Faculty Bibliography

In this study of 12 people with HIV (PWH) who received the first dose of SARS-CoV-2 mRNA vaccination, anti-SARS-CoV-2 receptor-binding domain antibodies were detectable in all participants; lower antibody levels were seen in those with lower CD4+ counts, and vaccine reactions were generally mild.

INTRODUCTION:We developed the strength training intervention (STRIVE), a home-based exercise program targeting physical function in patients with cirrhosis. In this pilot study, we aimed to evaluate the safety and efficacy of STRIVE. METHODS:Eligible were adult patients with cirrhosis at 3 sites. Patients were randomized 2:1-12 weeks of STRIVE, a 30-minute strength training video plus a health coach or standard of care (SOC). Physical function and quality of life were assessed using the Liver Frailty Index (LFI) and Chronic Liver Disease Questionnaire (CLDQ), respectively. RESULTS:Fifty-eight and 25 were randomized to STRIVE and SOC arms, respectively: 43% women, median age was 61 years, MELDNa, Model for End-Stage Liver Disease Sodium was 14, and 54% were Child-Pugh B/C. Baseline characteristics were similar in the STRIVE vs SOC arms except for rates of hepatic encephalopathy (19 vs 36%). LFI @ 12 weeks was available in 43 STRIVE and 20 SOC participants. After 12 weeks, the median LFI improved from 3.8 to 3.6 (ΔLFI -0.1) in the STRIVE arm and 3.7 to 3.6 (ΔLFI -0.1) in the SOC arm (P = 0.65 for ΔLFI difference). CLDQ scores improved from 4.6 to 5.2 in STRIVE participants (ΔCLDQ 0.38) and did not change in SOC participants (4.2-4.2; ΔCLDQ -0.03) (P = 0.09 for ΔCLDQ difference). One patient died (SOC arm) of bleeding. Only 14% of STRIVE participants adhered to the strength training video for 10-12 weeks. No adverse events were reported by STRIVE participants. DISCUSSION:STRIVE, a home-based structured exercise program for patients with cirrhosis, was safely administered at 3 sites, but adherence was low. Although all participants showed minimal improvement in the LFI, STRIVE was associated with a substantial improvement in quality of life.

BACKGROUND:Weight loss before kidney transplant (KT) is a known risk factor for weight gain and mortality, however, while unintentional weight loss is a marker of vulnerability, intentional weight loss might improve health. We tested whether pre-KT unintentional and intentional weight loss have differing associations with post-KT weight gain, graft loss and mortality. METHODS:Among 919 KT recipients from a prospective cohort study, we used adjusted mixed-effects models to estimate post-KT BMI trajectories, and Cox models to estimate death-uncensored graft loss, death-censored graft loss and all-cause mortality by 1-year pre-KT weight change category [stable weight (change ≤ 5%), intentional weight loss (loss > 5%), unintentional weight loss (loss > 5%) and weight gain (gain > 5%)]. RESULTS:The mean age was 53 years, 38% were Black and 40% were female. In the pre-KT year, 62% of recipients had stable weight, 15% had weight gain, 14% had unintentional weight loss and 10% had intentional weight loss. In the first 3 years post-KT, BMI increases were similar among those with pre-KT weight gain and intentional weight loss and lower compared with those with unintentional weight loss {difference +0.79 kg/m2/year [95% confidence interval (CI) 0.50-1.08], P < 0.001}. Only unintentional weight loss was independently associated with higher death-uncensored graft loss [adjusted hazard ratio (aHR) 1.80 (95% CI 1.23-2.62)], death-censored graft loss [aHR 1.91 (95% CI 1.12-3.26)] and mortality [aHR 1.72 (95% CI 1.06-2.79)] relative to stable pre-KT weight. CONCLUSIONS:This study suggests that unintentional, but not intentional, pre-KT weight loss is an independent risk factor for adverse post-KT outcomes.

The SRTR maintains the liver-simulated allocation model (LSAM), a tool for estimating the impact of changes to liver allocation policy. Integral to LSAM is a model that predicts the decision to accept or decline a liver for transplant. LSAM implicitly assumes these decisions are made identically for adult and pediatric liver transplant (LT) candidates, which has not been previously validated. We applied LSAM's decision-making models to SRTR offer data from 2013 to 2016 to determine its efficacy for adult (≥18) and pediatric (<18) LT candidates, and pediatric subpopulations-teenagers (≥12 to <18), children (≥2 to <12), and infants (<2)-using the area under the receiver operating characteristic (ROC) curve (AUC). For nonstatus 1A candidates, all pediatric subgroups had higher rates of offer acceptance than adults. For non-1A candidates, LSAM's model performed substantially worse for pediatric candidates than adults (AUC 0.815 vs. 0.922); model performance decreased with age (AUC 0.898, 0.806, 0.783 for teenagers, children, and infants, respectively). For status 1A candidates, LSAM also performed worse for pediatric than adult candidates (AUC 0.711 vs. 0.779), especially for infants (AUC 0.618). To ensure pediatric candidates are not unpredictably or negatively impacted by allocation policy changes, we must explicitly account for pediatric-specific decision making in LSAM.

Fine particulate matter (PM_2.5 ), a common form of air pollution which can induce systemic inflammatory response, is a risk factor for adverse health outcomes. Kidney transplant (KT) recipients are likely vulnerable to PM_2.5 due to comorbidity and chronic immunosuppression. We sought to quantify the association between PM_2.5 and post-KT outcomes. For adult KT recipients (1/1/2010-12/31/2016) in the Scientific Registry of Transplant Recipients, we estimated annual zip-code level PM_2.5 concentrations at the time of KT using NASA's SEDAC Global PM_2.5 Grids. We determined the associations between PM_2.5 and delayed graft function (DGF) and 1-year acute rejection using logistic regression and death-censored graft failure (DCGF) and mortality using Cox proportional hazard models. All models were adjusted for sociodemographics, recipient, transplant, and ZIP code level confounders. Among 87 233 KT recipients, PM_2.5 was associated with increased odds of DGF (OR = 1.59; 95% CI: 1.48-1.71) and 1-year acute rejection (OR = 1.31; 95% CI: 1.17-1.46) and increased risk of all-cause mortality (HR = 1.15; 95% CI: 1.07-1.23) but not DCGF (HR = 1.05; 95% CI: 0.97-1.51). In conclusion, PM_2.5 was associated with higher odds of DGF and 1-year acute rejection and elevated risk of mortality among KT recipients. Our study highlights the importance of considering environmental exposure as risk factors for post-KT outcomes.

Recently, model for end-stage liver disease (MELD)-based liver allocation in the United States has been questioned based on concerns that waitlist mortality for a given biologic MELD (bMELD), calculated using laboratory values alone, might be higher at certain centers in certain locations across the country. Therefore, we aimed to quantify the center-level variation in bMELD-predicted mortality risk. Using Scientific Registry of Transplant Recipients (SRTR) data from January 2015 to December 2019, we modeled mortality risk in 33 260 adult, first-time waitlisted candidates from 120 centers using multilevel Poisson regression, adjusting for sex, and time-varying age and bMELD. We calculated a "MELD correction factor" using each center's random intercept and bMELD coefficient. A MELD correction factor of +1 means that center's candidates have a higher-than-average bMELD-predicted mortality risk equivalent to 1 bMELD point. We found that the "MELD correction factor" median (IQR) was 0.03 (-0.47, 0.52), indicating almost no center-level variation. The number of centers with "MELD correction factors" within ±0.5 points, and between ±0.5-± 1, ±1.0-±1.5, and ±1.5-±2.0 points was 62, 41, 13, and 4, respectively. No centers had waitlisted candidates with a higher-than-average bMELD-predicted mortality risk beyond ±2 bMELD points. Given that bMELD similarly predicts waitlist mortality at centers across the country, our results support continued MELD-based prioritization of waitlisted candidates irrespective of center.

BACKGROUND:We studied the safety and reactogenicity SARS-CoV-2 mRNA vaccines in transplant recipients because immunosuppressed patients were excluded from vaccine trials. METHODS:US transplant recipients were recruited into this prospective cohort study through social media; those who completed the full vaccine series between December 9, 2020 and March 1, 2021 were included. We collected demographics, medical history, and safety information within 7 d after doses 1 and 2 (D1, D2). Associations between characteristics and reactions were evaluated using modified Poisson regression. RESULTS:We studied 741 transplant recipients who underwent BNT162b2 (54%) or mRNA-1273 (46%) vaccination. Median (interquartile range) age was 60 (44-69) y, 57% were female, and 10% were non-White. Although local site reactions decreased after D2 (85% D1 versus 78% D2, P < 0.001), systemic reactions increased (49% D1 versus 69% D2, P < 0.001). Younger participants were more likely to develop systemic symptoms after D1 (adjusted incidence rate ratio [aIRR] per 10 y = 0.850.900.94, P < 0.001) and D2 (aIRR per 10 y = 0.910.930.96, P < 0.001). Participants who experienced pain (aIRR = 1.111.662.47, P = 0.01) or redness (aIRR = 1.833.928.41, P < 0.01) were more likely to develop an antibody response to D1 of mRNA vaccines. No anaphylaxis, neurologic diagnoses, or SARS-CoV-2 diagnoses were reported. Infections were minimal (3% after D1, <0.01% after D2). One patient reported incident acute rejection post-D2. CONCLUSIONS:In solid organ transplant recipients undergoing mRNA vaccination, reactogenicity was similar to that reported in the original trials. Severe reactions were rare. These early safety data may help address vaccine hesitancy in transplant recipients.

BACKGROUND AND AIMS:In February 2020, the Organ Procurement and Transplantation Network replaced donor service area-based allocation of livers with acuity circles, a system based on three homogeneous circles around each donor hospital. This system has been criticized for neglecting to consider varying population density and proximity to coast and national borders. APPROACH AND RESULTS:Using Scientific Registry of Transplant Recipients data from July 2013 to June 2017, we designed heterogeneous circles to reduce both circle size and variation in liver supply/demand ratios across transplant centers. We weighted liver demand by Model for End-Stage Liver Disease (MELD)/Pediatric End-Stage Liver Disease (PELD) because higher MELD/PELD candidates are more likely to be transplanted. Transplant centers in the West had the largest circles; transplant centers in the Midwest and South had the smallest circles. Supply/demand ratios ranged from 0.471 to 0.655 livers per MELD-weighted incident candidate. Our heterogeneous circles had lower variation in supply/demand ratios than homogeneous circles of any radius between 150 and 1,000 nautical miles (nm). Homogeneous circles of 500 nm, the largest circle used in the acuity circles allocation system, had a variance in supply/demand ratios 16 times higher than our heterogeneous circles (0.0156 vs. 0.0009) and a range of supply/demand ratios 2.3 times higher than our heterogeneous circles (0.421 vs. 0.184). Our heterogeneous circles had a median (interquartile range) radius of only 326 (275-470) nm but reduced disparities in supply/demand ratios significantly by accounting for population density, national borders, and geographic variation of supply and demand. CONCLUSIONS:Large homogeneous circles create logistical burdens on transplant centers that do not need them, whereas small homogeneous circles increase geographic disparity. Using carefully designed heterogeneous circles can reduce geographic disparity in liver supply/demand ratios compared with homogeneous circles of radius ranging from 150 to 1,000 nm.