key: cord-0902331-og581e51
authors: Vinson, Amanda J.; Dai, Ran; Agarwal, Gaurav; Anzalone, Alfred J.; Lee, Stephen B.; French, Evan; Olex, Amy L.; Madhira, Vithal; Mannon, Roslyn B.
title: Sex and organ‐specific risk of major adverse renal or cardiac events in solid organ transplant recipients with COVID‐19
date: 2021-11-01
journal: Am J Transplant
DOI: 10.1111/ajt.16865
sha: 449d7819d968b6c7698678c9877c4f223d6e57d6
doc_id: 902331
cord_uid: og581e51

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 critical manifestations of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection have been attributed to catastrophic immune dysregulation and a pathologic cytokine release syndrome resulting in many downstream complications, including acute kidney injury (AKI), major adverse cardiovascular events (MACE), acute respiratory distress syndrome (ARDS), and death. [1] [2] [3] The most important predictor of poor outcomes is older age. 4 In the general population, male sex has been strongly associated with COVID-19 attributable mortality; with a 1.4-2-fold higher casefatality rate in males compared with females. 5, 6 Solid organ transplant (SOT) patients with COVID-19 appear to be at an even higher risk than the general population based on their exposure to chronic maintenance immunosuppression and underlying comorbidities. [7] [8] [9] In this population, older individuals with COVID-19 have a 28-day case fatality rate of ~20% 9,10 compared to a 0.8%-2% risk in the general population. 11 Likewise, the risk of AKI in SOT patients with COVID-19 is increased at ~50%, 12 with one study demonstrating a need for renal replacement therapy in 23% and graft loss in 6.3% of kidney transplant recipients. 13 While several studies have examined outcomes in SOT recipients who develop COVID- 19 , most have been small scale and many are single-center analyses. 7, 8, [14] [15] [16] [17] Both organ transplantation and COVID-19 have been shown to independently increase the risk of cardiovascular disease, but the risk of MACE or major adverse renal or cardiac events (MARCE) in transplant patients who have COVID-19 has not been previously explored, nor the impact of specific allograft type on this outcome. Additionally, older age is clearly associated with poor outcomes in SOT patients with COVID-19, 13, 18 however, male SOT patients with do not appear to be at increased risk. 7, 10, 13, 16, [18] [19] [20] In the largest study of SOT patients with COVID-19 to date (a meta-analysis of 74 studies including 5559 kidney transplant recipients from March 2020-January 2021) sex was not associated with an increased risk of death or AKI. 21 Whether this reflects the size of the individual SOT studies reported, or a true mitigation of the sex-specific difference in COVID-19 disease observed in the general, nonimmunosuppressed population, is an important question that remains to be seen. A better understanding of potential sex-based differences in COVID-19 risk may guide insights into mechanisms of SARS-CoV-2 pathology and result in more specific interventions and management of COVID-19 in both sexes. Likewise, the relative risk of organ transplant type with adverse outcomes after COVID-19 diagnosis has been underappreciated.

With these questions in mind, we investigated potential predictors of MARCE in SOT recipients with COVID-19 disease using the largest COVID-19 database in the United States, the National COVID Cohort Collaborative (N3C). 22 N3C represents a large, national repository of 56 academic medical centers contributing data on more than 1.9 million adult patients with COVID-19 and more than 4 million COVID-19-negative controls. This centralized, harmonized, and highly granular repository of electronic health record (EHR) data represents the most representative and substantive resource for studying the U.S. COVID-19 population. 23 Capitalizing on this large database, we aimed to explore if COVID-19 risk in SOT recipients is effected by allograft type, and if male sex remains associated with worse outcomes in the SOT population. This is the largest study of SOT recipients with COVID-19 to date.

N3C includes a broad category of patients with limited inclusion criteria for incoming data; specifically COVID-19 positivity or suspected positivity by lab testing or diagnostic codes for both inpatient and outpatient encounters. 24 The incoming data comes from four primary data models-OMOP, PCORnet, TriNetX, and ACTharmonized into the OMOP 5.3.1 data model and made available within a secure enclave for analysis at the patient-and encounterlevel ( Figure S1 ). 22 A heat map of the geographical distribution of all patients contributing data to N3C is shown in Figure S2 .

We conducted a retrospective cohort study to examine adult SOT patients (>18 years of age) in the United States with at least one positive test for COVID-19 between January 1, 2020 and June 21, 2021. SOT patients were defined as having kidney, liver, lung or heart organ transplantation. The N3C Enclave was developed to facilitate analysis of patient-level data across the United States for multiple conditions, consisting of regular refresh cycles with data contributing organizations providing updated electronic medical records (EMRs) into a centralized, federally secured platform. 21 Our data were extracted from release 34 (June 21, 2021). As a comparator group, we examined all adult non-SOT patients captured in N3C with a positive test for COVID-19 over the same period.

The primary exposure was sex-age strata (female vs. male for each of age 18-45, 46-65, and >65 years, for a total of six sex-age categories). Males 18-45 years were considered the reference group.

The exposure for a secondary analysis was transplant allograft type (kidney, liver, lung, or heart). We excluded patients with multiple allograft types from this secondary analysis.

The primary outcome was MARCE in the 90 days post COVID-19 diagnosis, defined as a composite of AKI with or without dialysis, acute myocardial infarction, angina, stent occlusion/thrombosis, stroke, transient ischemic attack, congestive heart failure or death from any cause. As secondary outcomes we examined components of MARCE including (i) MACE, (ii) AKI, and (iii) death from any cause in the 90 days post-COVID-19 diagnosis, as well as (iv) COVID-19 disease severity (requiring hospitalization for or death from as defined by the WHO Ordinal Scale for Clinical Improvement. 23 Finally, in an organ-specific analysis we included the outcome of allograft rejection.

In addition to the primary exposure, a computable phenotype was cre- For the primary analysis, a complete case analysis was performed.

Given large amounts of missingness for BMI (>40%), an indicator was created for missing BMI and included as an adjustment variable in multivariate analyses. CKD staging was missing in 51% of patients, thus CKD status was included as a binary outcome for presence or absence (not stage).

Descriptive statistics were used to report baseline characteristics for all SOT and non-SOT patients included in the study, stratified by whether they experienced MARCE.

Separately for SOT and non-SOT patients, the association between each sex-age strata (relative to males 18-45 years) and MARCE was evaluated using a multivariable Cox proportional hazards model adjusting for the covariates indicated above (with time since transplant and organ type in the SOT group). For those with SOT, time to MARCE within 90 days after COVID-19 diagnosis was displayed graphically using Kaplan Meier survival curves for each sex-age strata.

1. Using multivariable Cox proportional hazards models adjusting for the above covariates, we examined the adjusted hazard ratio for each sex-age strata separately on MACE, AKI, organ rejection and mortality. To determine the association between sex-age strata and COVID-19 severity as a binary outcome (severity ≥ moderate [hospitalized], severe [hospitalized and ventilated] or death with COVID-19), 23 we used multivariable logistic regression, again adjusting for the covariates listed above. Again, these analyses were repeated for non-SOT patients as a comparator group (except for the outcome of organ rejection).

2. An overall analysis of the entire cohort (SOT and non-SOT) with SOT status included in the regression was performed to determine the independent association of SOT status with (i) MARCE, (ii) MACE, (iii) AKI, (iv) death from any cause, and (v) COVID-19 disease severity.

3. The primary analysis described above was repeated using organ- without SOT and (ii) those with a kidney transplant (to allow for comparison of rejection risk). Finally, we explored potential sexbased differences in each primary and secondary outcome, stratified by allograft type, to determine if allograft type modified the association of recipient sex on post-COVID outcomes. We used random-effects meta-regression using aggregate-level data for each organ type. Heterogeneity in outcome between transplant allograft types was evaluated by Higgins I 2 and the chi-square test of heterogeneity.

All statistical analyses were performed using R built in the N3C Enclave.

Over the study period, we identified 10 987 SOT patients and Figure S3 ). (Table S1 ). Kaplan-Meier curves examining time to MARCE in SOT recipients are shown in Figure 2B . (Table S2) . When we evaluated the adjusted impact of sex and age on each endpoint, SOT males and females had similar age-stratified risk profiles with overlapping confidence intervals in most cases for each of the five endpoints ( Figure 4A ). Conversely, in the non-SOT cohort, within each age strata, female sex was protective against all outcomes ( Figure 4B ). 

We examined the risk of each primary and secondary outcome stratified by organ type relative to those without SOT ( Figure S4 ), and relative to those with a kidney transplant only ( Figure 5A ). Figure S4 ). Heterogeneity between organ types was high for all outcomes except death (I 2 > 80%). In most cases, kidney transplant patients were at the highest relative risk; however, there were no organ-specific differences in death risk, and heart transplant recipients experienced significantly more MACE ( Figure 5A ). Importantly, organ rejection was significantly higher in those with a lung ( Finally, we assessed the potential impact of the specific type of organ transplanted for the association of age and sex with MARCE (Tables S4A-D) , examining the overall risk in females versus males for each primary and secondary outcome (including organ rejection) by organ type ( Figure 5B ). Females with a kidney transplant were at lower risk than males for all outcomes except hospitalization and rejection. There were no sex-based differences noted in any of the other organ systems and no sex-based heterogeneity for any outcome (p-value >.05 for all analyses). When stratifying by age, there were no significant age-sex associations with MARCE in any of the individual organ types (Table S5 ). included kidney, liver, lung, and heart transplant recipients, but did not compare results by organ type. 31 A much smaller cohort study of Spanish SOT recipients failed to demonstrate any organ-specific differences in COVID-19 outcomes; however, included less than 100 liver, lung, and heart recipients combined and was thus underpowered for this comparison. 32 In the absence of SARS-CoV-2 infection, lung transplant recipients have the highest posttransplant mortality rate, followed by heart, liver, and kidney recipients. 17 However, the cumulative probability of cardiovascular disease has been shown to be significantly higher in heart and kidney transplant recipients (excess absolute risk [EAR] 458.3/10 000 person-years for heart recipients and 86.2/10 000 person-years for kidney recipients), compared to 26.6/10 000 person-years in liver transplant recipients. 17 This may explain the higher risk of MARCE, MACE and hospitalization we demonstrate in kidney and heart transplant recipients compared to liver and lung recipients, especially given the known compound effects of COVID-19 on the cardiovascular system. 33 However, we

show that all organ transplant types (including liver) have worse COVID-19 outcomes than the non-SOT comparator population, contrary to earlier studies demonstrating liver transplant to be protective. 29, 30 Finally, in our study, lung and heart transplant recipients were at highest risk for organ rejection in the 90 days after COVID-19 diagnosis. This may relate to systemic differences in immunosuppression and immunogenicity between organ types; lung and heart allografts evoke a stronger immune response than kidney, and especially, liver allografts. 34 Interestingly, females were at lower risk than males for MARCE, MACE, death and AKI if they had a kidney transplant; however, there were no sex-based differences for any other organ type.

Furthermore, in the 90 days after COVID diagnosis, there was no sex bias in hospitalization or rejection rates for any transplant type, despite females without COVID-19 being higher risk for SOT rejection. 35 Our study investigates the impact of sex and age in a complex patient population at high risk for infections and resulting infectious complications. [36] [37] [38] [39] In the general population, males have a significantly higher COVID-19-related mortality than females do. 3, 5 Estradiol is generally immune enhancing and testosterone immune suppressing 40 thus in the immunocompetent state, females have a more robust anti-viral immune response than males. 41 As endogenous steroids decrease with advancing age (rapidly in post-menopausal females and more gradually in males) there is a parallel functional decline in the immune system, 42 which may explain the attenuated benefit we demonstrate for the first time in aging non-SOT females versus males in response to COVID-19 ( Figure 2 ). "Inflam-aging" refers to a decline in adaptive immunity and a dysregulated activation of the innate immune system with advancing age. 43 This is more prominent in older males than females (though effects both sexes) and is associated with an increased risk of cytokine storm following SARS-CoV-2 infection and thereby, COVID-19 related death. 5

Hyperinflammation following SARS-CoV-2 infection has also been proposed to contribute to vascular inflammation and plaque instability, with resulting myocardial infarction, cardiomyopathy and heart | 11

AJT VINSON et al. failure 44, 45 ; further contributing to the increased risk of COVID-19 related cardiovascular morbidity in older immunocompetent males compared with females.

These sex disparate outcomes have not been previously observed in the SOT population. 7, 10, 13, 16, [18] [19] [20] In our study, we demonstrate for the first time that SOT males with COVID-19 also have an increased risk of MARCE compared with females, albeit to a lesser degree than in the general population (11% vs. 39% reduction in the hazard of MARCE with female vs. male sex in SOT and non-SOT cohorts, respectively). In SOT recipients, maintenance immunosuppression may have a differential impact on this result was again only significant in male patients.

In the non-SOT population, differences by sex were most pronounced in the youngest (reproductive) age strata, followed by midage (peri-menopause/andropause), and finally by the oldest group we provide a novel analysis of differential COVID-19 outcomes in SOT recipients by allograft type. This research was possible because of the patients whose information is included within the data and the organizations (see covid.

cd2h.org) and scientists who have contributed to the ongoing development of this community resource. The contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health.

The authors thank the following N3C core teams for their contri- 

All diagnostic, medication, procedure, and laboratory concepts and raw code (R, Python, SQL) used in this study are available in a GitHub repository. N3C is a public resource maintained by NCATS to support COVID-19 research. Investigators can request access to the Enclave here.

) Workstream, subgroup and administrative leaders

) Key liaisons at data partner sites

) Phenotype Team (Individuals who create the scripts that the sites use to submit their data, based on the COVID and Long COVID definitions

Analytics Team (Individuals who build the Enclave infrastructure, help create codesets, variables, and help Domain Teams and project teams with their datasets

Publication Committee Review Team: Carolyn Bramante

Amit Saha, Satyanarayana Vedula. Data partners with released data

Advocate Health Care Network-UL1TR002389: The Institute for Translational Medicine (ITM). OCHIN-INV-018455: Bill and Melinda Gates Foundation grant to Sage Bionetworks. Additional data partners who have signed DTA and data release pending

The University of Texas Health Science Center at Houston-UL1TR003167: Center for Clinical and Translational Sciences (CCTS). NorthShore University HealthSystem-UL1TR002389: The Institute for Translational Medicine (ITM). Yale New Haven Hospital-UL1TR001863

#N/A-UL1TR001445: Langone Health's Clinical and Translational Science Institute. Children's Hospital of Philadelphia-UL1TR001878: Institute for Translational Medicine and Therapeutics

University of California, Irvine-UL1TR001414: The UC Irvine Institute for Clinical and Translational Science (ICTS)

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