Faculty Bibliography

IMPORTANCE/UNASSIGNED:Identifying the mechanisms of structural racism, such as racial and ethnic segregation, is a crucial first step in addressing the persistent disparities in access to live donor kidney transplantation (LDKT). OBJECTIVE/UNASSIGNED:To assess whether segregation at the candidate's residential neighborhood and transplant center neighborhood is associated with access to LDKT. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:In this cohort study spanning January 1995 to December 2021, participants included non-Hispanic Black or White adult candidates for first-time LDKT reported in the US national transplant registry. The median (IQR) follow-up time for each participant was 1.9 (0.6-3.0) years. MAIN OUTCOME AND MEASURES/UNASSIGNED:Segregation, measured using the Theil H method to calculate segregation tertiles in zip code tabulation areas based on the American Community Survey 5-year estimates, reflects the heterogeneity in neighborhood racial and ethnic composition. To quantify the likelihood of LDKT by neighborhood segregation, cause-specific hazard models were adjusted for individual-level and neighborhood-level factors and included an interaction between segregation tertiles and race. RESULTS/UNASSIGNED:Among 162 587 candidates for kidney transplant, the mean (SD) age was 51.6 (13.2) years, 65 141 (40.1%) were female, 80 023 (49.2%) were Black, and 82 564 (50.8%) were White. Among Black candidates, living in a high-segregation neighborhood was associated with 10% (adjusted hazard ratio [AHR], 0.90 [95% CI, 0.84-0.97]) lower access to LDKT relative to residence in low-segregation neighborhoods; no such association was observed among White candidates (P for interaction = .01). Both Black candidates (AHR, 0.94 [95% CI, 0.89-1.00]) and White candidates (AHR, 0.92 [95% CI, 0.88-0.97]) listed at transplant centers in high-segregation neighborhoods had lower access to LDKT relative to their counterparts listed at centers in low-segregation neighborhoods (P for interaction = .64). Within high-segregation transplant center neighborhoods, candidates listed at predominantly minority neighborhoods had 17% lower access to LDKT relative to candidates listed at predominantly White neighborhoods (AHR, 0.83 [95% CI, 0.75-0.92]). Black candidates residing in or listed at transplant centers in predominantly minority neighborhoods had significantly lower likelihood of LDKT relative to White candidates residing in or listed at transplant centers located in predominantly White neighborhoods (65% and 64%, respectively). CONCLUSIONS/UNASSIGNED:Segregated residential and transplant center neighborhoods likely serve as a mechanism of structural racism, contributing to persistent racial disparities in access to LDKT. To promote equitable access, studies should assess targeted interventions (eg, community outreach clinics) to improve support for potential candidates and donors and ultimately mitigate the effects of segregation.

BACKGROUND:In children with chronic kidney disease (CKD), certain risk factors are associated with faster eGFR decline and earlier kidney failure. Whether these factors have lingering effects on post-transplant eGFR trajectory remains unclear. We characterized pre- and post-transplant eGFR trajectories in pediatric kidney transplant recipients by their pre-kidney replacement therapy (KRT) risk factors. METHODS:We studied eGFR trajectories before KRT initiation and after transplantation among Chronic Kidney Disease in Children (CKiD) Study participants. We used mixed-effects models to compare pre-KRT versus post-transplant eGFR trajectories within individual participants by 7 pre-KRT risk factors: glomerular/non-glomerular etiology, race, preemptive transplant, proteinuria, albuminuria, and systolic/diastolic blood pressure (SBP/DBP). RESULTS:We analyzed 1602 pre-KRT and 592 post-transplant eGFR measurements from 246 transplant recipients. Mean annual eGFR decline was decreased from 18.0% pre-KRT (95%CI, 16.1-19.8) to 5.0% post-transplant (95%CI, 3.3-6.7). All 7 pre-KRT risk factors showed strong associations with faster pre-KRT eGFR decline, but not with post-transplant eGFR decline; only albuminuria, high SBP, and high DBP reached statistical significance with notably attenuated associations. In our multivariable model of the pre-KRT risk factors, post-transplant eGFR decline was more rapid only when albuminuria and high SBP were both present. CONCLUSIONS:eGFR decline substantially slows down after transplant even among children with rapidly progressing forms of CKD. Nonetheless, those who had albuminuria and high SBP before KRT might continue to show faster eGFR decline after transplant, specifically when both risk factors were present. This subgroup might benefit from intensive pre-transplant management for at least one of the two risk factors. A higher resolution version of the Graphical abstract is available as Supplementary information.

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 AND OBJECTIVE/OBJECTIVE:Older adults initiating dialysis have a high risk of mortality and that risk may be related to potentially inappropriate medications (PIMs). Our objective was to identify and validate mortality risk associated with American Geriatrics Society Beers Criteria PIM classes and concomitant PIM use. METHODS:We used US Renal Data System data to establish a cohort of adults aged ≥ 65 years initiating dialysis (2013-2014) and had no PIM prescriptions in the 6 months prior to dialysis initiation. In a development cohort (40% sample), adjusted Cox proportional hazards models were performed to determine which of 30 PIM classes were associated with mortality (or "high-risk" PIMs). Adjusted Cox models were performed to assess the association of the number of "high-risk" PIM fills/month with mortality. All models were repeated in the validation cohort (60% sample). RESULTS:In the development cohort (n = 15,570), only 13 of 30 PIM classes were associated with a higher mortality risk. Compared with those with no "high-risk" PIM fills/month, patients having one "high-risk" PIM fill/month had a 1.29-fold (95% confidence interval 1.21-1.38) increased risk of death; those with two or more "high-risk" PIM fills/month had a 1.40-fold (95% confidence interval 1.24-1.58) increased risk. These findings were similar in the validation cohort (n = 23,569). CONCLUSIONS:Only a minority of Beers Criteria PIM classes may be associated with mortality in the older dialysis population; however, mortality risk increases with concomitant use of "high-risk" PIMs. Additional studies are needed to confirm these associations and their underlying mechanisms.

SIGNIFICANCE STATEMENT:Cardiovascular diseases account for 32% of deaths among kidney transplant recipients. Statin therapy is common in this population. However, its effect on mortality prevention remains unclear among kidney transplant recipients, whose clinical risk profile might be unique because of concomitant immunosuppressive therapy. In this national study of 58,264 single-kidney transplant recipients, statin use was associated with a 5% decrease in mortality. More importantly, this protective association was stronger among those who used a mammalian target of rapamycin (mTOR) inhibitor for immunosuppression (27% decrease in mTOR inhibitor users versus 5% in nonusers). Our results suggest that statin therapy may reduce mortality in kidney transplant recipients and that the strength of this protective association may vary by immunosuppression regimen. BACKGROUND:Cardiovascular diseases are the leading cause of mortality in kidney transplant (KT) recipients, accounting for 32% of deaths. Statins are widely used in KT recipients, but effectiveness for preventing mortality remains unclear in this population, especially because of interaction between statins and immunosuppressive agents. We analyzed a national cohort to assess the real-world effectiveness of statins for reducing all-cause mortality in KT recipients. METHODS:We studied statin use and mortality among 58,264 adults (18 years or older) who received single kidneys between 2006 and 2016 and had Medicare part A/B/D. Statin use was ascertained from Medicare prescription drug claims and deaths from Center for Medicare and Medicaid Services records. We estimated the association of statin use with mortality using multivariable Cox models, with statin use as a time-varying exposure and immunosuppression regimen as effect modifiers. RESULTS:Statin use increased from 45.5% at KT to 58.2% at 1-year post-KT to 70.9% at 5-year post-KT. We observed 9785 deaths over 236,944 person-years. Overall, statin use was significantly associated with lower mortality (adjusted hazard ratio [aHR], 0.95; 95% confidence interval [CI], 0.90 to 0.99). The strength of this protective association varied by calcineurin inhibitor use (among tacrolimus users, aHR, 0.97; 95% CI, 0.92 to 1.03 versus among calcineurin nonusers, aHR, 0.72; 95% CI, 0.60 to 0.87; interaction P =0.002), mammalian target of rapamycin (mTOR) inhibitor use (among mTOR inhibitor users, aHR, 0.73; 95% CI, 0.57 to 0.92 versus among nonusers, aHR, 0.95; 95% CI, 0.91 to 1.00; interaction P =0.03), and mycophenolate use (among mycophenolate users, aHR, 0.96; 95% CI, 0.91 to 1.02 versus among nonusers, aHR, 0.76; 95% CI, 0.64 to 0.89; interaction P =0.002). CONCLUSION:Real-world evidence supports statin therapy for reducing all-cause mortality in KT recipients. Effectiveness might be greater when combined with mTOR inhibitor-based immunosuppression.

BACKGROUND:Gabapentinoids, commonly used for treating neuropathic pain, may be misused and coprescribed with opioid and benzodiazepine, increasing the risk of mortality and dependency among kidney transplant recipients. METHODS:We identified adult kidney transplant recipients who enrolled in Medicare Part D in 2006-2017 using the United States Renal Data System/Medicare claims database. We characterized recipients' post-transplant concomitant prescription of gabapentinoids, opioids, and benzodiazepine stratified by transplant year and recipient factors (age, sex, race, and diabetes). We investigated whether concomitant prescriptions were associated with postkidney transplant mortality using Cox regression. Models incorporated inverse probability weighting to adjust for confounders. RESULTS:Among 63,359 eligible recipients, 13% of recipients filled at least one gabapentinoid prescription within 1 year after kidney transplant. The prevalence of gabapentinoid prescriptions increased by 70% over the study period (16% in 2017 versus 10% in 2006). Compared with nonusers, gabapentinoids users were more likely to have diabetes (55% versus 37%) and obesity (46% versus 34%). Of the 8509 recipients with gabapentinoid prescriptions, 45% were coprescribed opioids, 7% were coprescribed benzodiazepines, and 3% were coprescribed both opioids and benzodiazepines. Compared with no study prescriptions, gabapentinoid monotherapy (adjusted hazard ratio [aHR]=1.25; 95% confidence interval [CI], 1.16 to 1.32) and combination therapy (gabapentinoids and opioids [aHR=1.49; 95% CI, 1.39 to 1.60], gabapentinoids and benzodiazepines [aHR=1.46; 95% CI, 1.03 to 2.08], and coprescribing all three [aHR=1.88; 95% CI, 1.18 to 2.98]) were all associated with a higher risk of postkidney transplant mortality. CONCLUSIONS:Gabapentinoid coprescription with both benzodiazepines and opioids among kidney transplant recipients increased over time. Kidney transplant recipients prescribed gabapentinoids had a higher risk of post-transplant mortality, and the risk was higher with opioids or benzodiazepine coprescription.

A recent study concluded that SARS-CoV-2 mRNA vaccine responses were improved among transplant patients taking mTOR inhibitors (mTORi). This could have profound implications for vaccine strategies in transplant patients; however, limitations in the study design raise concerns about the conclusions. To address this issue more robustly, in a large cohort with appropriate adjustment for confounders, we conducted various regression- and machine learning-based analyses to compare antibody responses by immunosuppressive agents in a national cohort (n = 1037). MMF was associated with significantly lower odds of positive antibody response (aOR = _0.09 0.13_0.18 ). Consistent with the recent mTORi study, the odds tended to be higher with mTORi (aOR = _1.00 1.45_2.13 ); however, importantly, this seemingly protective tendency disappeared (aOR = _0.47 0.73_1.12 ) after adjusting for MMF. We repeated this comparison by combinations of immunosuppression agents. Compared to MMF + tacrolimus, MMF-free regimens were associated with higher odds of positive antibody response (aOR = _2.39 4.26_7.92 for mTORi+tacrolimus; _2.34 5.54_15.32 for mTORi-only; and _6.78 10.25_15.93 for tacrolimus-only), whereas MMF-including regimens were not, regardless of mTORi use (aOR = _0.81 1.54_2.98 for MMF + mTORi; and _0.81 1.51_2.87 for MMF-only). We repeated these analyses in an independent cohort (n = 512) and found similar results. Our study demonstrates that the recently reported findings were confounded by MMF, and that mTORi is not independently associated with improved vaccine responses.

Kidney transplant (KT) recipients with delirium, a preventable surgical complication, are likely to reap cognitive benefits from restored kidney function, but may be more vulnerable to longer-term neurotoxic stressors post-KT (i.e., aging, immunosuppression). In this prospective cohort study, we measured delirium (chart-based), global cognitive function (3MS), and executive function (Trail Making Test Part B minus Part A) in 894 recipients (2009-2021) at KT, 1/3/6-months, 1-year, and annually post-KT. Dementia was ascertained using linked Medicare claims. We described repeated measures of cognitive performance (mixed effects model) and quantified dementia risk (Fine & Gray competing risk) by post-KT delirium. Of 894 recipients, 43(4.8%) had post-KT delirium. Delirium was not associated with global cognitive function at KT (difference = -3.2 points, 95%CI: -6.7, 0.4) or trajectories post-KT (0.03 points/month, 95%CI: -0.27, 0.33). Delirium was associated with worse executive function at KT (55.1 s, 95%CI: 25.6, 84.5), greater improvements in executive function <2 years post-KT (-2.73 s/month, 95%CI: -4.46,-0.99), and greater decline in executive function >2 years post-KT (1.72 s/month, 95%CI: 0.22, 3.21). Post-KT delirium was associated with over 7-fold greater risk of dementia post-KT (adjusted subdistribution hazard ratio = 7.84, 95%CI: 1.22, 50.40). Transplant centers should be aware of cognitive risks associated with post-KT delirium and implement available preventative interventions to reduce delirium risk.

BACKGROUND:Solid organ transplant recipients (SOTRs) are less likely to mount an antibody response to SARS-CoV-2 mRNA vaccines. Understanding risk factors for impaired vaccine response can guide strategies for antibody testing and additional vaccine dose recommendations. METHODS:Using a nationwide observational cohort of 1031 SOTRs, we created a machine learning model to explore, identify, rank, and quantify the association of 19 clinical factors with antibody responses to 2 doses of SARS-CoV-2 mRNA vaccines. External validation of the model was performed using a cohort of 512 SOTRs at Houston Methodist Hospital. RESULTS:Mycophenolate mofetil use, a shorter time since transplant, and older age were the strongest predictors of a negative antibody response, collectively contributing to 76% of the model's prediction performance. Other clinical factors, including transplanted organ, vaccine type (mRNA-1273 versus BNT162b2), sex, race, and other immunosuppressants, showed comparatively weaker associations with an antibody response. This model showed moderate prediction performance, with an area under the receiver operating characteristic curve of 0.79 in our cohort and 0.67 in the external validation cohort. An online calculator based on our prediction model is available at http://transplantmodels.com/covidvaccine/. CONCLUSIONS:Our machine learning model helps understand which transplant patients need closer follow-up and additional doses of vaccine to achieve protective immunity. The online calculator based on this model can be incorporated into transplant providers' practice to facilitate patient-centric, precision risk stratification and inform vaccination strategies among SOTRs.