Faculty Bibliography

A more granular donor kidney grading scale, the kidney donor profile index (KDPI), has recently emerged in contradistinction to the standard criteria donor/expanded criteria donor framework. In this paper, we built a Markov decision process model to evaluate the survival, quality-adjusted life years (QALY), and cost advantages of using high-KDPI kidneys based on multiple KDPI strata over a 60-month time horizon as opposed to remaining on the waiting list waiting for a lower-KDPI kidney. Data for the model were gathered from the Scientific Registry of Transplant Recipients and the United States Renal Data System Medicare parts A, B, and D databases. Of the 129,024 phenotypes delineated in this model, 65% of them would experience a survival benefit, 81% would experience an increase in QALYs, 87% would see cost-savings, and 76% would experience cost-savings per QALY from accepting a high-KDPI kidney rather than remaining on the waiting list waiting for a kidney of lower-KDPI. Classification and regression tree analysis (CART) revealed the main drivers of increased survival in accepting high-KDPI kidneys were wait time ≥30 months, panel reactive antibody (PRA) <90, age ≥45 to 65, diagnosis leading to renal failure, and prior transplantation. The CART analysis showed the main drivers of increased QALYs in accepting high-kidneys were wait time ≥30 months, PRA <90, and age ≥55 to 65.

BACKGROUND/UNASSIGNED:Living kidney donation is possible for people living with HIV (PLWH) in the United States within research studies under the HIV Organ Policy Equity (HOPE) Act. There are concerns that donor nephrectomy may have an increased risk of end-stage renal disease (ESRD) in PLWH due to HIV-associated kidney disease and antiretroviral therapy (ART) nephrotoxicity. Here we report the first 3 cases of living kidney donors with HIV under the HOPE Act in the United States. METHODS/UNASSIGNED:Within the HOPE in Action Multicenter Consortium, we conducted a prospective study of living kidney donors with HIV. Pre-donation, we estimated the 9-year cumulative incidence of ESRD, performed genetic testing of apolipoprotein L1 (APOL1), excluding individuals with high-risk variants, and performed pre-donation kidney biopsies (HOPE Act requirement). The primary endpoint was ≥grade 3 nephrectomy-related adverse events (AEs) in year one. Post-donation, we monitored glomerular filtration rate (measured by iohexol/Tc-99m DTPA [mGFR] or estimated with serum creatinine [eGFR]), HIV RNA, CD4 count, and ART. FINDINGS/UNASSIGNED: at two years (eGFR) in donor 3. HIV RNA remained <20 copies/mL and CD4 count remained stable in all donors. INTERPRETATION/UNASSIGNED:The first three living kidney donors with HIV under the HOPE Act in the United States have had promising outcomes at two-four years, providing proof-of-concept to support living donation from PLWH to recipients with HIV. FUNDING/UNASSIGNED:National Institute of Allergy and Infectious Diseases, National Institutes of Health.

The latent viral reservoir(LVR) remains a major barrier to HIV-1 curative strategies. It is unknown whether receiving a liver transplant from a donor with HIV might lead to an increase in the LVR since the liver is a large lymphoid organ. We found no differences in intact provirus, defective provirus, or the ratio of intact to defective provirus between recipients with ART-supporesed HIV who received a liver from a donor with(n = 19) or without HIV(n = 10). All measures remained stable from baseline by one-year post transplant. These data demonstrate that the LVR is stable after liver transplantation in people living with HIV.

Background: Pediatric transplant candidates have historically been disadvantaged on the transplant waitlist, with nearly half of pediatric deceased donor organs allocated to adult recipients (Hsu, Gastroenterology, 2017), and allocation pediatric end-stage liver disease (PELD) scores that underestimate children's expected 3-month mortality compared to that of adult patients (Chang, JAMA Pediatrics, 2018). Disparities in organ distribution prompted revision of the liver allocation policy in 2020 from donation services areas (DSA) to a series of distance-based concentric circles called acuity circles (AC) before being offered nationally (US GAO, 2022), which was designed to minimize geographic inequity in liver transplant. Prior to implementation of the new liver allocation policy, analysis using the Liver Simulated Allocation Model projected that AC allocation would decrease disparities for pediatric liver transplant candidates and recipients by increasing transplants and decreasing waitlist mortality (Mogul, Transplantation, 2020). In this study, we evaluate differences in pediatric whole liver transplants performed before and after the implementation of acuity circle liver allocation policy.
Study Design: We evaluated patient characteristics, adjusted MELD/PELD at time of transplant, calculated donor age at time of transplant among pediatric whole liver transplant recipients in low versus high-volume pediatric liver transplant centers performed before and after implementation of AC-based liver allocation policy using the Scientific Registry of Transplant Recipients.
Result(s): Before and after the implementation of ACs, differences in pediatric liver transplants by age group (<2 years, 2-5 years old, 5-12 years old, and 12-18 years old) remained significantly different between low and high-volume pediatric transplant centers. Under DSA allocation policy, the median MELD/PELD at transplant was 37.0 (IQR 30.0-41.0) in low-volume centers and 40.0 (IQR 30.0-41.0) in high-volume centers. After the implementation of acuity circles, median MELD/PELD at transplant decreased to 35.0 (IQR 21.0-41.0) in low-volume centers and 35.0 (IQR 25.0-41.0) in high-volume centers. Finally, donor age at time of transplant increased from 8.0 (IQR 2.00-18.0) to 13.5 (IQR 4.5-21.0) at low-volume centers, and from 3.0 (IQR 1.0-14.0) to 4.0 (IQR 1.0-14.0) at high-volume centers before and after the implementation of ACs.
Conclusion(s): The change from DSAs to ACs in allocation policy and the shift from regional to national review boards have affected the characteristics of organ recipients, adjusted MELD/PELD at time of transplant, and donor age at time of transplant differentially between whole liver transplant recipients at low-and high-volume pediatric liver transplant centers

Background. Coronavirus disease 2019 (COVID-19)"“associated pulmonary aspergillosis (CAPA) is likely underdiagnosed, and current diagnostic tools are either invasive or insensitive. Methods. A retrospective study of mechanically ventilated patients with COVID-19 admitted to 5 Johns Hopkins hospitals between March 2020 and June 2021 was performed. Multivariable logistic regression was used for the CAPA prediction model building. Performance of the model was assessed using the area under the receiver operating characteristic curve (AUC). Results. In the cohort of 832 patients, 98 (11.8%) met criteria for CAPA. Age, time since intubation, dexamethasone for COVID-19 treatment, underlying pulmonary circulatory diseases, human immunodeficiency virus, multiple myeloma, cancer, or hematologic malignancies were statistically significantly associated with CAPA and were included in the CAPA prediction model, which showed an AUC of 0.75 (95% confidence interval, .70"“.80). At a screening cutoff of ≥0.085, it had a sensitivity of 82%, a specificity of 51%, a positive predictive value of 18.6%, and a negative predictive value of 95.3%. (The CAPA screening score calculator is available at www.transplantmodels.com). Conclusions. We developed a CAPA risk score as a noninvasive tool to aid in CAPA screening for patients with severe COVID-19. Our score will also identify a group of patients who are unlikely to have CAPA and who therefore need not undergo additional diagnostics and/or empiric antifungal therapy.

UNLABELLED:Following the outbreak of coronavirus disease 2019 (COVID-19) in the United States, the number of kidney waitlist additions and living-donor and deceased-donor kidney transplants (LDKT/DDKT) decreased substantially but began recovering within a few months. Since then, there have been several additional waves of infection, most notably, the Delta and Omicron surges beginning in August and December 2021, respectively. METHODS/UNASSIGNED:Using SRTR data, we compared observed waitlist registrations, waitlist mortality, waitlist removal due to deteriorating condition, LDKT, and DDKT over 5 distinct pandemic periods to expected events based on calculations from preepidemic data while accounting for seasonality and secular trends. RESULTS/UNASSIGNED:). CONCLUSIONS/UNASSIGNED:Despite exceptionally high COVID-19 incidence during the Omicron wave, the transplant system responded similarly to prior waves that imposed a lesser disease burden, demonstrating the transplant system's growing adaptations and resilience to this now endemic disease.