Solid organ transplant recipients (SOTr) with coronavirus disease 2019 (COVID‐19) are expected to have poorer outcomes compared to nontransplant patients because of immunosuppression and comorbidities. The clinical characteristics of 47 SOTr (38 kidneys and 9 nonkidney organs) were compared to 100 consecutive hospitalized nontransplant controls. Twelve of 47 SOTr managed as outpatients were subsequently excluded from the outcome analyses to avoid potential selection bias. Chronic kidney disease (89% vs 57% P = .0007), diabetes (66% vs 33% P = .0007), and hypertension (94% vs 72% P = .006) were more common in the 35 hospitalized SOTr compared to controls. Diarrhea (54% vs 17%, P < .0001) was more frequent in SOTr. Primary composite outcome (escalation to intensive care unit, mechanical ventilation, or in‐hospital all‐cause mortality) was comparable between SOTr and controls (40% vs 48%, odds ratio [OR] 0.72 confidence interval [CI] [0.33‐1.58] P = .42), despite more comorbidities in SOTr. Acute kidney injury requiring renal replacement therapy occurred in 20% of SOTr compared to 4% of controls (OR 6 CI [1.64‐22] P = .007). Multivariate analysis demonstrated that increasing age and clinical severity were associated with mortality. Transplant status itself was not associated with mortality.

IMPORTANCE Among kidney transplant recipients, Black patients continue to have worse graft function and reduced patient and graft survival. Better understanding of different phenotypes and subgroups of Black kidney transplant recipients may help the transplant community to identify individualized strategies to improve outcomes among these vulnerable groups.OBJECTIVE To cluster Black kidney transplant recipients in the US using an unsupervised machine learning approach.DESIGN, SETTING, AND PARTICIPANTS This cohort study performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in Black kidney transplant recipients in the US from January 1, 2015, to December 31, 2019, in the Organ Procurement and Transplantation Network/United Network for Organ Sharing database. Each cluster's key characteristics were identified using the standardized mean difference, and subsequently the posttransplant outcomes were compared among the clusters. Data were analyzed from June 9 to July 17, 2021. EXPOSURE Machine learning consensus clustering approach.MAIN OUTCOMES AND MEASURES Death-censored graft failure, patient death within 3 years after kidney transplant, and allograft rejection within 1 year after kidney transplant.RESULTS Consensus cluster analysis was performed for 22 687 Black kidney transplant recipients (mean [SD] age, 51.4 [12.6] years; 13 635 men [60%]), and 4 distinct clusters that best represented their clinical characteristics were identified. Cluster 1 was characterized by highly sensitized recipients of deceased donor kidney retransplants; cluster 2, by recipients of living donor kidney transplants with no or short prior dialysis; cluster 3, by young recipients with hypertension and without diabetes who received young deceased donor transplants with low kidney donor profile index scores; and cluster 4, by older recipients with diabetes who received kidneys from older donors with high kidney donor profile index scores and extended criteria donors. Cluster 2 had the most favorable outcomes in terms of death-censored graft failure, patient death, and allograft rejection. Compared with cluster 2, all other clusters had a higher risk of death-censored graft failure and death. Higher risk for rejection was found in clusters 1 and 3, but not cluster 4. CONCLUSIONS AND RELEVANCEIn this cohort study using an unsupervised machine learning approach, the identification of clinically distinct clusters among Black kidney transplant recipients underscores the need for individualized care strategies to improve outcomes among vulnerable patient groups.

Background: The incidence and mortality of renal cell carcinoma (RCC) after kidney transplantation (KTx) remain unclear. This study's aims were (1) to investigate the pooled incidence/incidence trends, and (2) to assess the mortality/mortality trends in KTx patients with RCC. Methods: A literature search was conducted using the MEDLINE, EMBASE and Cochrane databases from inception through October 2018. Studies that reported the incidence or mortality of RCC among kidney transplant recipients were included. The pooled incidence and 95% CI were calculated using a random-effect model. The protocol for this meta-analysis is registered with PROSPERO; no. CRD42018108994. Results: A total of 22 observational studies with a total of 320,190 KTx patients were enrolled. Overall, the pooled estimated incidence of RCC after KTx was 0.7% (95% CI: 0.5–0.8%, I2 = 93%). While the pooled estimated incidence of de novo RCC in the native kidney was 0.7% (95% CI: 0.6–0.9%, I2 = 88%), the pooled estimated incidence of RCC in the allograft kidney was 0.2% (95% CI: 0.1–0.4%, I2 = 64%). The pooled estimated mortality rate in KTx recipients with RCC was 15.0% (95% CI: 7.4–28.1%, I2 = 80%) at a mean follow-up time of 42 months after RCC diagnosis. While meta-regression analysis showed a significant negative correlation between year of study and incidence of de novo RCC post-KTx (slopes = −0.05, P = 0.01), there were no significant correlations between the year of study and mortality of patients with RCC (P = 0.50). Egger's regression asymmetry test was performed and showed no publication bias in all analyses. Conclusions: The overall estimated incidence of RCC after KTX was 0.7%. Although there has been a potential decrease in the incidence of RCC post-KTx, mortality in KTx patients with RCC has not decreased over time.

This meta-analysis was conducted with the aims to summarize all available evidence on (1) prevalence of pre-existing atrial fibrillation (AF) and/or incidence of AF following kidney transplantation; (2) the outcomes of kidney transplant recipients with AF; and (3) the trends of estimated incidence of AF following kidney transplantation over time. A literature search was conducted utilizing MEDLINE, EMBASE, and the Cochrane Database from inception through March 2018. We included studies that reported (1) prevalence of pre-existing AF or incidence of AF following kidney transplantation or (2) outcomes of kidney transplant recipients with AF. Effect estimates from the individual study were extracted and combined utilizing random-effect, generic inverse variance method of DerSimonian and Laird. The protocol for this meta-analysis is registered with PROSPERO (International Prospective Register of Systematic Reviews; no. CRD42018086192). Eight cohort studies with 137,709 kidney transplant recipients were enrolled. Overall, the pooled estimated prevalence of pre-existing AF in patients undergoing kidney transplantation was 7.0% (95% CI: 5.6–8.8%) and pooled estimated incidence of AF following kidney transplantation was 4.9% (95% CI: 1.7–13.0%). Meta-regression analyses were performed and showed no significant correlations between year of study and either prevalence of pre-existing AF (p = 0.93) or post-operative AF after kidney transplantation (p = 0.16). The pooled odds ratios (OR) of mortality among kidney transplant recipients with AF was 1.86 (3 studies; 95% CI: 1.03–3.35). In addition, AF is also associated with death-censored allograft loss (2 studies; OR: 1.55, 95% CI: 1.02–2.35) and stroke (3 studies; OR: 2.54, 95% CI: 1.11–5.78) among kidney transplant recipients. Despite advances in medicine, incidence of AF following kidney transplant does not seem to decrease over time. In addition, there is a significant association of AF with increased mortality, allograft loss, and stroke after kidney transplantation.

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