years of experience in the field of transplantation (P = 0.03) were associated with stronger belief that social media can be influential in living organ donation. Respondents at transplant centers with higher reported use of social media had more favorable views about sharing information with transplant recipients (P < 0.01), increasing awareness about deceased organ donation (P < 0.01), and advertising for transplant centers (P < 0.01). Individual characteristics influence opinions about the role and clinical usefulness of social media. CONCLUSIONS:Transplant center involvement and support for social media may influence clinician perceptions and practices. Increasing use of social media among transplant professionals may provide an opportunity to deliver high-quality information to patients.