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: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.

Recent changes to liver allocation replaced donor service areas with circles as the geographic unit of allocation. Circle-based allocation might increase the number of transplantation centers and candidates required to place a liver, thereby increasing the logistical burden of making and responding to offers on organ procurement organizations and transplantation centers. Circle-based allocation might also increase distribution time and cold ischemia time (CIT), particularly in densely populated areas of the country, thereby decreasing allocation efficiency. Using Scientific Registry of Transplant Recipient data from 2019 to 2021, we evaluated the number of transplantation centers and candidates required to place livers in the precircles and postcircles eras, nationally and by donor region. Compared with the precircles era, livers were offered to more candidates (5 vs. 9; p  < 0.001) and centers (3 vs. 5; p  < 0.001) before being accepted; more centers were involved in the match run by offer number 50 (9 vs. 14; p  < 0.001); CIT increased by 0.2 h (5.9 h vs. 6.1 h; p  < 0.001); and distribution time increased by 2.0 h (30.6 h vs. 32.6 h; p  < 0.001). Increased burden varied geographically by donor region; livers recovered in Region 9 were offered to many more candidates (4 vs. 12; p  < 0.001) and centers (3 vs. 8; p  < 0.001) before being accepted, resulting in the largest increase in CIT (5.4 h vs. 6.0 h; p  < 0.001). Circle-based allocation is associated with increased logistical burdens that are geographically heterogeneous. Continuous distribution systems will have to be carefully designed to avoid exacerbating this problem.

UNLABELLED:Incompatible living donor kidney transplant recipients (ILDKTr) require desensitization to facilitate transplantation, and this substantial upfront immunosuppression may result in serious complications, including cancer. METHODS/UNASSIGNED:To characterize cancer risk in ILDKTr, we evaluated 858 ILDKTr and 12 239 compatible living donor kidney transplant recipients (CLDKTr) from a multicenter cohort with linkage to the US transplant registry and 33 cancer registries (1997-2016). Cancer incidence was compared using weighted Cox regression. RESULTS/UNASSIGNED:Among ILDKTr, the median follow-up time was 6.7 y (maximum 16.1 y) for invasive cancers (ascertained via cancer registry linkage) and 5.0 y (maximum 16.1 y) for basal and squamous cell carcinomas (ascertained via the transplant registry and censored for transplant center loss to follow-up). Invasive cancers occurred in 53 ILDKTr (6.2%) and 811 CLDKTr (6.6%; weighted hazard ratio [wHR] 1.01; 95% confidence interval [CI], 0.76-1.35). Basal and squamous cell carcinomas occurred in 41 ILDKTr (4.8%) and 737 CLDKTr (6.0%) (wHR 0.99; 95% CI, 0.69-1.40). Cancer risk did not vary according to donor-specific antibody strength, and in an exploratory analysis, was similar between CLDKTr and ILDKTr for most cancer types and according to cancer stage, except ILDKTr had a suggestively increased risk of colorectal cancer (wHR 3.27; 95% CI, 1.23-8.71); however, this elevation was not significant after correction for multiple comparisons. CONCLUSIONS/UNASSIGNED:These findings indicate that the risk of cancer is not increased for ILDKTr compared with CLDKTr. The possible elevation in colorectal cancer risk is unexplained and might suggest a need for tailored screening or prevention.

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.

Decreased postdonation eGFR is associated with a higher risk of ESRD after living kidney donation, even when accounting for predonation characteristics. The Toulouse-Rangueil model (TRM) estimates 12 month postdonation eGFR (eGFR12) to inform counseling of candidates for living donation. The TRM was validated in several single-center European cohorts but has not been validated in US donors. We assessed the TRM in living kidney donors in the US using SRTR data 1/2000-6/2021. We compared the 2021 CKD-EPI equation eGFR12 observed estimates to the TRM eGFR12 predictions. Median (IQR) bias was -3.4 (-9.3, 3.4) mL/min/1.73 m². Bias was higher for males vs. females (bias [IQR] -4.4 [-9.9, 1.8] vs. -2.9 [-8.8, 4.1]) and younger (31-40) vs. older donors (>50) (bias -4.9 [-10.6, 3.0] vs. -2.1 [-7.5, 4.0]). Bias was also larger for Black vs. White donors (bias (-6.7 [-12.1, -0.3], p < 0.001) vs. (-3.4 [-9.1, 3.1], p < 0.001)). Overall correlation was 0.71. In a sensitivity analysis using the 2009 CKD-EPI equation, results were generally consistent with exception to a higher overall bias (bias -4.2 [-9.8, 2.4]). The TRM overestimates postdonation renal function among US donors. Overestimation was greatest for those at higher risk for postdonation ESRD including male, Black, and younger donors. A new equation is needed to estimate postdonation renal function.

Background Pre-liver transplant (LT) sarcopenia is associated with poor survival. Methods exist for measuring body composition with use of CT scans; however, it is unclear which components best predict post-LT outcomes. Purpose To quantify the association between abdominal CT-based body composition measurements and post-LT mortality in a large North American cohort. Materials and Methods This was a retrospective cohort of adult first-time deceased-donor LT recipients from 2009 to 2018 who underwent pre-LT abdominal CT scans, including at the L3 vertebral level, at Johns Hopkins Hospital. Measurements included sarcopenia (skeletal muscle index [SMI] <50 in men and <39 in women), sarcopenic obesity, myosteatosis (skeletal muscle CT attenuation <41 mean HU for body mass index [BMI] <25 and <33 mean HU for BMI ≥25), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and VAT/SAT ratio. Covariates in the adjusted models were selected with use of least absolute shrinkage and selection operator regression with lambda chosen by means of 10-fold cross-validation. Cox proportional hazards models were used to quantify associations with post-LT mortality. Model discrimination was quantified using the Harrell C-statistic. Results A total of 454 recipients (median age, 57 years [IQR, 50-62 years]; 294 men) were evaluated. In the adjusted model, pre-LT sarcopenia was associated with a higher hazard ratio (HR) of post-LT mortality (HR, 1.6 [95% CI: 1.1, 2.4]; C-statistic, 0.64; P = .02). SMI was significantly negatively associated with survival after adjustment for covariates. There was no evidence that myosteatosis was associated with mortality (HR, 1.3 [95% CI: 0.86, 2.1]; C-statistic, 0.64; P = .21). There was no evidence that BMI (HR, 1.2 [95% CI: 0.95, 1.4]), VAT (HR, 1.0 [95% CI: 0.98, 1.1]), SAT (HR, 1.0 [95% CI: 0.97, 1.0]), and VAT/SAT ratio (HR, 1.1 [95% CI: 0.90, 1.4]) were associated with mortality (P = .15-.77). Conclusions Sarcopenia, as assessed on routine pre-liver transplant (LT) abdominal CT scans, was the only factor significantly associated with post-LT mortality. © RSNA, 2022 See also the editorial by Ruehm in this issue.

BACKGROUND:The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variability), provides a ripe opportunity for AI-based clinical decision support (CDS). However, AI-CDS for transplant applications must consider important concerns regarding fairness (ie, health equity). The objective of this study was to use human-centered design methods to elicit providers' perceptions of AI-CDS for liver transplant listing decisions. METHODS:In this multicenter qualitative study conducted from December 2020 to July 2021, we performed semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. We used inductive coding and constant comparison analysis of interview data. RESULTS:Analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient's role in the AI-CDS. CONCLUSIONS:Overall, providers interviewed were cautiously optimistic about the potential for AI-CDS to improve clinical and equitable outcomes for patients. These findings can guide multidisciplinary developers in the design and implementation of AI-CDS that deliberately considers health equity.