Faculty Bibliography

BACKGROUND:Biliary complications (BCs) continue to impact patient and graft survival after liver transplant (LT), despite improvements in organ preservation, surgical technique, and posttransplant care. Real-world evidence provides a national estimate of the incidence of BC after LT, implications for patient and graft outcomes, and attributable cost not available in transplant registry data. METHODS:An administrative health claims-based BC identification algorithm was validated using electronic health records (N = 128) and then applied to nationally linked Medicare and transplant registry claims. RESULTS:The real-world evidence algorithm identified 97% of BCs in the electronic health record review. Nationally, the incidence of BCs within 1 y of LT appears to have improved from 22.2% in 2002 to 20.8% in 2018. Factors associated with BCs include donor type (living versus deceased), recipient age, diagnosis, prior transplant, donor age, and donor cause of death. BCs increased the risk-adjusted hazard ratio (aHR) for posttransplant death (aHR, 1.43; P  < 0.0001) and graft loss (aHR, 1.48; P  < 0.0001). Nationally, BCs requiring intervention increased risk-adjusted first-year Medicare spending by $39 710 ( P  < 0.0001). CONCLUSIONS:BCs remain an important cause of morbidity and expense after LT and would benefit from a systematic quality-improvement program.

BACKGROUND:Statins are the third most prescribed drug class in kidney transplant recipients as cardiovascular disease is the leading cause of death in this population. However, statins' safety profile remains unclear in kidney transplant recipients who are uniquely burdened by concomitant immunosuppression and comorbidities. We conducted a national study to characterize the association of statin use with adverse events in kidney transplant recipients. METHODS:We studied adult (18 years or older) single-organ kidney transplant recipients in 2006-2016 with Medicare as primary payer ( n =57,699). We used prescription drug claims to capture statin use and International Classification of Diseases 9/10 diagnosis codes to capture statin-related adverse events (post-transplant diabetes mellitus, hemorrhagic stroke, cataract, liver injury, and rhabdomyolysis). We conducted multivariable Cox regression for each outcome with statin use as a time-varying exposure. RESULTS:Post-transplant diabetes mellitus was the most common outcome (5-year Kaplan-Meier incidence; 43% in statin users versus 35% in nonusers), followed by cataract (22% versus 12%), liver injury (2% versus 3%), hemorrhagic stroke (1.9% versus 1.4%), and rhabdomyolysis (1.5% versus 0.9%). In our multivariable analysis, statin use was associated with higher hazard of post-transplant diabetes mellitus (adjust hazard ratio [aHR], 1.12; 95% confidence interval [95% CI], 1.07 to 1.18), cataract (aHR, 1.22; 95% CI, 1.14 to 1.31), and rhabdomyolysis (aHR, 1.37; 95% CI, 1.10 to 1.71) but lower hazard of liver injury (aHR, 0.82; 95% CI, 0.71 to 0.95). Statin use was not associated with hemorrhagic stroke (aHR, 1.04; 95% CI, 0.86 to 1.26). CONCLUSIONS:Statins seem to be generally well tolerated in kidney transplant recipients. However, statin use might be associated with slightly higher risk of post-transplant diabetes mellitus, cataract, and rhabdomyolysis.

Machine learning (ML) models have recently shown potential for predicting kidney allograft outcomes. However, their ability to outperform traditional approaches remains poorly investigated. Therefore, using large cohorts of kidney transplant recipients from 14 centers worldwide, we developed ML-based prediction models for kidney allograft survival and compared their prediction performances to those achieved by a validated Cox-Based Prognostication System (CBPS). In a French derivation cohort of 4000 patients, candidate determinants of allograft failure including donor, recipient and transplant-related parameters were used as predictors to develop tree-based models (RSF, RSF-ERT, CIF), Support Vector Machine models (LK-SVM, AK-SVM) and a gradient boosting model (XGBoost). Models were externally validated with cohorts of 2214 patients from Europe, 1537 from North America, and 671 from South America. Among these 8422 kidney transplant recipients, 1081 (12.84%) lost their grafts after a median post-transplant follow-up time of 6.25 years (Inter Quartile Range 4.33-8.73). At seven years post-risk evaluation, the ML models achieved a C-index of 0.788 (95% bootstrap percentile confidence interval 0.736-0.833), 0.779 (0.724-0.825), 0.786 (0.735-0.832), 0.527 (0.456-0.602), 0.704 (0.648-0.759) and 0.767 (0.711-0.815) for RSF, RSF-ERT, CIF, LK-SVM, AK-SVM and XGBoost respectively, compared with 0.808 (0.792-0.829) for the CBPS. In validation cohorts, ML models' discrimination performances were in a similar range of those of the CBPS. Calibrations of the ML models were similar or less accurate than those of the CBPS. Thus, when using a transparent methodological pipeline in validated international cohorts, ML models, despite overall good performances, do not outperform a traditional CBPS in predicting kidney allograft failure. Hence, our current study supports the continued use of traditional statistical approaches for kidney graft prognostication.

Repeat kidney transplantation (re-KT) is the preferred treatment for patients with graft failure. Changing allocation policies, widening the risk profile of recipients, and improving dialysis care may have altered the survival benefit of a re-KT. We characterized trends in re-KT survival benefit over 3 decades and tested whether it differed by age, race/ethnicity, sex, and panel reactive assay (PRA). By using the Scientific Registry of Transplant Recipient data, we identified 25 419 patients who underwent a re-KT from 1990 to 2019 and 25 419 waitlisted counterfactuals from the same year with the same waitlisted time following graft failure. In the adjusted analysis, a re-KT was associated with a lower risk of death (adjusted hazard ratio [aHR] = 0.63; 95% confidence interval [CI], 0.61-0.65). By using the 1990-1994 era as a reference (aHR = 0.77; 95% CI, 0.69-0.85), incremental improvements in the survival benefit were noted (1995-1999: aHR = 0.72; 95% CI, 0.67-0.78: 2000-2004: aHR = 0.59; 95% CI, 0.55-0.63: 2005-2009: aHR = 0.59; 95% CI, 0.56-0.63: 2010-2014: aHR = 0.57; 95% CI, 0.53-0.62: 2015-2019: aHR = 0.64; 95% CI, 0.57-0.73). The survival benefit of a re-KT was noted in both younger (age = 18-64 years: aHR = 0.63; 95% CI, 0.61-0.65) and older patients (age ≥65 years: aHR = 0.66; 95% CI, 0.58-0.74; P_interaction = .45). Patients of all races/ethnicities demonstrated similar benefits with a re-KT. However, it varied by the sex of the recipient (female patients: aHR = 0.60; 95% CI, 0.56-0.63: male patients: aHR = 0.66; 95% CI, 0.63-0.68; P_interaction = .004) and PRA (0-20: aHR = 0.69; 95% CI, 0.65-0.74: 21-80: aHR = 0.61; 95% CI, 0.57-0.66; P_interaction = .02; >80: aHR = 0.57; 95% CI, 0.53-0.61; P_interaction< .001). Our findings support the continued practice of a re-KT and efforts to overcome the medical, immunologic, and surgical challenges of a re-KT.

BACKGROUND AND AIMS/OBJECTIVE:Identifying international differences in utilization and outcomes of liver transplantation (LT) after donation after circulatory death (DCD) donation provides a unique opportunity for benchmarking and population-level insight. METHODS:Adult (≥18 years) LT data between 2008 and 2018 from the UK and US were used to assess mortality and graft failure after DCD LT. We used time-dependent Cox-regression methods to estimate hazard ratios (HR) for risk-adjusted short-term (0-90 days) and longer-term (90 days-5 years) outcomes. RESULTS:One-thousand five-hundred-and-sixty LT receipts from the UK and 3426 from the US were included. Over the study period, the use of DCD livers increased from 15.7% to 23.9% in the UK compared to 5.1% to 7.6% in the US. In the UK, DCD donors were older (UK:51 vs. US:33 years) with longer cold ischaemia time (UK: 437 vs. US: 333 min). Recipients in the US had higher Model for End-stage Liver Disease (MELD) scores, higher body mass index, higher proportions of ascites, encephalopathy, diabetes and previous abdominal surgeries. No difference in the risk-adjusted short-term mortality or graft failure was observed between the countries. In the longer-term (90 days-5 years), the UK had lower mortality and graft failure (adj.mortality HR:UK: 0.63 (95% CI: 0.49-0.80); graft failure HR: UK: 0.72, 95% CI: 0.58-0.91). The cumulative incidence of retransplantation was higher in the UK (5 years: UK: 11.9% vs. 4.6%; p < .001). CONCLUSIONS:For those receiving a DCD LT, longer-term post-transplant outcomes in the UK are superior to the US, however, significant differences in recipient illness, graft quality and access to retransplantation were seen between the two countries.

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.

OBJECTIVE:The feasibility and 6-month outcome safety of lung transplants (LTs) from hepatitis C virus (HCV)-viremic donors for HCV-seronegative recipients (R-) were established in 2019, but longer-term safety and uptake of this practice nationally remain unknown. METHODS:testing, rank-sum testing, and Cox regression to compare posttransplant outcomes between HCV D+/R- and D-/R- LT recipients. RESULTS:HCV D+/R- LT increased from 2 to 97/year; centers performing HCV D+/R- LT increased from 1 to 25. HCV D+/R- versus HCV D-/R- LT recipients had more obstructive disease (35.7% vs 23.3%, P < .001), lower lung allocation score (36.5 vs 41.1, P < .001), and longer waitlist time (P = .002). HCV D+/R- LT had similar risk of acute rejection (adjusted odds ratio [aOR], 0.87; P = .58), extracorporeal membranous oxygenation (aOR, 1.94; P = .10), and tracheostomy (aOR, 0.42; P = .16); similar median hospital stay (P = .07); and lower risk of ventilator > 48 hours (aOR, 0.68; P = .006). Adjusting for donor, recipient, and transplant characteristics, risk of all-cause graft failure and mortality were similar at 30 days, 1 year, and 3 years for HCV D+/R- versus HCV D-/R- LT (all P > .1), as well as for high- (≥20/year) versus low-volume LT centers and high- (≥5/year) versus low-volume HCV D+/R- LT centers (all P > .5). CONCLUSIONS:HCV D+/R- and HCV D-/R- LT have similar outcomes at 3 years posttransplant. These results underscore the safety of HCV D+/R- LT and the potential benefit of expanding this practice further.

BACKGROUND:Disparities in pediatric kidney transplantation (KT) result in reduced access and worse outcomes for minority children. We assessed the impact of recent systems changes on these disparities. METHODS:This is a retrospective cohort study of pediatric patients utilizing data from the US Renal Data System (n = 7547) and Scientific Registry of Transplant Recipients (n = 6567 waitlisted and n = 6848 transplanted patients). We compared access to transplantation, time to deceased donor kidney transplant (DDKT), and allograft failure (ACGF) in the 5 years preceding implementation of the Kidney Allocation System (KAS) to the 5 years post-KAS implementation 2010-2014 vs. 2015-2019, respectively. RESULTS:p = 0.05) while there was no difference in 3- or 5-year ACGF among LDKT recipients. CONCLUSIONS:After KAS implementation, there is equity in time to DDKT. Pre-KAS increased hazard of ACGF among Black children has decreased in the post-KAS era; however, persistent disparities exist in time to transplant listing among Black and Hispanic children when compared to white children. A higher resolution version of the Graphical abstract is available as Supplementary information.