Despite the rapidly increasing prevalence of obesity in the transplant population, the optimal management of obese liver transplant candidates remains undefined. Setting strict body mass index cutoffs for transplant candidacy remains controversial, with limited data to guide this practice. Body mass index is an imperfect measure of surgical risk in this population, partly due to volume overload and variable visceral adiposity. Weight loss before transplantation may be beneficial, but it remains important to avoid protein calorie malnutrition and sarcopenia. Intensive lifestyle modifications appear to be successful in achieving weight loss, though the durability of these interventions is not known. Pretransplant and intraoperative bariatric surgeries have been performed, but large randomized controlled trials are lacking. Traditional cardiovascular comorbidities are more prevalent in obese individuals and remain the basis for pretransplant cardiovascular evaluation and risk stratification. The recent US liver transplant experience demonstrates comparable patient and graft survival between obese and nonobese liver transplant recipients, but obesity presents important medical and surgical challenges during and after transplant. Specifically, obesity is associated with an increased incidence of wound infections, wound dehiscence, biliary complications and overall infection, and confers a higher risk of posttransplant obesity and metabolic syndrome-related complications. In this review, we examine current practices in the obese liver transplant population, offer recommendations based on the currently available data, and highlight areas where additional research is needed.

Background Low tacrolimus concentrations have been associated with higher risk of acute rejection, particularly within African-American (AA) kidney transplant recipients; little is known about intrapatient tacrolimus variabilities impact on racial disparities. Methods Ten year, single-center, longitudinal cohort study of kidney recipients. Intrapatient tacrolimus variability was assessed using the coefficient of variation (CV) measured between 1 month posttransplant and the clinical event, with a comparable period assessed in those without events. Pediatrics, nontacrolimus/mycophenolate regimens and nonrenal transplants were excluded. Multivariable Cox regression models were used to analyze data. Results 1411 recipients were included (54.4% AA) with 39 521 concentrations utilized to assess intrapatient tacrolimus CV. Overall, intrapatient tacrolimus CV was higher in AAs vs non-AAs (39.9±19.8 % vs. 34.8±15.8% p<0.001). Tacrolimus variability was a significant risk factor for deleterious clinical outcomes. A 10% increase in tacrolimus CV augmented the risk of acute rejection by 20% (aHR 1.20, 1.13–1.28; p<0.001) and the risk of graft loss by 30% (aHR 1.30, 1.23–1.37; p<0.001), with significant effect modification by race for acute rejection, but not graft loss. High tacrolimus variability (CV >40%) was a significant explanatory variable for disparities in AAs; the crude relative risk of acute rejection in AAs was reduced by 46% when including tacrolimus variability in modeling and reduced by 40% for graft loss. Conclusions These data demonstrate that intrapatient tacrolimus variability is strongly associated with acute rejection in AAs and graft loss in all patients. Tacrolimus variability is a significant explanatory variable for disparities in AA recipients.

Despite being in existence for >40 years, the application of telemedicine has lagged significantly in comparison to its generated interest. Detractors include the immobile design of most historic telemedicine interventions and the relative lack of smartphones among the general populace. Recently, the exponential increase in smartphone ownership and familiarity have provided the potential for the development of mobile health (mHealth) interventions that can be mirrored realistically in clinical applications. Existing studies have demonstrated some potential clinical benefits of mHealth in the various phases of solid organ transplantation (SOT). Furthermore, studies in nontransplant chronic diseases may be used to guide future studies in SOT. Nevertheless, substantially more must be accomplished before mHealth becomes mainstream. Further evidence of clinical benefits and a critical need for cost-effectiveness analysis must prove its utility to patients, clinicians, hospitals, insurers, and the federal government. The SOT population is an ideal one in which to demonstrate the benefits of mHealth. In this review, the current evidence and status of mHealth in SOT is discussed, and a general path forward is presented that will allow buy-in from the health care community, insurers, and the federal government to move mHealth from research to standard care.

Low-dose and high-dose valganciclovir regimens provide similar efficacy in preventing CMV disease in high-risk RTR, with a reduced incidence of leukopenia associated with the low-dose regimen and no difference in resistant CMV. Low-dose valganciclovir may provide a significant cost avoidance benefit.

Background: Non-adherence to medication is a well-studied and known cause of late allograft loss, but it is difficult to measure and prospectively monitor. The aim of this study was to assess if appointment non-adherence was correlated with medication non-adherence and a predictor of graft outcomes. Methods: This was a longitudinal cohort study that used the National United States Renal Data System and veterans affairs health records data with time-to-event analyses conducted to assess the impact on graft and patient survival. Results: The number of transplants that were included in the analysis was 4,646 (3,656 with complete records); 14.6% of patients had an appointment no show rate of ≥12% (non-adherence). Appointment and medication non-adherence were highly correlated and both were significant independent predictors of outcomes. Those with appointment non-adherence had 1.5 times the risk of acute rejection (22.0 vs. 14.7%, p < 0.0001) and a 65% higher risk of graft loss (adjusted hazards ratio (aHR) 1.65, 95% CI 1.38-1.97, p < 0.0001). There was a significant interaction between appointment and medication non-adherence; those with appointment and medication non-adherence were at very high risk of graft loss (aHR 4.18, 95% CI 3.39-5.15, p < 0.0001), compared to those with only appointment non-adherence (aHR 1.39, 95% CI 0.97-2.01, p = 0.0766) or only medication non-adherence (aHR 2.44, 95% CI 2.11-2.81, p < 0.0001). Conclusion: These results demonstrate that non-adherence to health care appointments is a significant and independent risk factor for graft loss.