Faculty Bibliography

AIM/OBJECTIVE:There is conflicting evidence regarding the safety and effectiveness of warfarin for atrial fibrillation (AF) treatment among older end-stage renal disease (ESRD) patients, and differences among subgroups are unclear. METHODS:Older dialysis patients who were newly diagnosed with AF (7/2007-12/2011) were identified in the United States Renal Data System. The adjusted hazard ratios (HR) of the outcomes (any stroke, ischaemic stroke, major bleeding, severe gastrointestinal bleeding, and death) by time-varying warfarin use were estimated using Cox regression accounting for the inverse probability of treatment weight. RESULTS:Among 5765 older dialysis patients with incident AF, warfarin was associated with significantly increased risk of major bleeding (HR = 1.50, 95% CI 1.33-1.68), but was not statistically associated with any stroke (HR = 0.92, 95% CI 0.75-1.12), ischaemic stroke (HR = 0.88, 95%CI 0.70-1.11) or gastrointestinal bleeding (HR = 1.03, 95% CI 0.80-1.32). Warfarin use was associated with a reduced risk of mortality (HR = 0.72, 95%CI 0.65-0.80). The association between warfarin and major bleeding differed by sex (male: HR = 1.29; 95%CI 1.08-1.55; female: HR = 1.67; 95%CI 1.44-1.93; P-value for interaction = 0.03). CONCLUSION/CONCLUSIONS:Older ESRD patients with AF who were treated with warfarin had a no difference in stroke risk, lower mortality risk, but increased major bleeding risk. The bleeding risk associated with warfarin was greater among women than men. The risk/benefit ratio of warfarin may be less favourable among older women.

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.

Background:Frail obese community-dwelling older adults are at increased mortality risk. Among hemodialysis (HD) patients, frailty is common and associated with increased mortality risk; however, in dialysis, obesity is associated with decreased mortality risk. Whether the frail-obese phenotype is associated with increased mortality risk among HD patients remains unclear. Methods:This study included 370 incident HD patients enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease (PACE) study. We measured frailty using the Fried phenotype, general obesity [body mass index (BMI) ≥30 kg/m2] and abdominal obesity [waist:hip ratio (WHR) ≥median WHR] and estimated their associations with mortality. Results:The mean age was 55 years, with 42% female, 73% African American, 57% diabetic and 52% frail. Frail HD patients had higher mean BMI (frail = 30.3 kg/m2, non-frail = 28.3 kg/m2; P = 0.02) and similar WHR (P = 0.8). Twenty-two percent were frail with general obesity and 27% were frail with abdominal obesity. Frailty was associated with 1.66-fold increased mortality risk [95% confidence interval (CI) 1.03-2.67]. BMI was associated with a decreased mortality risk [25.0-29.9 kg/m2 hazard ratio (HR) 0.53 (95% CI 0.31-0.93); ≥30 kg/m2 HR 0.34 (95% CI 0.19-0.62)]. Frailty was associated with elevated mortality risk among HD patients with general [HR 3.77 (95% CI 1.10-12.92)] and abdominal obesity [HR 2.38 (95% CI 1.17-4.82)]. Frailty was not associated with mortality among HD patients without general or abdominal obesity. Conclusions:In adults initiating HD, frailty was associated with elevated mortality risk, even among the obese. Frail-obese HD patients may be a high-risk, often-overlooked population, as obesity is assumed to be protective. Measurement of frailty and obesity may facilitate risk stratification.

The impact of donor quality on post-kidney transplant (KT) survival may vary by candidate condition. Characterizing this variation would increase access to KT without sacrificing outcomes. We developed a tool to estimate post-KT survival for combinations of donor quality and candidate condition. We studied deceased donor KT recipients (n = 120 818) and waitlisted candidates (n = 376 272) between 2005 and 2016 by using the Scientific Registry of Transplant Recipients. Donor quality and candidate condition were measured by using the Kidney Donor Profile Index (KDPI) and the Estimated Post Transplant Survival (EPTS) score. We estimated 5-year post-KT survival based on combinations of KDPI and EPTS score using random forest algorithms and waitlist survival by EPTS score using Weibull regressions. Survival benefit was defined as absolute reduction in mortality risk with KT. For candidates with an EPTS score of 80, 5-year waitlist survival was 47.6%, and 5-year post-KT survival was 78.9% after receiving kidneys with a KDPI of 20 and was 70.7% after receiving kidneys with a KDPI of 80. The impact of KDPI on survival benefit varied greatly by EPTS score. For candidates with low EPTS scores (eg, <40), the KDPI had limited impact on survival benefit. For candidates with middle or high EPTS scores (eg, >40), survival benefit decreased with higher KDPI but was still substantial even with a KDPI of 100 (>16 percentage points). Our prediction tool (www.transplantmodels.com/kdpi-epts) can support individualized decision-making on kidney offers in clinical practice.

More than one-third of US adults have limited health literacy, putting them at risk of adverse clinical outcomes. We evaluated the prevalence of limited health literacy among 1578 adult kidney transplant (KT) candidates (May 2014-November 2017) and examined its association with listing for transplant and waitlist mortality in this pilot study. Limited health literacy was assessed at KT evaluation by using a standard cutoff score ≤5 on the Brief Health Literacy Screen (score range 0-12, lower scores indicate worse health literacy). We used logistic regression and adjusted Cox proportional hazards models to identify risk factors for limited health literacy and to quantify its association with listing and waitlist mortality. We found that 8.9% of candidates had limited health literacy; risk factors included less than college education (adjusted odds ratio [aOR] = 2.87, 95% confidence interval [CI]:1.86-4.43), frailty (aOR = 1.85, 95% CI:1.22-2.80), comorbidity (Charlson comorbidity index [1-point increase] aOR = 1.12, 95% CI: 1.04-1.20), and cognitive impairment (aOR = 3.45, 95% CI: 2.20-5.41) after adjusting for age, sex, race, and income. Candidates with limited health literacy had a 30% (adjusted hazard ratio = 0.70, 95% CI: 0.54-0.91) decreased likelihood of listing and a 2.42-fold (95% CI: 1.16- to 5.05-fold) increased risk of waitlist mortality. Limited health literacy may be a salient mechanism in access to KT; programs to aid candidates with limited health literacy may improve outcomes and reduce disparities.

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.