Temporal Reduction in COVID-19-Associated Fatality Among Kidney Transplant Recipients: The Brazilian COVID-19 Registry Cohort Study

Abstract

Graphical Abstract:

Graphical Abstract

Introduction

Over the past year, the coronavirus disease 2019 (COVID-19) global pandemic has been responsible for more than 126 million cases of severe acute respiratory syndrome worldwide and over 2.76 million deaths. With large numbers of COVID cases, Brazil has become an epicenter of the COVID-19 outbreak in the world (1, 2). Among many specific vulnerable groups affected by SARS-COV-2 infection, transplant immunocompromised recipients represent a recognized high-risk group for this infection (3).

Although to date there is still no specific treatment for COVID-19, several pharmacological and non-pharmacological strategies have been explored to improve the clinical outcomes. Among these strategies, the following are noteworthy: 1) the use of prehospital pulse oximetry to early detect silent hypoxemia (4); 2) the important role of non-invasive mechanical ventilation often avoiding unnecessary early intubation (5); 3) prone position to improve oxygenation in intubated and non-intubated patients with COVID-19-related acute respiratory distress syndrome (6, 7); 4) anticoagulant treatment in patients with coagulopathy (8); and 5) corticosteroids in patients with severe disease (9).

Data from the general population suggest an improvement in survival rates during the pandemic, mainly among critically ill patients (10–13). Multicenter national studies have reported COVID-19-related fatality rates varying from 20.5 to 32% among hospitalized kidney transplant (KT) patients (14–18), but no study evaluated the impact of the timing on deaths in this population.

In this analysis of the multicenter national Brazilian registry of SARS-CoV-2 infection study, we aimed to assess fatality rates over the first 6 months of pandemic and to explore whether demographics, clinical profile, and in-hospital management of COVID-19 were associated with trends in the outcomes.

Materials and Methods

Study Design

This is an ongoing multicenter national Brazilian registry of SARS-CoV-2 infection among kidney transplant recipients (ClinicalTrials.gov: NCT04494776) (19). For this analysis, we extracted data of patients with COVID-19-related signs and symptoms and SARS-CoV-2 detected by reverse-transcription polymerase chain reaction (RT-PCR) of a respiratory sample, between 3rd March and 31st August 2020, who required hospitalization, totalizing 878 patients from 35 transplant centers of four Brazilian Regions (615 from the Southeast, 124 Northeast, 111 South, and 28 from the Midwest). Patients were followed for 3 months after the diagnosis or until death or graft loss, and the end-of-study data was 30th November 2020.

Variables

Patient age, gender, ethnicity, and body mass index were collected and included in the analysis. Comorbidities comprised the following conditions: hypertension, diabetes, cardiovascular, pulmonary, neurological or hepatic diseases, current or previous neoplasia, and autoimmune disease. The following clinical presentation parameters were also included in the analysis: fever and/or chills, cough, dyspnea, myalgia, diarrhea, headache, fatigue and or/asthenia, runny nose, and nausea and/or vomiting. Data related to KT such as donor source, end-stage kidney disease (ESKD) etiology, time after transplantation, baseline renal function, maintenance immunosuppressive (IS) drugs, steroid (ST) pulse therapy <3 months, use of rabbit antithymocyte globulin (rATG) <3 months were analyzed.

The following laboratory exams at admission were recorded: lymphocytes count, hemoglobin, platelets count, C-reactive protein, lactic dehydrogenase, aspartate transaminase; alanine transaminase; creatine phosphokinase, serum sodium, ferritin, serum creatinine. Chest radiography and/or computed tomography at admission were used to classify pulmonary abnormalities.

The following treatments available in the registry were analyzed: antibiotics, particularly azithromycin, high-dose steroids, prophylactic or therapeutic use of anticoagulants, and use of oseltamivir, ivermectin, and chloroquine or hydroxychloroquine.

The analysis of outcomes in COVID-19 transplant recipients across time was carried out considering fatality rates and the following variables: invasive mechanical ventilation, intensive care unit admission, and development of AKI with dialysis requirement.

Definitions

The COVID-19-associated fatality rate was defined as the percentage of deaths that occurred in patients with confirmed SARS-CoV-2 infection. Hospital admission criteria and the use of pharmacological and non-pharmacological treatments were at the discretion of each of the participating centers. The definition of “high-dose steroids” was at the center discretion, according to their local practices.

We considered as the index case the first KT patient diagnosed with COVID-19 and included in the Brazilian Kidney Transplant COVID-19 Registry (March 3rd, 2020). The sample was divided into quartiles, as demonstrated in Figure 1: Q1: patients diagnosed <72 days after the index case (n = 227); Q2: 72–104 days (n = 214); Q3: 105–140 days (n = 219); Q4: >140 days (n = 218).

FIGURE 1

Baseline serum creatinine (sCr) was defined as the last three available sCr measurements before COVID-19 infection. Glomerular filtration rate (eGFR) was estimated by the CKD-EPI formula. Delta sCr (Δ sCr) was the difference between admission and baseline sCr values. Acute kidney injury (AKI) was defined as a rise in sCr of ≥50% from its baseline value (20). Graft loss was defined as the return to long-term dialysis therapy or retransplantation.

Statistical Analysis

Categorical variables were presented as frequency and percentage. All continuous variables were non-normally distributed and were summarized as median and interquartile range (IQR). Trend analyses comparing data across the quartiles were performed using Cochran–Armitage test for categorical variables, and Jonckheere-Terpstra test for numerical variables. Survival curves were obtained using Kaplan-Meier method and compared using the log-rank test. Univariable and multivariable analyses to identify independent risk factors associated with death were performed using Cox regression, with center-based random effects (frailty model). Collinear variables, and those poorly associated with death in univariable analysis (p > 0.15) were excluded from the multivariable model. No variable exceeded 5% of missing values and Multiple Imputation by Chained Equation (MICE) was used to replace missing data values, as follows: 1) generating replacement values (“imputations”) for missing data and repeating this procedure 10 times, 2) analyzing the 10 imputed data sets, and 3) combining (pooling) the results using Rubin’s Rules (21). A significantly statistical difference was assumed when the p-value was less than 0.05. Statistical analysis was performed using the IBM SPSS 25 and R 4.0.2.

Results

Demographic Characteristics Across the Quartiles

The baseline demographic characteristics at COVID-19 diagnosis are shown in Table 1. Changes in patients’ clinical profile occurred over time, with a significant reduction in age, and in the percentage of patients with ≥3 comorbidities.

The Clinical Presentation Across the Quartiles

The analysis across quartiles showed a decrease in the proportion of patients with dyspnea and hypoxemia at diagnosis, whereas myalgia, diarrhea, and headache progressively increased. Although the time from the onset of COVID-19 symptoms to diagnosis remained stable over time (median 6 days; IQR 3–9), a longer time until hospitalization since symptoms onset was observed, increasing from Q1 (median 5 days, IQR 2–9) to Q4 (median 6 days, IQR 3–10) (p_for-trend = 0.005) (Figure 2).

FIGURE 2

Laboratory data and chest radiological findings at COVID-19 diagnosis are shown in Supplementary Table S1. An increase in the percentage of patients with normal chest radiological evaluation was observed from Q1 (2.1%) to Q4 (6.7%) (p_for-trend = 0.015).

Immunosuppression and Pharmacological Treatment Across the Quartiles

Complete immunosuppressive drug withdrawal decreased from Q1 to Q4 (from 43.6 to 30.3%, p_for-trend = 0.003), while no significant changes were observed in the percentage of patients submitted to withdrawal or reduction of the antiproliferative or calcineurin inhibitors agents, or no intervention on the immunosuppressive regimen (Figure 3A).

FIGURE 3

Regarding the pharmacological treatments, there was an increase in the use of antibiotics, high-dose steroids, prophylactic use of anticoagulants, and ivermectin, while the use of azithromycin, oseltamivir, chloroquine, or hydroxychloroquine decreased from Q1 to Q4 (Figure 3B).

The Outcomes Across the Quartiles

The 28-day fatality rate was 24.6% (n = 216), with a significant downward trend over time, from 29.5% in Q1 to 18.3% in Q4 (log rank = 0.027, p_for-trend = 0.004) (Figures 4A,B).

FIGURE 4

Causes of death within 28 days included septic shock (60.2%), acute respiratory failure (21.8%), cardiovascular or embolic event (5.1%), and in 13% the cause of death was not clearly defined nor registered. No difference in the distribution of the causes of death occurred from Q1 to Q4 (p_for-trend = 0.677). Although 69.5% of deaths occurred in the first 28 days, the median time from COVID-19 diagnosis to death increased from 17 days (Q1) to 25 days (Q4) (p_for-trend = 0.035). Within the 90-day follow-up, the overall fatality rate was 35.4% (n = 311), with a non-significant downward trend from 39.2 to 31.2% (Log-rank = 0.208, p_for-trend = 0.073) (Supplementary Figure S1). Causes of death within 90 days were similar to that described for 28 days.

No changes were observed in the percentage of patients receiving invasive mechanical ventilation. However, the time from the onset of symptoms to orotracheal intubation increased from 8 to 11 days in median (p_for-trend = <0.001), and fewer patients were admitted to intensive care units (ICU) over time (from 62.1 to 49.5%, p_for-trend = 0.038) (Figures 5A,B). No significant trend was observed in the percentage of patients requiring dialysis therapy (Figure 5C).

FIGURE 5

Fourteen (1.6%) patients lost the graft within the 90 days follow-up, most of them with advanced chronic kidney disease at the time of COVID-19 diagnosis (median baseline eGFR 16.9 ml/min/1.73 m², IQR, 9.5–24.3) (Supplementary Table S2). Figure 5D shows the 28 and 90-day fatality rates in patients requiring dialysis therapy, ICU admission, and invasive mechanical ventilation.

Patients with COVID-19 diagnosis 140 days after the index case (Q4) showed a 35% reduction risk in 28-day mortality (HR 0.65, 95% CI 0.44–0.97, p = 0.037). Each month after March 3rd was associated with 10% reduction in the fatality (HR 0.90, 95% CI 0.82–0.99), p = 0.024). Age and presence of three or more comorbidities in addition to chronic kidney disease were also risk factors associated with increased risk of death, whereas the use of mTOR inhibitor and the increasing baseline glomerular filtration rate were associated with decreased risk of death (Table 2; Supplementary Table S3). The impact of timing on 90-day fatality was not clearly demonstrated (Supplementary Table S4).

Discussion

This national multicenter cohort suggests that COVID-19-associated fatality decreased over the first 6 months after the beginning of the pandemic. Changes in the demographic profile of infected patients, in the clinical presentation at diagnosis, and in pharmacological and non-pharmacological treatment options might explain this result.

The overall fatality rate was high and similar to that described in international published cohorts (15, 16, 18, 22). As a novelty, this cohort showed that the cumulative incidence of death within 28 days after diagnosis significantly decreased over time, and deaths occurred later. Changes in the demographic profile, mainly the reduction in the percentage of patients with multiple comorbid conditions, probably contributed to this finding, since the number of comorbidities was an independent risk factor for death (3). Despite the statistically significant trend for higher BMI over time, we believe that this finding is not clinically relevant. The reasons for the changes in the demographic profile over the months are not clear. The wide dissemination of the worst prognosis on the elderly, and patients with comorbidities might have resulted in intensification of protective measures in these individuals.

Other factors that might have impacted outcomes were the changes in the recommendations of the health care organizations, the higher availability of diagnostics tests, and the learning curve about disease diagnosis and management, leading to earlier and broader diagnosis, properly referred hospitalization, or better management of pharmacological and non-pharmacological interventions. In fact, the reduction in the percentage of patients with dyspnea, hypoxemia, and radiological chest findings suggest earlier demand for medical assistance, earlier clinical suspicion and diagnosis, and/or earlier hospitalization. The median time until intubation was prolonged by 3 days, suggesting improvements in the optimal use of non-invasive ventilation techniques. Unfortunately, we did not capture information about ventilatory management before invasive mechanical ventilation. Noteworthy, the interpretation of the downward trend in ICU admission must be cautious, since the availability of ICU beds is not uniform across the country’s centers and regions (2).

Interestingly, the improvement in the 90-day fatality was not evident. We believe that the 28-day mortality rate reflects disease severity, and prompt and proper diagnosis and treatment. In turn, 90-day mortality also seems to reflect intra-hospital care, such as preventing nosocomial infections, thromboembolic events, and other adverse events related to health care, malnutrition, and immobilization. Although these processes have probably also improved over the period, our study was not empowered to show this trend.

A clear change in the pharmacological supporting treatments was observed, which might also have impacted outcomes, mainly the higher use of high-dose steroids and anticoagulants (8, 9). The retrospective nature of a registry study, the absence of data on the onset of all interventions, and the diversity of COVID-19 management protocols in our continental country preclude any definitive conclusion about the efficacy of these strategies. We could not access information of patients who did not have access to medical care. The overwhelmed health system during the peaks of the pandemic could have hindered the arrival of more severe COVID-19 patients at the hospital, leading to deaths before hospitalization. In addition, despite the homogeneous number of patients in each quartile, groups have different duration, potentially hampering to capture the workload of periods with a higher incidence of cases and the effect of overwhelmed hospitals.

As another limitation, this study was limited to the first wave of the pandemic in Brazil, and reflected the pre-vaccination period. We do not have information on the viral genotype, which also might influence the clinical presentation and outcomes. However, at that time, the variants of concern leading to potential changes in the clinical profile and patients outcomes had not been identified yet (23). The imprecise definition of death cause in more than 10% of patients also impaired a better understanding of the reasons behind the reduction in fatality rates, as well as hampered the precise distinction between related and non-related COVID deaths.

It is also notable that a lower percentage of patients had their immunosuppressive regimen completely withdrawn over the study time. Despite plenty of in vitro studies suggesting the potential benefit of immunosuppressive drugs on the clinical outcomes of coronavirus infection (24–29), no clinical study supports robust conclusions. In the multivariable analysis, the use of mTOR inhibitors in the maintenance immunosuppressive regimen was associated with lower death risk. The reduction in SARS-CoV-2 replication after the inhibition of the Akt/mTOR/HIF-1 signaling pathway was previously demonstrated by a recently published in vitro study (29). However, no conclusion in this regard is feasible considering the limitation of the study design. Finally, despite the statistically significant linearly increasing trend through time, complex dynamics observed in some variables, such as the time between COVID-19 diagnosis and hospitalization, do not necessarily reflect clinically relevant changes.

Notwithstanding the above-mentioned limitations, inherent to registry data analysis, our study has important strengths: to the best of our knowledge, this is one of the largest multicenter national registers on COVID-19 in KT patients; the national representation is consistent with site activities and with COVID-19 incidence in the Brazilian States; a robust center-adjusted analysis was performed to minimize site-effect; and the selection of hospitalized patients only, excluding patients with mild COVID-19 forms, makes our sample more homogeneous as to the initial severity criterion.

In conclusion, this study suggests that the COVID-associated fatality in KT patients requiring hospitalization improved over the six first months of the pandemic. Prospective studies are of utmost needed to better understand the impact of each intervention on outcomes.

Capsule Sentence Summary

This multicenter national Brazilian study accessed the fatality rates of COVID-19 among kidney transplanted patients over the first 6 months after the beginning of the pandemic. Using trend analysis, we could observe a decrease in the fatality rates from March to August 2020. A center-adjusted analysis was performed to explore the reasons for the improvement in the outcomes. Differences in demographics, clinical presentation, and treatment options might be involved in this trend.

The COVID-19-KT Brazil Study Group

Beyond the authors, the COVID-19-KT Brazil Study Group includes the following participants: Roger Kist⁸, Aline Lima Cunha Alcântara², Maria Luiza de Mattos Brito Oliveira Sales³, Mario Abbud Filho⁹, Katia Cronenberge Sousa¹⁰, Roberto Ceratti Manfro¹¹, Tomás Pereira Júnior¹², Maria Eduarda Heinzen de Almeida Coelho¹³, Marilda Mazzali²¹, Marcos Vinicius de Sousa²¹, Juliana Bastos Campos¹⁴, Nicole Gomes Campos Rocha¹⁵, Tania Leme da Rocha Martinez¹⁷, Joao Egidio Romao Junior¹⁷, Maria Regina Teixeira Araújo¹⁷, Sibele Lessa Braga¹⁷, Marcos Alexandre Vieira¹⁶, Elen Almeida Romão²², Miguel Moysés Neto²², Juliana Aparecida Zanocco²³, Auro Buffani Claudino²³, Gustavo Guilherme Queiroz Arimatea¹⁹, Tereza Azevedo Matuck²⁰, Alexandre Tortoza Bignelli²⁴, Maria Ferneda Puerari²⁴, José Hermógenes Rocco Suassuna²⁵, Suzimar da Silveira Rioja²⁵, Rafael Lage Madeira²⁶, Sandra Simone Vilaça²⁶, Carlos Alberto Chalabi Calazans²⁷, Daniel Costa Chalabi Calazans²⁷, Patricia Malafronte²⁸, Luiz Antonio Miorin²⁸, Larissa Guedes da Fonte Andrade²⁹, Filipe Carrilho de Aguiar²⁹, Fabiana Loss de Carvalho Contieri³⁰, Karoline Sesiuk Martins³⁰, Helady Sanders Pinheiro³¹, Emiliana Spadarotto Sertório³¹, André Barreto Pereira³², David Jose⁹; Barros Machado³³, Carolina Maria Pozzi³⁴, Leonardo Viliano Kroth³⁴, Lauro Monteiro Vasconcellos Filho³⁶, Rafael Fabio Maciel³⁷, Amanda Maíra Damasceno Silva³⁸, Ana Paula Maia Baptista³⁹, Pedro Augusto Macedo de Souza⁴⁰, Marcus Lasmar⁴¹, Luciana Tanajura Santamaria Saber⁴², Lilian Palma⁴³.

²¹Hospital de Clínicas da Universidade de Campinas-UNICAMP, Campinas, SP, Brazil; ²²Divisão de Nefrologia, Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), Ribeirão Preto, SP, Brazil; ²³Hospital Santa Marcelina, São Paulo, SP, Brazil; ²⁴Hospital Universitário Cajuru, Curitiba, PR, Brazil; ²⁵Hospital Universitário Pedro Ernesto, Rio de Janeiro, RJ, Brazil; ²⁶Hospital Felício Rocho, Belo Horizonte, BH, Brazil; ²⁷Hospital Marcio Cunha, Ipatinga, MG, Brazil; ²⁸Santa Casa de Misericórdia de São Paulo, São Paulo, SP, Brazil; ²⁹Hospital das Clínicas da UFPE Universidade Federal de Pernambuco, Recife, PE, Brazil; ³⁰Hospital do Rocio, Campo Largo, PR, Brazil; ³¹Hospital Universitário da Universidade Federal de Juiz de Fora, Juiz de Fora, MG, Brazil; ³²Hospital Marieta Konder Bornhausen, Itajai, SC, Brazil; ³³Hospital Alemão Osvaldo Cruz, São Paulo, SP, Brazil; ³⁴Hospital Evangélico, Curitiba, PR, Brazil; ³⁵Hospital São Lucas da PUCRS, Porto Alegre, RS, Brazil; ³⁶Hospital Meridional, Cariacica, ES, Brazil; ³⁷Hospital Nossa Senhora das Neves, João Pessoa, PB, Brazil; ³⁸Hospital Antonio Targino, Campina Grande, PB, Brazil; ³⁹Hospital São Rafael, Salvador, BA, Brazil; ⁴⁰Santa Casa de Misericórdia de Belo Horizonte, Belo Horizonte, MG, Brazil; ⁴¹Hospital Universitário Ciências Médicas, Belo Horizonte, MG, Brazil; ⁴²Santa Casa de Misericórdia de Ribeirão Preto, Ribeirão Preto, SP, Brazil; ⁴³Centro Médico de Campinas, Campinas, SP, Brazil.

References

• 1.

  World Health Organization. WHO Coronavirus (COVID-19) Dashboard. Available at: https://covid19.who.int/ (Accessed March 28, 2021).

  • Google Scholar

• 2.

  Ranzani OT Bastos LSL Gelli JGM Marchesi JF Baião F Hamacher S et al Characterisation of the First 250000 Hospital Admissions for COVID -19 in Brazil: A Retrospective Analysis of Nationwide Data. Lancet Respir Med (2021). 9(4):407–18. 10.1016/S2213-2600(20)30560-9

  • CrossRef
  • Google Scholar

• 3.

  Williamson EJ Walker AJ Bhaskaran K Bacon S Bates C Morton CE et al Factors Associated with COVID-19-Related Death Using OpenSAFELY. Nature (2020). 584(7821):430–6. 10.1038/s41586-020-2521-4

  • CrossRef
  • Google Scholar

• 4.

  Jouffroy R Jost D Prunet B Prehospital Pulse Oximetry: a Red Flag for Early Detection of Silent Hypoxemia in COVID-19 Patients. Crit Care (2020). 24(1):313. 10.1186/s13054-020-03036-9

  • CrossRef
  • Google Scholar

• 5.

  Walker J Dolly S Ng L Prior-Ong M Sabapathy K The Role of CPAP as a Potential Bridge to Invasive Ventilation and as a Ceiling-of-Care for Patients Hospitalized with Covid-19-An Observational Study. PLoS One (2020). 15(12):e0244857. 10.1371/journal.pone.0244857

  • CrossRef
  • Google Scholar

• 6.

  Alhazzani W Møller MH Arabi YM Loeb M Gong MN Fan E et al Surviving Sepsis Campaign: Guidelines on the Management of Critically Ill Adults with Coronavirus Disease 2019 (COVID-19). Intensive Care Med (2020). 46(5):854–87. 10.1007/s00134-020-06022-5

  • CrossRef
  • Google Scholar

• 7.

  Sztajnbok J Maselli-Schoueri JH Cunha de Resende Brasil LM Farias de Sousa L Cordeiro CM Sansão Borges LM et al Prone Positioning to Improve Oxygenation and Relieve Respiratory Symptoms in Awake, Spontaneously Breathing Non-intubated Patients with COVID-19 Pneumonia. Respir Med Case Rep (2020). 30:101096. 10.1016/j.rmcr.2020.101096

  • CrossRef
  • Google Scholar

• 8.

  Tang N Bai H Chen X Gong J Li D Sun Z Anticoagulant Treatment is Associated with Decreased Mortality in Severe Coronavirus Disease 2019 Patients with Coagulopathy. J Thromb Haemost (2020). 18(5):1094–9. 10.1111/jth.14817

  • CrossRef
  • Google Scholar

• 9.

  Horby P Lim WS Emberson JR Mafham M Bell JL Linsell L et al Dexamethasone in Hospitalized Patients with Covid-19 - Preliminary Report. N Engl J Med (2020). 84(8):693–704. 10.1056/NEJMoa2021436

  • CrossRef
  • Google Scholar

• 10.

  Horwitz LI Jones SA Cerfolio RJ Francois F Greco J Rudy B et al Trends in COVID-19 Risk-Adjusted Mortality Rates. J Hosp Med (2021). 16(2):90–2. 10.12788/jhm.3552

  • CrossRef
  • Google Scholar

• 11.

  Auld SC Caridi-Scheible M Robichaux C Coopersmith CM Murphy DJ , Emory COVID-19 Quality and Clinical Research Collaborative. Declines in Mortality over Time for Critically Ill Adults with Coronavirus Disease 2019. Crit Care Med (2020). 48(12):e1382–e1384. 10.1097/ccm.0000000000004687

  • CrossRef
  • Google Scholar

• 12.

  Dennis JM McGovern AP Vollmer SJ Mateen BA Improving Survival of Critical Care Patients With Coronavirus Disease 2019 in England: A National Cohort Study, March to June 2020*. Crit Care Med (2021). 49(2):209–14. 10.1097/ccm.0000000000004747

  • CrossRef
  • Google Scholar

• 13.

  Garcia-Vidal C Cózar-Llistó A Meira F Dueñas G Puerta-Alcalde P Cilloniz C et al Trends in Mortality of Hospitalised COVID-19 Patients: A Single centre Observational Cohort Study from Spain. Lancet Reg Health Eur (2021). 3:100041. 10.1016/j.lanepe.2021.100041

  • CrossRef
  • Google Scholar

• 14.

  Cravedi P Mothi SS Azzi Y Haverly M Farouk SS Pérez‐Sáez MJ et al COVID‐19 and Kidney Transplantation: Results from the TANGO International Transplant Consortium. Am J Transpl (2020). 20(11):3140–8. 10.1111/ajt.16185

  • CrossRef
  • Google Scholar

• 15.

  Caillard S Anglicheau D Matignon M Durrbach A Greze C Frimat L et al An Initial Report from the French SOT COVID Registry Suggests High Mortality Due to COVID-19 in Recipients of Kidney Transplants. Kidney Int (2020). 98(6):1549–58. 10.1016/j.kint.2020.08.005

  • CrossRef
  • Google Scholar

• 16.

  Favà A Cucchiari D Montero N Toapanta N Centellas FJ Vila‐Santandreu A et al Clinical Characteristics and Risk Factors for Severe COVID‐19 in Hospitalized Kidney Transplant Recipients: A Multicentric Cohort Study. Am J Transpl (2020). 20(11):3030–41. 10.1111/ajt.16246

  • CrossRef
  • Google Scholar

• 17.

  Hilbrands LB Duivenvoorden R Vart P Franssen CFM Hemmelder MH Jager KJ et al COVID-19-Related Mortality in Kidney Transplant and Dialysis Patients: Results of the ERACODA Collaboration. Nephrol Dial Transpl (2020). 35(11):1973–83. 10.1093/ndt/gfaa261

  • CrossRef
  • Google Scholar

• 18.

  Kates OS Haydel BM Florman SS Rana MM Chaudhry ZS Ramesh MS et al COVID-19 in Solid Organ Transplant: A Multi-Center Cohort Study. Clin Infect Dis (2020). 73(11):e4090–e4099. 10.1093/cid/ciaa1097

  • CrossRef
  • Google Scholar

• 19.

  Requião-Moura LR Sandes-Freitas TVd. Viana LA Cristelli MP Andrade LGMd. Garcia VD et al High Mortality Among Kidney Transplant Recipients Diagnosed with Coronavirus Disease 2019: Results from the Brazilian Multicenter Cohort Study. PLoS One (2021). 16(7):e0254822. 10.1371/journal.pone.0254822

  • CrossRef
  • Google Scholar

• 20.

  Khwaja A KDIGO Clinical Practice Guidelines for Acute Kidney Injury. Nephron (2012). 120(4):c179–c184. 10.1159/000339789

  • CrossRef
  • Google Scholar

• 21.

  Rubin DB . Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons (1987).

  • Google Scholar

• 22.

  Cravedi P Suraj SM Azzi Y Haverly M Farouk S Perez-Saez MJ et al COVID-19 and Kidney Transplantation: Results from the TANGO International Transplant Consortium. Am J Transpl (2020). 20(11):3140–8. 10.1111/ajt.16185

  • CrossRef
  • Google Scholar

• 23.

  Tegally H Wilkinson E Giovanetti M Iranzadeh A Fonseca V Giandhari J et al Emergence of a SARS-CoV-2 Variant of Concern with Mutations in Spike Glycoprotein. Nature (2021). 592:438–43. 10.1038/s41586-021-03402-9

  • CrossRef
  • Google Scholar

• 24.

  Chen X Chou C-Y Chang G-G Thiopurine Analogue Inhibitors of Severe Acute Respiratory Syndrome-Coronavirus Papain-Like Protease, a Deubiquitinating and deISGylating Enzyme. Antivir Chem Chemother (2009). 19(4):151–6. 10.1177/095632020901900402

  • CrossRef
  • Google Scholar

• 25.

  Hart BJ Dyall J Postnikova E Zhou H Kindrachuk J Johnson RF et al Interferon-β and Mycophenolic Acid Are Potent Inhibitors of Middle East Respiratory Syndrome Coronavirus in Cell-Based Assays. J Gen Virol (2014). 95(Pt 3):571–7. 10.1099/vir.0.061911-0

  • CrossRef
  • Google Scholar

• 26.

  Carbajo-Lozoya J Müller MA Kallies S Thiel V Drosten C von Brunn A Replication of Human Coronaviruses SARS-CoV, HCoV-NL63 and HCoV-229E is Inhibited by the Drug FK506. Virus Res (2012). 165(1):112–7. 10.1016/j.virusres.2012.02.002

  • CrossRef
  • Google Scholar

• 27.

  Carbajo-Lozoya J Ma-Lauer Y Malešević M Theuerkorn M Kahlert V Prell E et al Human Coronavirus NL63 Replication is Cyclophilin A-Dependent and Inhibited by Non-immunosuppressive Cyclosporine A-Derivatives Including Alisporivir. Virus Res (2014). 184:44–53. 10.1016/j.virusres.2014.02.010

  • CrossRef
  • Google Scholar

• 28.

  Pfefferle S Schöpf J Kögl M Friedel CC Müller MA Carbajo-Lozoya J et al The SARS-Coronavirus-Host Interactome: Identification of Cyclophilins as Target for Pan-Coronavirus Inhibitors. PLoS Pathog (2011). 7(10):e1002331. 10.1371/journal.ppat.1002331

  • CrossRef
  • Google Scholar

• 29.

  Appelberg S Gupta S Svensson Akusjärvi S Ambikan AT Mikaeloff F Saccon E et al Dysregulation in Akt/mTOR/HIF-1 Signaling Identified by Proteo-Transcriptomics of SARS-CoV-2 Infected Cells. Emerg Microbes Infect (2020). 9(1):1748–60. 10.1080/22221751.2020.1799723

  • CrossRef
  • Google Scholar