The prevalence of postacute sequelae of coronavirus disease 2019 in solid organ transplant recipients: Evaluation of risk in the National COVID Cohort Collaborative.

Postacute sequelae after the coronavirus disease (COVID) of 2019 (PASC) is increasingly recognized, although data on solid organ transplant (SOT) recipients (SOTRs) are limited. Using the National COVID Cohort Collaborative, we performed 1:1 propensity score matching (PSM) of all adult SOTR and nonimmunosuppressed/immunocompromised (ISC) patients with acute COVID infection (August 1, 2021 to January 13, 2023) for a subsequent PASC diagnosis using International Classification of Diseases, 10th Revision, Clinical Modification codes. Multivariable logistic regression was used to examine not only the association of SOT status with PASC, but also other patient factors after stratifying by SOT status. Prior to PSM, there were 8769 SOT and 1 576 769 non-ISC patients with acute COVID infection. After PSM, 8756 SOTR and 8756 non-ISC patients were included; 2.2% of SOTR (n = 192) and 1.4% (n = 122) of non-ISC patients developed PASC (P value < .001). In the overall matched cohort, SOT was independently associated with PASC (adjusted odds ratio [aOR], 1.48; 95% confidence interval [CI], 1.09-2.01). Among SOTR, COVID infection severity (aOR, 11.6; 95% CI, 3.93-30.0 for severe vs mild disease), older age (aOR, 1.02; 95% CI, 1.01-1.03 per year), and mycophenolate mofetil use (aOR, 2.04; 95% CI, 1.38-3.05) were each independently associated with PASC. In non-ISC patients, only depression (aOR, 1.96; 95% CI, 1.24-3.07) and COVID infection severity were. In conclusion, PASC occurs more commonly in SOTR than in non-ISC patients, with differences in risk profiles based on SOT status.

Adherence to guideline-recommended care of late-onset hypertension in females versus males: A population-based cohort study.

BACKGROUND: Sex-based disparities in cardiovascular outcomes may be improved with appropriate hypertension management. OBJECTIVE: To compare the evidence-based evaluation and management of females with late-onset hypertension compared to males in the contemporary era. METHODS: Design: Retrospective population-based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Residents aged ≥66 years with newly diagnosed hypertension between January 1, 2010, and December 31, 2017. EXPOSURE: Sex (female vs. male). OUTCOMES AND MEASURES: We used Poisson and logistic regression to estimate adjusted sex-attributable differences in the performance of guideline-recommended lab investigations. We estimated adjusted differences in time to the prescription of, and type of, first antihypertensive medication prescribed between females and males, using Cox regression. RESULTS: Among 111,410 adults (mean age 73 years, 53% female, median follow-up 6.8 years), females underwent a similar number of guideline-recommended investigations (adjusted incidence rate ratio, 0.997 [95% confidence interval [CI] 0.99-1.002]) compared to males. Females were also as likely to complete all investigations (0.70% females, 0.77% males; adjusted odds ratio, 0.96 [95% CI 0.83-1.11]). Females were slightly less likely to be prescribed medication (adjusted hazard ratio [aHR] 0.98 [95% CI 0.96-0.99]) or, among those prescribed, less likely to be prescribed first-line medication (aHR, 0.995 [95% CI 0.994-0.997]). CONCLUSIONS: Compared to males, females with late-onset hypertension were equally likely to complete initial investigations with comparable prescription rates. These findings suggest that there may be no clinically meaningful sex-based differences in the initial management of late-onset hypertension to explain sex-based disparities in cardiovascular outcomes.

A multinational cohort study uncovered sex differences in excess mortality after kidney transplant.

Worldwide and at all ages, males have a higher mortality risk than females. This mortality bias should be preserved in kidney transplant recipients unless there are sex differences in the effects of transplantation. Here we compared the excess risk of mortality (risk above the general population) in female versus male recipients of all ages recorded in three large transplant databases. This included first deceased donor kidney transplant recipients and accounted for the modifying effects of donor sex and recipient age. After harmonization of variables across cohorts, relative survival models were fitted in each cohort separately and results were combined using individual patient data meta-analysis among 466,892 individuals (1988-2019). When the donor was male, female recipients 0-12 years (Relative Excess Risk 1.54, 95% Confidence Interval 1.20-1.99), 13-24 years (1.17, 1.01-1.34), 25-44 years (1.11, 1.05-1.18) and 60 years and older (1.05, 1.02-1.08) showed higher excess mortality risks than male recipients of the same age. When the donor was female, the Relative Excess Risk for those over 12 years were similar to those when the donor was male. There is a higher excess mortality risk in female than male recipients with differences larger at younger than older ages and only statistically significant when the donor was male. While these findings may be partly explained by the known sex differences in graft loss risks, sex differences in the risks of death with graft function may also contribute. Thus, higher risks in females than males suggest that management needs to be modified to optimize transplant outcomes among females.

Recipient race modifies the association between obesity and long-term graft outcomes after kidney transplantation.

Donor and recipient obesity (defined using body mass index [BMI]) are associated with worse outcomes after kidney transplant (KT). In adult KT recipients identified using the Scientific Registry of Transplant Recipients (2000-2017), we examined the modifying effect of recipient race on recipient obesity (BMI > 30 kg/m2) and combined donor and recipient (DR) obesity pairing, with death-censored graft loss (DCGL), all-cause graft loss (ACGL), and short-term graft outcomes using multivariable Cox proportional hazards models and logistic regression. Obesity was associated with a higher risk of DCGL in White (adjusted hazard ratio [aHR], 1.29; 95% CI, 1.25-1.35) than Black (aHR, 1.13; 95% CI, 1.08-1.19) recipients. White, but not Black, recipients with obesity were at higher risk for ACGL (aHR, 1.08; 95% CI, 1.05-1.11, for White recipients; aHR, 0.99; 95% CI, 0.95-1.02, for Black recipients). Relative to nonobese DR, White recipients with combined DR obesity experienced more DCGL (aHR, 1.38; 95% CI, 1.29-1.47 for White; aHR, 1.19; 95% CI, 1.10-1.29 for Black) and ACGL (aHR, 1.12; 95% CI, 1.07-1.17 for White; aHR, 1.00; 95% CI, 0.94-1.07 for Black) than Black recipients. Short-term obesity risk was similar irrespective of race. An elevated BMI differentially affects long-term outcomes in Black and White KT recipients; uniform BMI thresholds to define transplant eligibility are likely inappropriate.

Hormone replacement therapy and COVID-19 outcomes in solid organ transplant recipients compared with the general population.

Exogenous estrogen is associated with reduced coronavirus disease (COVID) mortality in nonimmunosuppressed/immunocompromised (non-ISC) postmenopausal females. Here, we examined the association of estrogen or testosterone hormone replacement therapy (HRT) with COVID outcomes in solid organ transplant recipients (SOTRs) compared to non-ISC individuals, given known differences in sex-based risk in these populations. SOTRs ≥45 years old with COVID-19 between April 1, 2020 and July 31, 2022 were identified using the National COVID Cohort Collaborative. The association of HRT use in the last 24 months (exogenous systemic estrogens for females; testosterone for males) with major adverse renal or cardiac events in the 90 days post-COVID diagnosis and other secondary outcomes were examined using multivariable Cox proportional hazards models and logistic regression. We repeated these analyses in a non-ISC control group for comparison. Our study included 1135 SOTRs and 43 383 immunocompetent patients on HRT with COVID-19. In non-ISC, HRT use was associated with lower risk of major adverse renal or cardiac events (adjusted hazard ratio [aHR], 0.61; 95% confidence interval [CI], 0.57-0.65 for females; aHR, 0.70; 95% CI, 0.65-0.77 for males) and all secondary outcomes. In SOTR, HRT reduced the risk of acute kidney injury (aHR, 0.79; 95% CI, 0.63-0.98) and mortality (aHR, 0.49; 95% CI, 0.28-0.85) in males with COVID but not in females. The potentially modifying effects of immunosuppression on the benefits of HRT requires further investigation.

Sex and organ-specific risk of major adverse renal or cardiac events in solid organ transplant recipients with COVID-19.

While older males are at the highest risk for poor coronavirus disease 2019 (COVID-19) outcomes, it is not known if this applies to the immunosuppressed recipient of a solid organ transplant (SOT), nor how the type of allograft transplanted may impact outcomes. In a cohort study of adult (>18 years) patients testing positive for COVID-19 (January 1, 2020-June 21, 2021) from 56 sites across the United States identified using the National COVID Cohort Collaborative (N3C) Enclave, we used multivariable Cox proportional hazards models to assess time to MARCE after COVID-19 diagnosis in those with and without SOT. We examined the exposure of age-stratified recipient sex overall and separately in kidney, liver, lung, and heart transplant recipients. 3996 (36.4%) SOT and 91 646 (4.8%) non-SOT patients developed MARCE. Risk of post-COVID outcomes differed by transplant allograft type with heart and kidney recipients at highest risk. Males with SOT were at increased risk of MARCE, but to a lesser degree than the non-SOT cohort (HR 0.89, 95% CI 0.81-0.98 for SOT and HR 0.61, 95% CI 0.60-0.62 for non-SOT [females vs. males]). This represents the largest COVID-19 SOT cohort to date and the first-time sex-age-stratified and allograft-specific COVID-19 outcomes have been explored in those with SOT.

The risk and consequences of breakthrough SARS-CoV-2 infection in solid organ transplant recipients relative to non-immunosuppressed controls.

Clinical outcomes in solid organ transplant (SOT) recipients with breakthrough COVID (BTCo) after two doses of mRNA vaccination compared to the non-immunocompromised/immunosuppressed (ISC) general population, are not well described. In a cohort of adult patients testing positive for COVID-19 between December 10, 2020 and April 4, 2022, we compared the cumulative incidence of BTCo in a non-ISC population to SOT recipients (overall and by organ type) using the National COVID Cohort Collaborative (N3C) including data from 36 sites across the United States. We assessed the risk of complications post-BTCo in vaccinated SOT recipients versus SOT with unconfirmed vaccination status (UVS) using multivariable Cox proportional hazards and logistic regression. BTCo occurred in 4776 vaccinated SOT recipients over a median of 149 days (IQR 99-233), with the highest cumulative incidence in heart recipients. The relative risk of BTCo was greatest in SOT recipients (relative to non-ISC) during the pre-Delta period (HR 2.35, 95% CI 1.80-3.08). The greatest relative benefit with vaccination for both non-ISC and SOT cohorts was in BTCo mortality (HR 0.37, 95% CI 0.36-0.39 for non-ISC; HR 0.67, 95% 0.57-0.78 for SOT relative to UVS). While the relative benefit of vaccine was less in SOT than non-ISC, SOT patients still exhibited significant benefit with vaccination.

Combined Donor-Recipient Obesity and the Risk of Graft Loss After Kidney Transplantation.

Background: As the prevalence of obesity increases globally, appreciating the effect of donor and recipient (DR) obesity on graft outcomes is of increasing importance. Methods: In a cohort of adult, kidney transplant recipients (2000-2017) identified using the SRTR, we used Cox proportional hazards models to examine the association between DR obesity pairing (body mass index (BMI) >30 kg/m2), and death-censored graft loss (DCGL) or all-cause graft loss, and logistic regression to examine risk of delayed graft function (DGF) and ≤30 days graft loss. We also explored the association of DR weight mismatch (>30 kg, 10-30 kg (D>R; D

What are the short-term annual cost savings associated with kidney transplantation?

BACKGROUND: Kidney transplantation (KT) is often reported in the literature as associated with cost savings. However, existing studies differ in their choice of comparator, follow-up period, and the study perspective. Also, there may be unobservable heterogeneity in health care costs in the patient population which may divide the population into groups with differences in cost distributions. This study estimates the cost savings associated with KT from a payer perspective and identifies and characterizes both high and low patient cost groups. METHOD: The current study was a population-based retrospective before-and-after study. The timespan involved at most three years before and after KT. The sample included end-stage kidney disease patients in Nova Scotia, a province in Canada, who had a single KT between January 1, 2011, and December 31, 2018. Each patient served as their control. The primary outcome measure was total annual health care costs. We estimated cost savings using unadjusted and adjusted models, stratifying the analyses by donor type. We quantified the uncertainty around the estimates using non-parametric and parametric bootstrapping. We also used finite mixture models to identify data-driven cost groups based on patients' pre-transplantation annual inpatient costs. RESULTS: The mean annual cost savings per patient associated with KT was $19,589 (95% CI: $14,013, $23,397). KT was associated with a 24-29% decrease in mean annual health care costs per patient compared with the annual costs before KT. We identified and characterized patients in three cost groups made of 2.9% in low-cost (LC), 51.8% in medium-cost (MC) and 45.3% in high-cost (HC). Cost group membership did not change after KT. Comparing costs in each group before and after KT, we found that KT was associated with 17% mean annual cost reductions for the LC group, 24% for the MC group and 26% for the HC group. The HC group included patients more likely to have a higher comorbidity burden (Charlson comorbidity index ≥ 3). CONCLUSIONS: KT was associated with reductions in annual health care costs in the short term, even after accounting for costs incurred during KT.

An ex-ante cost-utility analysis of the deemed consent legislation compared to expressed consent for kidney transplantations in Nova Scotia.

BACKGROUND: This study was an ex-ante cost-utility analysis of deemed consent legislation for deceased organ donation in Nova Scotia, a province in Canada. The legislation became effective in January 2021. The study's objective was to assess the conditions necessary for the legislation change's cost-effectiveness compared to expressed consent, focusing on kidney transplantation (KT). METHOD: We performed a cost-utility analysis using a Markov model with a lifetime horizon. The study was from a Canadian payer perspective. The target population was patients with end-stage kidney disease (ESKD) in Atlantic Canada waitlisted for KT. The intervention was the deemed consent and accompanying health system transformations. Expressed consent (before the change) was the comparator. We simulated the minimum required increase in deceased donor KT per year for the cost-effectiveness of the deemed consent. We also evaluated how changes in dialysis and maintenance immunosuppressant drug costs and living donor KT per year impacted cost-effectiveness in sensitivity analyses. RESULTS: The expected lifetime cost of an ESKD patient ranged from $177,663 to $553,897. In the deemed consent environment, the expected lifetime cost per patient depended on the percentage increases in the proportion of ESKD patients on the waitlist getting a KT in a year. The incremental cost-utility ratio (ICUR) increased with deceased donor KT per year. Cost-effectiveness of deemed consent compared to expressed consent required a minimum of a 1% increase in deceased donor KT per year. A 1% increase was associated with an ICUR of $32,629 per QALY (95% CI: - $64,279, $232,488) with a 81% probability of being cost-effective if the willingness-to-pay (WTP) was $61,466. Increases in dialysis and post-KT maintenance immunosuppressant drug costs above a threshold impacted value for money. The threshold for immunosuppressant drug costs also depended on the percent increases in deceased donor KT probability and the WTP threshold. CONCLUSIONS: The deemed consent legislation in NS for deceased organ donation and the accompanying health system transformations are cost-effective to the extent that they are anticipated to contribute to more deceased donor KTs than before, and even a small increase in the proportion of waitlist patients receiving a deceased donor KT than before the change represents value for money.

The differential impact of size mismatch in live versus deceased donor kidney transplant.

BACKGROUND: The impact of weight mismatch between donors and recipients (D-R) undergoing living-donor kidney transplant (LDKT) versus weight-matched deceased donor kidney transplant (DDKT) is not established. AIM: To determine whether absolute weight mismatch between D-R affects graft survival following LDKT and how this relates to graft outcomes with DDKT when D-R are weight matched. MATERIALS & METHODS: We used multivariable Cox proportional hazards models and the Scientific Registry of Transplant Recipients to determine the association of weight-mismatched D-R (>50 kg, 30-50 kg or 10-30 kg ((D < R); (D > R) and <10 kg (D = R)) with death-censored graft failure in US LDKT recipients from 2006 to 2017. We also explored outcomes relative to weight-matched DDKT and finally, the impact of combined D-R weight-sex mismatch. RESULTS: In LDKT, the risk of graft loss was highest in the setting of D < R (HR 1.28, 95% CI 1.05-1.56 for >50 kg difference relative to D = R); however, this was still lower risk than weight-matched DDKT. D-R sex and combined weight-sex mismatch were only important for male recipients (HR 1.47, 95% CI 1.27-1.71 for a male recipient >30 kg larger than their female donor, relative to weight-matched male donor-male recipient). This remained superior to weight-sex-matched DDKT however. CONCLUSION: D-R weight-sex mismatch is important in LDKT; however, graft survival remains superior to proceeding with matched DDKT. Optimizing D-R matching in LDKT could be facilitated through a national kidney-paired donation registry. LDKT weight-sex mismatch should not be deferred in favor of DDKT.

Predicting Kidney Graft Survival Using Machine Learning Methods: Prediction Model Development and Feature Significance Analysis Study.

BACKGROUND: Kidney transplantation is the optimal treatment for patients with end-stage renal disease. Short- and long-term kidney graft survival is influenced by a number of donor and recipient factors. Predicting the success of kidney transplantation is important for optimizing kidney allocation. OBJECTIVE: The aim of this study was to predict the risk of kidney graft failure across three temporal cohorts (within 1 year, within 5 years, and after 5 years following a transplant) based on donor and recipient characteristics. We analyzed a large data set comprising over 50,000 kidney transplants covering an approximate 20-year period. METHODS: We applied machine learning-based classification algorithms to develop prediction models for the risk of graft failure for three different temporal cohorts. Deep learning-based autoencoders were applied for data dimensionality reduction, which improved the prediction performance. The influence of features on graft survival for each cohort was studied by investigating a new nonoverlapping patient stratification approach. RESULTS: Our models predicted graft survival with area under the curve scores of 82% within 1 year, 69% within 5 years, and 81% within 17 years. The feature importance analysis elucidated the varying influence of clinical features on graft survival across the three different temporal cohorts. CONCLUSIONS: In this study, we applied machine learning to develop risk prediction models for graft failure that demonstrated a high level of prediction performance. Acknowledging that these models performed better than those reported in the literature for existing risk prediction tools, future studies will focus on how best to incorporate these prediction models into clinical care algorithms to optimize the long-term health of kidney recipients.

Early and recurrent hospitalization after kidney transplantation: Analysis of a contemporary canadian cohort of kidney transplant recipients.

Hospital readmission is a common occurrence following kidney transplantation, but less is known about the predictors of early and recurrent hospitalization. We analyzed a cohort of adult kidney transplant recipients in Nova Scotia, Canada, from January 2010 to December 2015. Readmission rates for 30 days, 6 months, and 1 year were calculated as a proportion of total transplants. Factors independently associated with early readmission were investigated using multivariable Cox hazards models with multivariable Anderson-Gill Cox models being used for factors independently associated with recurrent readmission. Of the 213 patients included, 41 (19.2%), 78 (36.6%), and 88 (41.3%) were readmitted to hospital within 30 days, 6 months, and 1 year, respectively. On multivariable analyses, a history of congestive heart failure (HR 1.741, 95% CI 1.039-2.918), peptic ulcer disease (HR 2.290, 95% CI 1.054-4.973), and liver disease (HR 2.492, 95% CI 1.162-5.344) was associated with higher risk of first rehospitalization. Recurrent hospital admission was associated with initial hospital duration ≥ 8 days (HR 2.140, 95% CI 1.265-3.618), congestive heart failure (HR 1.366, 95% CI 1.044-1.787), and liver disease (HR 1.785, 95% CI 1.257-2.534). Increasing duration of initial hospitalization, congestive heart failure, and liver disease are important to consider when evaluating a patient's risk for recurrent readmission following kidney transplant.

Burden of Emergency Medical Services Usage by Dialysis Patients.

BACKGROUND: Patients receiving chronic dialysis often require emergent and inpatient care; however, only a minimal amount is known about their out-of-hospital/inter-hospital use of Emergency Medical Services (EMS). The purpose of this study was to describe the utilization of EMS in a cohort of dialysis patients. METHODS: We analyzed a cohort of adult (≥18 years) chronic dialysis patients within the Nova Scotia Health Authority Central Zone Renal Program who initiated chronic dialysis between January 1, 2009 and June 30, 2013 (last follow up July 1, 2015). Dialysis patient data was linked to regional EMS data. Requests for EMS, including encounter type, day of the week, and patient characteristics were described. RESULTS: The cohort consisted of 468 patients of whom 79% (N = 361) had an EMS encounter. There were a total of 8,774 EMS encounters for the entire cohort. Patients who had an EMS encounter tended to be older (64 ± 14 years), compared to those without an encounter (55 ± 16 years, P < 0.001) and also had a higher burden of comorbidity. Transfers (including those between facilities) accounted for 89% of all encounters (N = 7,826), followed by emergency department (ED) transports (N = 749, 9%). Overall, 79% of all non-transfers underwent transport to the ED. For patients receiving thrice weekly in-center hemodialysis, the highest EMS utilization for ED transport occurred on the first hemodialysis day after the long dialysis break (22%, P < 0.01). The lowest proportion of ED transports occurred on the day after hemodialysis day 3. CONCLUSION: Utilization of EMS services by dialysis patients is considerable, particularly for transfers. This highlights a potential area to be targeted for reducing resource utilization. Calls requiring transport to the ED occurred most often on Mondays and Tuesdays, the day after the long-dialysis break, and may represent a time of heightened risk for in-center hemodialysis patients.

Whole-genome characterization in pedigreed non-human primates using genotyping-by-sequencing (GBS) and imputation.

BACKGROUND: Rhesus macaques are widely used in biomedical research, but the application of genomic information in this species to better understand human disease is still in its infancy. Whole-genome sequence (WGS) data in large pedigreed macaque colonies could provide substantial experimental power for genetic discovery, but the collection of WGS data in large cohorts remains a formidable expense. Here, we describe a cost-effective approach that selects the most informative macaques in a pedigree for 30X WGS, followed by low-cost genotyping-by-sequencing (GBS) at 30X on the remaining macaques in order to generate sparse genotype data at high accuracy. Dense variants from the selected macaques with WGS data are then imputed into macaques having only sparse GBS data, resulting in dense genome-wide genotypes throughout the pedigree. RESULTS: We developed GBS for the macaque genome using a digestion with PstI, followed by sequencing of size-selected fragments at 30X coverage. From GBS sequence data collected on all individuals in a 16-member pedigree, we characterized high-confidence genotypes at 22,455 single nucleotide variant (SNV) sites that were suitable for guiding imputation of dense sequence data from WGS. To characterize dense markers for imputation, we performed WGS at 30X coverage on nine of the 16 individuals, yielding 10,193,425 high-confidence SNVs. To validate the use of GBS data for facilitating imputation, we initially focused on chromosome 19 as a test case, using an optimized panel of 833 sparse, evenly-spaced markers from GBS and 5,010 dense markers from WGS. Using the method of "Genotype Imputation Given Inheritance" (GIGI), we evaluated the effects on imputation accuracy of 3 different strategies for selecting individuals for WGS, including 1) using "GIGI-Pick" to select the most informative individuals, 2) using the most recent generation, or 3) using founders only.  We also evaluated the effects on imputation accuracy of using a range of from 1 to 9 WGS individuals for imputation. We found that the GIGI-Pick algorithm for selection of WGS individuals outperformed common heuristic approaches, and that genotype numbers and accuracy improved very little when using >5 WGS individuals for imputation. Informed by our findings, we used 4 macaques with WGS data to impute variants at up to 7,655,491 sites spanning all 20 autosomes in the 12 remaining macaques, based on their GBS genotypes at only 17,158 loci. Using a strict confidence threshold, we imputed an average of 3,680,238 variants per individual at >99 % accuracy, or an average 4,458,883 variants per individual at a more relaxed threshold, yielding >97 % accuracy. CONCLUSIONS: We conclude that an optimal tradeoff between genotype accuracy, number of imputed genotypes, and overall cost exists at the ratio of one individual selected for WGS using the GIGI-Pick algorithm, per 3-5 relatives selected for GBS. This approach makes feasible the collection of accurate, dense genome-wide sequence data in large pedigreed macaque cohorts without the need for more expensive WGS data on all individuals.