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Original Clinical Science—General

Outcomes of COVID-19 in Solid Organ Transplant Recipients: A Propensity-matched Analysis of a Large Research Network

Hadi, Yousaf B. MD1; Naqvi, Syeda F.Z. MD2; Kupec, Justin T. MD1; Sofka, Sarah MD3; Sarwari, Arif MD3

Author Information
doi: 10.1097/TP.0000000000003670



The systemic illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or coronavirus disease 2019 (COVID-19), has taken the shape of a major international health crisis.1 Some data on COVID-19 outcomes in the population of solid organ transplant (SOT) recipients are available; however, it is unclear if these patients fare better or worse compared with nontransplant patients.

The scientific data available suggest that host tissue damage due to COVID-19 is mediated by both the virus-related pathogenic effects and the immune-mediated host response to the virus.2 In patients who are immunocompromised, such as SOT patients, there is reported concern for worse outcomes and high mortality.3 As a hyperreactive innate immune response may be linked to adverse COVID-19 outcomes, immunosuppression (such as that received by transplant patients) can be postulated to reduce the risk of severe disease. In contrast, transplanted patients suffer from a large comorbidity burden of heart disease, diabetes, advancing age, among others, which have previously been shown to pose a risk of worse outcomes.4 Previous studies on COVID-19 in SOT recipients are limited by sample size and by their focus on hospitalized patients.3 We conducted a large propensity-matched study to compare clinical outcomes of COVID-19 between SOT recipients and the general population.


We conducted a retrospective cohort study using the TriNETX (Cambridge, MA) platform. TriNETX platform is a multicenter federated research network of >32 Healthcare Organizations (HCOs) in the United States that provides real-time access to de-identified healthcare record data of >40 million patients from the participating healthcare organizations. HCOs included in TriNetX are generally large academic healthcare organizations that comprise tertiary care facilities and outpatient satellite clinics.

TriNetX aggregates clinical variables directly from the electronic health records of the participating institutions and also processes clinical documents through a Natural Language Processing system to extract clinical facts that are then quality assured and included in a systemic, standardized format. TriNetX has received a waiver from Western Institutional Review Board as it only provides aggregate counts and statistical summaries, including de-identified information, and does not release any personal protected health information. West Virginia University Clinical and Translational Science Institute manages the TriNetX platform at West Virginia University.

Patient Selection

A real-time search was conducted on the TriNetX platform. We included all patients with COVID-19 on the TriNetX platform who were aged >16 years at diagnosis. Patients were included if they were diagnosed with COVID-19 or received a positive test between January 20, 2020, and September 30, 2020. Selection criteria were based on diagnostic codes and positive laboratory confirmation using terminology recommended by the Centers for Disease Control and Prevention and are detailed in the Supplementary File S1 (SDC,

Patients with COVID-19 thus identified were then categorized into 2 groups based on SOT status. Transplanted organs studied in our analysis included heart, kidney, liver, and lung transplants. Patient identification period was limited from January 20, 2020, to September 30, 2020. January 20 was chosen as it was the date of diagnosis of the first case of COVID-19 in the United States. September 30 was chosen so that all patients had 2 months of follow-up available, as the primary study endpoint was a composite outcome at 30 and 60 days from diagnosis. Study search was updated on January 6, 2021.

SOT recipients were identified using the International Classification of Diseases, Ninth Revision and 10th Revision, Clinical Modification codes Z94.4; Z94.0; Z94.2, and Z94.1.

Study Outcomes

Outcomes were compared between the SOT recipients and the nontransplant group. The primary study outcome was a composite of death or mechanical ventilation in the 30- and 60-day period from index event, which was defined as the time of COVID-19 diagnosis or first COVID-19-positive test result date. Other study outcomes included mortality, hospitalization, and need for mechanical ventilation in the 30-day period from COVID-19 diagnosis and mortality in 60 days after diagnosis. Laboratory values after COVID-19 diagnosis were studied up to 7 days from COVID-19 diagnosis.

Statistical Analysis

All statistical analyses were conducted on the TriNetX platform in real time. Population and subpopulation characteristics were described using mean, SD, and proportions as appropriate. Univariate analysis was conducted using the chi-square test and independent-sample t tests for categorical and continuous data, respectively.

Propensity score matching for the study was performed within the TriNetX platform. We performed one-to-one (1:1) matching for race, age, diabetes, hypertension, chronic lung diseases, nicotine dependence, heart failure, ischemic heart disease, body mass index (BMI), and gender to identify a propensity-matched control group of nontransplant patients. Logistic regression analysis was conducted on the input matrices of covariates to calculate propensity scores. Then 1:1 matching was performed on the basis of the propensity scores using greedy nearest neighbor algorithms using a caliper width of 0.1 pooled SDs. The order of the rows was randomized to eliminate bias resulting from nearest neighbor algorithms. For the purposes of our study, a 2-sided alpha of <0.05 was defined a priori for statistical significance. Balance on covariates in the propensity-matched cohorts was assessed using standardized mean difference, and absolute values >0.1 were considered to be indicative of residual imbalance.

Risk ratios (RRs) were calculated with 95% confidence intervals (CIs) to compare outcomes between transplant and nontransplant cohorts. TriNetX obfuscates patient counts by rounding to the nearest 10 for all analyses with results in counts <10.

Subgroup analyses were conducted on hospitalized patients only and on patients with liver, kidney, lung, and heart transplants. Further details of study methodology are discussed in Supplementary File S1 (SDC,


Study Population

Of the 233 354 patients who were identified to have COVID-19 by inclusion criteria, 2307 patients (0.99%) were SOT recipients, and the remaining (231 047) were nontransplant patients.

Baseline Characteristics of Study Cohorts

At the time of COVID-19 diagnosis, the mean age was 54.3 years (SD, 14.5) in the SOT cohort, and a majority of participants were male individuals (n = 1370, 59.38%). White race was the most common, comprising 52.71% of the cohort. Transplanted organs included kidney in 1740 (75.4%) patients, liver in 418 (18.1%) patients, heart transplant in 262 (11.36%) patients, and lung transplant in 180 (7.8%) patients. Among these patients, 2042 patients had solitary SOT, while 265 patients had >1 transplanted organ; 229 of these patients had transplanted kidneys along with another organ, while the remaining had other combinations of transplanted organs.

Tacrolimus was prescribed to 1608 patients (70%) for immunosuppression during the 6-month period before COVID-19 diagnosis. Other immunosuppressive agents included mycophenolate mofetil, which was prescribed to 1074 patients (47%), while 137 patients (6%) received cyclosporine.

Male gender was more common in the SOT cohort compared with the nontransplant cohort (P < 0.01), and transplant recipient COVID patients had higher mean age (P < 0.01), and White race was more common in the nontransplant group at baseline (P = 0.03). Obesity, hypertension, diabetes, nicotine dependence, heart failure, and ischemic heart disease were more common in transplant recipients (all P < 0.001).

Geographically, 1457 patients were from southern United States (63%), 270 from the Northeast (12%), while Midwest and Western United States contributed 14% and 10% patients, respectively, to the study population.

Clinical Outcomes

Seven hundred fifteen patients with SOT (30.99%) required hospitalization in the 30-day period after COVID diagnosis, and 155 patients (6.72%) required mechanical ventilation. Intensive care services were required by 253 patients (10.97%).

In the SOT cohort, 1048 patients (45.43%) received glucocorticoids. Azithromycin was prescribed to 351 patients (15.22%), remdesivir was administered to 151 patients (6.55%), 143 patients (6.12%) received hydroxychloroquine, and 32 patients (1.39%) received tocilizumab after diagnosis of COVID-19.

Thirty-day mortality in the transplant cohort was 4.77%, and the rate of composite outcome of death or mechanical ventilation was 8.71% in the transplant cohort.

Crude 30-day mortality rate from COVID-19 diagnosis was higher in the SOT cohort as opposed to the nontransplant cohort (4.77% versus 1.94%; RR, 2.47; 95% CI, 2.05-2.96). Hospitalization within 30 days of COVID-19 diagnosis was also higher in the transplant cohort in unmatched analysis when compared with the nontransplant cohort, as was the need for mechanical ventilation, rate of acute kidney injury, and need for renal replacement therapy. In the unmatched analysis, a higher proportion of participants in the transplant group met the composite outcome of death or mechanical ventilation at both 30 and 60 days.

We performed one-to-one matching for age, diabetes, hypertension, chronic lung diseases, race, nicotine dependence, heart failure, ischemic heart disease, BMI, and gender to identify a propensity-matched control group of nontransplant patients. Baseline clinical characteristics in the 2 groups were similar after propensity score matching, with no residual imbalance (standard difference <0.1 for all covariates). These characteristics are shown in Table 1.

TABLE 1. - Comparison of demographic and clinical characteristics of COVID-19 patients with and without solid organ transplant before and after propensity score matching
Variable Before matching After matching
Solid organ transplant cohort (n = 2307) Nontransplant cohort (n = 231 047) Standard difference P Solid organ transplant cohort (2289) Nontransplant cohort (n = 2289) Standard difference P
Number Percent/SD Number Percent/SD Number Percent/SD Number Percent/SD
 Age (mean) 54.3 14.5 45.9 19.1 0.50 <0.01 54.5 14.5 55.2 15.0 0.05 0.09
 Male 1370 59.38 102 783 44.49 0.30 <0.01 1357 59.28 1399 61.12 0.04 0.20
 Female 934 40.49 127 456 55.17 0.30 <0.01 929 40.59 890 38.88 0.04 0.24
 BMI (30 and above) 795 34.46 32 715 14.16 0.49 <0.01 785 34.29 818 35.74 0.03 0.31
 Black or African American 725 31.43 47 025 20.35 0.25 <0.01 717 31.32 756 33.03 0.04 0.22
 White 1216 52.71 126 390 54.70 0.04 0.06 1207 52.73 1196 52.25 0.01 0.74
 Hispanic or Latino 406 17.60 39 040 16.90 0.02 0.37 398 17.39 371 16.21 0.03 0.29
 Asian 55 2.38 6276 2.72 0.02 0.33 55 2.40 41 1.79 0.04 0.15
 Hypertension 2125 92.11 59 722 25.85 1.82 <0.01 2107 92.05 2113 92.31 0.01 0.74
 Chronic lower respiratory diseases 682 29.56 32 955 14.26 0.38 <0.01 679 29.66 633 27.65 0.04 0.13
 Diabetes mellitus 1404 60.86 31 078 13.45 1.13 <0.01 1386 60.55 1420 62.04 0.03 0.30
 Ischemic heart disease 1013 43.91 17 364 7.52 0.92 <0.01 997 43.56 1020 44.56 0.02 0.49
 Nicotine dependence 241 10.45 14 998 6.49 0.14 <0.01 241 10.53 251 10.97 0.01 0.63
COVID-19, coronavirus disease 2019.

In the propensity score-matched analysis, no difference was noted in the 2 groups for the rate of compositive outcome of intubation or mechanical ventilation at 30 or 60 days. The hospitalization rate was higher in the transplant cohort, and a higher rate of acute kidney injury was noted in the transplant cohort. No difference was noted in mortality at 30 or 60 days postdiagnosis. Clinical outcomes in the 2 groups are compared in Table 2.

TABLE 2. - Outcomes in the 2 cohorts of COVID-19 patients with and without solid organ transplant before and after propensity score matching
Outcome Solid organ transplant group (n =  2307) Percentage Nontransplant group (n = 231 047) Percentage Risk ratio 95 % CI lower 95 % CI upper
Before propensity score matching
 Mortality within 30 d 110 4.77 4470 1.94 2.47 2.05 2.96
 Mortality within 60 d 139 6.03 5102 2.21 2.73 2.32 3.21
 Inpatient services 715 30.99 21 160 9.16 3.38 3.18 3.60
 Critical care 253 10.97 7367 3.19 3.44 3.06 3.87
 Mechanical ventilation 155 6.72 4903 2.12 3.17 2.71 3.70
 30-d composite outcome 201 8.71 7517 3.25 2.68 2.34 3.06
 60-d composite outcome 218 9.45 7929 3.43 2.75 2.42 3.13
 Acute renal injury 570 24.71 9258 4.01 6.17 5.73 6.64
 Need for renal replacement therapy 113 4.90 957 0.41 11.83 9.77 14.31
Outcome Solid organ transplant group (n = 2289) Percentage Nontransplant group (n = 2289) Percentage Risk ratio 95 % CI lower 95 % CI upper
After propensity score matching
 Mortality within 30 d 109 4.76 110 4.81 0.99 0.77 1.28
 Mortality within 60 d 138 6.03 132 5.77 1.05 0.83 1.32
 Inpatient services 709 30.97 583 25.47 1.22 1.11 1.34
 Critical care 252 11.01 217 9.48 1.16 0.98 1.38
 Mechanical ventilation 154 6.73 127 5.55 1.21 0.97 1.52
 30-d composite outcome 200 8.74 192 8.39 1.04 0.86 1.26
 60-d composite outcome 217 9.48 210 9.17 1.03 0.86 1.24
 Acute renal injury 566 24.73 327 14.29 1.73 1.53 1.96
 Need for renal replacement therapy 111 4.85 87 3.80 1.28 0.97 1.68
CI, confidence interval; COVID-19, coronavirus disease 2019.

Kaplan-Maier survival curves were plotted for mortality and composite outcome of death or mechanical ventilation for the unmatched and matched SOT and non-SOT cohorts. The log rank test revealed no difference in survival in the 2 matched groups for mortality (P = 0.46) and composite outcome (P = 0.55) (Figure 1).

Kaplan-Meier plots of composite endpoint (mortality and mechanical ventilation combined) in SARS-CoV-2 infected patients with SOT (purple) and without SOT (green), before (A) and after (B) propensity matching. SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; SOT, solid organ transplant.

There was no difference in mean C-reactive protein, bilirubin, aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, and erythrocyte sedimentation rate after COVID-19 diagnosis in the 2 matched groups; however, the transplant recipients had a higher serum mean ferritin, as shown in Table 3.

TABLE 3. - Laboratory values after COVID-19 episodes in the 2 matched and unmatched groups
Outcome Before propensity matching After propensity matching
Solid organ transplant cohort (n = 2307) Nontransplant cohort (n = 231 047) P Solid organ transplant cohort (n = 2289) Nontransplant cohort (n = 2289) P
Patients with outcome Mean (±) Patients with outcome Mean (±) Patients with outcome Mean (±) Patients with outcome Mean (±)
C-reactive protein (mg/L) 672 66.67 (80.59) 27 383 65.75 (79.36) 0.77 667 66.44 (80.34) 531 61.00 (76.00) 0.23
Lactate dehydrogenase (U/L) 580 388.47 (355.14) 21 361 420.97 (537.37) 0.15 575 388.19 (356.46) 446 414.93 (312.71) 0.21
Erythrocyte sedimentation rate (mm/h) 217 52.21 (32.19) 8549 53.11 (32.44) 0.69 215 52.41 (32.26) 182 56.84 (32.22) 0.17
Alanine aminotransferase (U/L) 1147 50.49 (227.32) 44 305 50.65 (158.78) 0.97 1135 50.71 (228.51) 777 37.78 (48.51) 0.12
Aspartate aminotransferase (U/L) 1151 82.11 (735.76) 42 906 58.19 (340.40) 0.02 1139 82.69 (739.60) 763 45.19 (61.43) 0.16
Bilirubin (mg/dL) 1130 0.73 (1.45) 44 155 0.63 (0.98) <0.01 1118 0.73 (1.45) 789 0.65 (0.89) 0.17
Ferritin (ng/mL) 613 1,743.48 (3,744.61) 24 783 981.09 (2,867.69) <0.01 608 1,746.00 (3,758.69) 506 1,188.26 (1,900.61) 0.003
Creatinine (mg/dL) 1295 2.18 (2.17) 51 719 1.18 (1.39) <0.01 1281 2.19 (2.17) 897 2.13 (2.79) 0.61
COVID-19, coronavirus disease 2019.

On a propensity-matched subgroup analysis of only hospitalized patients, no difference was observed in mortality, mechanical ventilation, or the composite outcome between transplant and nontransplant cohorts. A higher rate of acute kidney injury was noted in the transplant recipient patients. This is detailed in Table 4.

TABLE 4. - Outcomes in hospitalized patients in the 2 cohorts (propensity-matched analysis)
Outcome Solid organ transplant group (n = 707) Percentage Nontransplant group (n = 707) Percentage Risk ratio 95% CI lower 95% CI upper
After propensity score matching
 Mortality within 30 d 72 10.18 73 10.33 0.99 0.73 1.34
 Mortality within 60 d 89 12.59 88 12.45 1.01 0.77 1.33
 Critical care 219 30.98 216 30.55 1.01 0.87 1.19
 Mechanical ventilation 84 11.88 71 10.04 1.18 0.88 1.59
 30-d composite outcome 119 16.83 123 17.40 0.97 0.77 1.21
 60-d composite outcome 132 18.67 132 18.67 1.00 0.80 1.24
 Acute renal injury 316 44.70 189 26.73 1.67 1.44 1.94
 Need for renal replacement therapy 95 13.44 81 11.46 1.17 0.89 1.55
CI, confidence interval.

The outcomes in the different transplant cohorts by transplanted organ type are detailed in Table 5.

TABLE 5. - Outcomes for different organ transplant patients
Outcome Heart transplant only (n = 183), n (%) Kidney transplant only (n = 1511), n (%) Liver transplant only (n = 240), n (%) Lung transplant only (n = 108), n (%) Kidney and another organ (n = 229), n (%)
Mortality within 30 d 13 (7.10) 57 (3.77) 16 (6.99)
Inpatient services 66 (36.07) 412 (27.27) 71 (29.58) 45 (41.67) 97 (42.36)
Critical care 26 (14.21) 137 (9.07) 25 (10.42) 20 (18.52) 39 (17.03)
Mechanical ventilation 13 (7.10) 88 (5.82) 13 (5.42) 23 (10.04)
Acute renal injury 51 (27.87) 342 (22.63) 56 (23.33) 27 (25.00) 74 (32.31)
Need for renal replacement therapy 81 (5.36) 15 (6.55)
30-d composite outcome 18 (9.84) 109 (7.21) 18 (7.50) 14 (12.96) 31 (13.54)


Data currently available in scientific literature regarding COVID-19 infection in SOT recipients point toward a high morbidity and mortality among transplant recipients presenting with COVID-19.5-7 As opposed to the mortality rate of 1%–5% reported for the general population,8 the initial early studies reported early mortality rates as high as 21%–28%.6,9,10 In the initial large report by Pereira et al,3 more than half of the hospitalized transplant recipients admitted with COVID-19 infection required intubation, and a mortality rate of 18% was noted. Similarly, of the 18 SOT recipients with COVID-19 reported by Fernández-Ruiz et al,11 5 (28%) had died within a short follow-up (median: 18 d). In contrast, 1 series of 21 patients by Stephanie et al from the United States reported 1 death at a median follow-up of 18 days.12 Webb et al13 compared COVID-19 outcomes in liver transplant recipients with those without liver transplant (mostly hospitalized patients) and did not find an increase in mortality; however, more patients with transplants required intubation and intensive care unit admission.

More recently, a few larger registries have reported data on COVID-19 outcomes in SOT recipients. A French COVID Registry included 279 kidney transplant recipients with COVID-19. They reported a 30-day mortality rate of 22.8% in their cohort. Of note, all patients were included up until April 2020, and the cohort comprised mostly hospitalized patients. The Spanish Registry published by Coll et al14 reported 27% mortality in their cohort of solid organ and hematopoietic stem cell transplant patients; 89% of their cohort was derived from inpatients. The third registry from the University of Washington has reported an overall mortality of 20.5% in a multicenter cohort of 482 transplant recipients with COVID-19.15 Their study was limited to hospitalized patients only. Thus, the currently available literature points toward high mortality in SOT population with COVID-19.

Our results are in contrast to these earlier reports. We have analyzed a large cohort of patients with a history of SOT from the United States and found mostly similar outcomes in organ transplant recipients when compared with the nontransplant group after robust propensity matching. Mortality in the SOT cohort in our analysis was high; overall, 6% SOT patients died in 60 days after COVID diagnosis, and mortality was 12.59% in the hospitalized cohort of SOT patients, which was almost 3 times higher than the overall unmatched population. However, we found that this high mortality is attributable to the comorbid conditions and other risk factors in the SOT cohort, as no difference in mortality to a matched cohort was observed. Large lacunae exist in the previous literature, which likely explain these results. First, an overwhelming majority of SOT recipients reported in these studies are hospitalized patients, which has likely resulted in the selection of patients at the “severe end” of the disease spectrum; mild to moderate cases are generally managed in the outpatient setting. Our analysis eliminates this Berkson bias; in fact, only one-third of the transplant patients included in our analysis required hospitalization. No comparison with a control group of patients without SOT could be made in the earlier studies, and therefore, it could not be deduced if patients with SOT fared better or worse compared with patients without SOT. The high mortality in earlier reports cannot be attributed to transplant status itself due to lack of control for confounders and matching. Another observation is that the previous data were largely collected and reported during the first 4 months of the pandemic, and COVID-related mortality and outcomes have substantially improved since that time. One retrospective report from John Hopkins University also noted 2.5% mortality in SOT recipients with COVID that is contrary to the other reported data discussed here.16 We found higher rates of acute kidney injury in the SOT cohort even after matching, which is in keeping with prior literature.

A “cytokine storm” is attributed to clinical worsening in COVID-19, and thus, theoretically, the withdrawal of antirejection therapy can exacerbate inflammatory response.17 Conversely, the continuation of such therapy may be postulated to blunt the host response to the virus delaying its clearance. The optimal management of antirejection agents in the setting of COVID-19 infection remains unclear. Previous reports have noted a decrease in the dosage of antimetabolite agents, while other agents were less uniformly decreased.3 Furthermore, while the role of steroids in the nontransplant patient with moderate to severe disease portends a benefit, their role in this subpopulation of transplant patients is unknown. Almost half the patients in our transplant cohort received glucocorticoids.

We believe that our report has some important strengths. The sample size of most previous studies did not allow for a comparison with nontransplant populations. Because of the study design and the large sample size, we were able to conduct propensity-matched analyses with a nontransplant cohort. Our matched analysis shows that transplant status independently does not portend worse prognosis after COVID-19 disease. However, crude mortality and severe disease rates are almost 3-fold higher in patients with SOT.

The limitations of our study include its retrospective design and the biases inherent to studies conducted on electronic medical records from research networks. Standardized criteria to identify cases and limiting studied variables and outcomes to those that are less likely to suffer from any pollution introduced by documentation errors should have minimized any such bias. We were able to analyze a large sample and control for possible confounders that should strengthen the validity of our findings. As our data are derived primarily from large academic centers in the United States, generalizability to other specific populations may be limited. Furthermore, patients with asymptomatic course of infection who did not receive testing for COVID-19 remain uncaptured in our study, and thus, it can be inferred that our analysis includes a relatively more “severe” part of the disease spectrum.

In conclusion, in our large research network study, we have found that COVID-19 in SOT recipients carries high mortality and rates of poor outcomes; however, propensity-matched analyses reveal that this increased risk is secondary to higher burden of comorbidities and other risk factors of severe COVID-19 disease. Early diagnosis and intensive surveillance will be essential in this vulnerable population.


The authors acknowledge the help of the West Virginia Clinical and Translational Science Institute in providing training for data analysis on the TriNETX platform.


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