The first documented transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the UK was on 28 February. By 11 March, a pandemic was declared. The UK government acted by closing public institutions before imposing national lockdown on 23 March. By 5 May, the UK had upwards of 30 000 deaths and a mortality rate of over 41 per million.1
The devastating impact of this pandemic is seen profoundly in the renal failure population. UK Renal Registry data showed a tally of 3719 cases with 966 deaths. In comparison, the total number of patients on renal replacement therapy (RRT) was 66 612 (1.5% mortality rate as a function of total RRT patients). London, the worst affected city, has an RRT population of 14 394, with positive SARS-CoV-2 cases at 1156 and 499 deaths (unpublished data).
Bart’s Health NHS Trust, the largest trust in the country, serves 1.5 million people in the East London region with a high proportion of black, Asian, ethnic minority (BAME) population. There are in excess of 1400 transplants, 1200 hemodialysis, and 230 peritoneal dialysis patients in the renal program. We formally paused our transplant program on 24 March. At this point, the active waiting list stood at 363 patients.
The natural history of SARS-CoV-2 infections in renal transplant patients have been described in observational cohorts and case series from the UK, the USA, Europe, and Asia.2-7 These reports narrate the early experience of managing patients in respective centers. Due to the paucity of evidence, the treatments have varied from supportive therapy to the use of hydroxychloroquine, antivirals, and anti-inflammatory (steroids and interferon-β) agents. Regardless of the treatments instituted, the morbidity and mortality rates remain very high leading to most of the transplant programs either suspending or significantly reducing the transplant activity.8
In the absence of a proven curative treatment, the UK’s Public Health advocates a shielding strategy (also known as “social distancing” outside the UK).9 Identified vulnerable members of society, including RRT patients, are advised to stay at home at all times and avoid any face-to-face contact unless it to see the healthcare workers or carers as a part of their medical care.10
The dilemma the transplant community faces is in balancing the risks and benefits in a highly vulnerable group of patients, predicated on the paradigm of transplantation being the optimal RRT. The risk of contracting SARS-CoV-2 in hemodialysis patients attending thrice weekly dialysis sessions (and cumulative risk from inherent comorbidities of not being transplanted) needs to be weighed against risk of immunosuppression, especially in acute transplantation. For the latter, the risk of surgery, cardiovascular mortality, infection, and increased immunosuppression burden will be elevated for some months, before reaching equipoise. Variation in swabbing practice and frequency of hospital attendance amongst RRT patients; however, prevents accurate comparisons as the true denominators are unknown.
Thus far, the transplant experience is an extrapolation from the general population. This comparison is arguably artificial and misleading due to heterogeneity. We, therefore, undertook an observational study comparing transplanted and patients active on the waiting list at the time of suspension who were symptomatic with laboratory-confirmed SARS-CoV-2 positive swabs to report clinical characteristics and outcomes, and identify any prognostic indicators for the largest such cohort reported to date.
MATERIALS AND METHODS
All consecutive transplant and waiting list active patients in the Bart’s Health NHS Trust with a confirmed diagnosis of coronavirus disease 2019 (COVID-19) since the beginning of the pandemic till the end of April 2020 were included. The data were collected manually by review of electronic patients records, Renalware 2.0 and picture archiving and communication system. Only patients with confirmed positive nasopharyngeal reverse transcriptase-polymerase chain reaction swabs for SARS-CoV-2 RNA were included. Patients, both admitted and managed as outpatient were included. Only the patients active on the waiting lists were included in the final cohort.
No ethical approval was required, given only anonymized patient data were analyzed in an observational setting. The analysis was performed by using SPSS version 26. The normality of the data was tested using the Shapiro-Wilk test. Mann-Whitney U and Chi-square tests were performed to compare the differences between variables as the data distribution was not normal. P of <0.05 was considered statistically significant.
A total of 60 patients (28 with working renal transplants and 32 waitlisted active) were identified. All patients were tested positive for SARS-CoV 2 RNA. Three transplant and 18 waitlisted patients were managed as out-patients while the rest needed varying degrees of medical care as inpatients.
There were 16 (57%) male with 19 (68%) patients from BAME background (50% of our transplant cohort is BAME). The median age was 57 y (25 to 72 y) with 43% of <3 y of age.
The median time since the transplant was 39 mo (1 to 227 mo) with 25% of these performed less than a year ago (1 within 3 mo and 6 between 3 and 12 mo). Twenty-two (79%) were deceased donor transplants. The median BMI was 28 (19 to 38) with 21 (75%) patients being overweight (BMI >25). The comorbidities prevalence is listed in Table 1.
TABLE 1. -
Distribution of comorbidities across transplant and waitlisted patients
||Chronic lung disease
||Diabetes mellitus (DM)
||Ischemic heart disease (IHD)
||Cerebrovascular disease (CVD)
||Chronic liver disease
||Peripheral vascular disease (PVD)
Summary of comorbidities in transplanted and waitlisted patients. There were no significant differences between these groups (P > 0.05).
This cohort included 5 peritoneal dialysis and 27 hemodialysis patients. Nineteen (59%) were males with 22 (70%) patients from BAME background. Waiting list has 321 active patients with 77% from BAME background. The median age was 54 y (18 to 72 y) with 28% of these <50 y of age. The median BMI was 28 (17 to 38) with 81% patients overweight (BMI >25).
Comparison of Transplant and Waitlisted Groups
There were no differences in demographics, comorbidities (age, ethnicity, BMI, hypertension, diabetes, ischemic heart disease, cerebrovascular disease, chronic liver disease, chronic lung disease, and peripheral vascular disease), biochemical, or hematological parameters between the groups.
Thirty-two out of three hundred twenty-one (9.9%) active waitlisted patients contracted COVID-19 in contrast to 28 of 1434 (1.9%) of functioning transplant cohort (1.9%). The difference in incidence between the 2 groups was significant (P < 0.001).
All but 3 patients were admitted in hospital (admission duration 1 to 31 d). Two patients developed nosocomial COVID-19 (1 on d 72 of the index admission, with fungal pneumonia) and other was admitted with iatrogenic esophageal perforation. Symptoms are summarized in Table 2.
TABLE 2. -
Symptoms of patients with COVID-19
||Fever at presentation
||Fever during admission
||Shortness of breath
Summary of common symptoms of COVID-19 for the transplant and waitlisted patients. Three transplant patients were managed in other organizations, hence the missing data. Missing data for the waitlisted population is due to a significant proportion being treated as outpatients.
COVID-19, coronavirus disease 2019.
One patient presented generally unwell with diarrhea, vomiting, and transplant acute kidney injury (AKI) and was found to have near occlusive superior mesenteric artery thrombus, ischemic bowel, and partial infarction of the transplanted kidney. Management was palliation due to significant frailty and unlikely to survive a complex major operation after multidisciplinary discussion among gastrointestinal, vascular, and transplant surgeons.
Transplant Waiting List Patients
Summarized in Table 2, these were not significantly different from the transplant patients. Only 14 (44%) of these patients required hospital admission with 7 requiring intensive therapy unit (ITU) care.
The immunosuppressive regimes and the changes made to these after the diagnosis of COVID-19 are summarized in Table 3.
TABLE 3. -
Immunosuppression at the time of presentation and changes post-diagnosis for transplant patients
Changes after diagnosis
|No change in antimetabolite
||3 (2 patients were already not on antimetabolite due to infections)
Summary of induction and maintenance immunosuppression at presentation and subsequent changes during the course of COVID-19. The majority of the patients received the basiliximab induction. All but 3 patients had changes made to their antimetabolite dosages.
ATG, anti-thymocyte globulin; AZA, azathioprine; COVID-19, coronavirus disease 2019; MMF, mycophenolate mofetil.
Steroid increase was from 5 mg once daily to 10 mg daily apart from 1 patient who was enrolled in the hydrocortisone (10 d treatment) arm of the RECOVERY trial.11 An increase in steroid dose was associated with patient mortality (P = 0.035).
Investigations are summarized in Table 4. Nineteen (82%) patients had lymphopenia at admission and the vast majority was of new onset (89%).
TABLE 4. -
List of investigations across transplant and waitlisted cohorts with their correlation to patient mortality
||Waiting list patients
||Correlation to patient mortality (P value)
||Correlation to patient mortality
|White cell count
|Neutrophil lymphocyte ratio
|CRP at 48 h
||1606 (153–10 334)
Comparison of investigations between the groups and their relationship to patient mortality. CRP at 48 h and at peak was related to patient mortality for both groups, as was peak ferritin for the waitlisted population. Rest of the investigations were not related to patient mortality. Endash indicates “Waitlisted patients” are with renal failure hence no creatinine.
CRP, C-reactive protein.
A higher CRP was seen in sicker patients. Presentation CRP was not correlated to the patient outcome but CRP at 48 h from the diagnosis was significantly higher in patients who subsequently died (P = 0.039). This trend was replicated when the peak CRP was correlated with the patients’ outcome (P = 0.001) (Figure 1). A CRP cutoff of 86 gives the predictive sensitivity of 0.78 (AOC 0.803) when compared to the composite outcome of patients’ death and ITU admission was used.
All patients admitted had a chest X-ray. Nineteen (76%) patients showed some degree of either ground glass shadowing or consolidation.
Forty-seven percent of patients had new-onset lymphopenia. Higher CRP at 48 h and peak CRP again was associated with mortality (P = 0.003 and P = 0.004). A CRP cutoff of 85 at 48 h, gives the predictive sensitivity of 0.78 (AOC 0.825) when a composite outcome of patient death and ITU admission was used.
CRP (at 48 h post-admission and at peak), when combined for both the transplant and chronic kidney disease (CKD) population, it again was significantly associated with composite (transplant and CKD) patient mortality (P < 0.001 at both 48 h and peak CRP levels).
Peak ferritin level was higher in the waitlisted patients who subsequently died (P = 0.002). Thirteen (40%) patients had CXR suggestive of COVID-19.
We retrospectively collected data for qSOFA on admission and at 48 h. For transplant cohort, all deceased patients had a qSOFA score of ≥1. At 48 h, this score was related to patient mortality (P = 0.036). There was no correlation of qSOFA score with mortality for transplant patients on admission or the waitlisted patients for both admission and 48-h scores.
Allograft Function and Survival
Median baseline creatinine was 155 µmol/L (68 to 356 µmol/L) that increased to 255 µmol/L (58 to 566 µmol/L) on admission. The incidence of AKI was high (14/25 – 56%). There were 7 patients with grade 1, 4 with grade 2, and 3 patients with grade 3 AKI according to kidney disease outcomes quality initiative criteria.12
At final follow-up, 22 patients had return of renal function either to baseline (including the ones with no significant AKI) or improving. Four of these patients died with a functioning graft. Two patients required RRT in the form of continuous veno-venous hemofiltration. AKI did not correlate with mortality.
Nine out of twenty-eight patients died, with a mortality rate of 32%. Five transplant patients were admitted to ITU, out of which only 1 patient is alive and improving. Three patients were deemed unlikely to benefit from ITU and had ward-based ceiling of care due to excessive frailty and died in the ward.
Ethnicity, BMI, and comorbidities were not associated with mortality. There was a trend towards older patient at higher risk of poor outcomes (P = 0.06). None of the hematological tests showed any correlation to patient survival.
Five patients in this cohort died (mortality rate of 15%) (3 in ITU and 2 in ward). CRP at 48 h and peak CRP were associated with mortality (P = 0.002, P = 0.006).
This study to date is the first comparative analysis of renal transplant to the waitlisted patients who are their natural controls. The analysis performed in the literature thus far to the general population is artificial and can be misleading as these patients are vulnerable and at an increased risk of worse outcomes from COVID-19 due to comorbidities and/or the burden of immunosuppression.
Patient age has shown to be a strong risk factor for symptomatic disease and mortality, in both previous and current pandemics.13-16 In our cohort, advanced age was not associated with higher risk of mortality. Forty-three percent of the transplants and 28% of waitlisted patients admitted to the hospital were younger than 50 y of age.
We also observed a positive correlation between CRP and mortality. Although higher peak CRP a as predictor of mortality was expected, it is noteworthy that this was also true for CRP at 48 h from the diagnosis for each group, both individually and when the effect of CRP was assessed by combining both transplants and waitlisted population was assessed. Given the small size of the cohort, this might reflect a strong effect size. If seen in bigger cohorts, 48 h CRP can be used as an effective and easy prognostic tool that might help in the early escalation of treatment when effective therapies do become available.
Immunosuppressed patients are known to show diminished symptoms and sometimes delayed presentation but in our study, symptomatology was not affected by immunosuppression.
Quoted mortality rates across the world have been between 1% and 10%, which is less than that of SARS and Middle East respiratory syndrome.17 Our mortality rate of 32% is a gross over estimation of true mortality as only symptomatic and patients needing hospital admission were swabbed. As sobering as this mortality rate is, this has to be looked at in the wider context of the total transplant and hemodialysis population to get a better idea of true mortality. Swabbing practices are likely to generate more positive, in-center hemodialysis cases than stable transplant patients due to shielding.10 In our center, the mortality rate for CKD waitlisted patients is 1.5% as compared to 0.62% for transplant patients. In the absence of any significantly efficacious pharmacological treatment for COVID-19, the shielding policy of staying at home and strictly avoiding any face to face contact remains the single most effective form of safeguarding for these patients. With lower overall mortality of our transplant patients, despite being resident in the worst-hit areas in the UK, this guidance seems to be working. This strategy of shielding is likely to be practiced for these vulnerable patients until an effective vaccine or treatment is available.
The average UK BAME population is around 11% with London being the most diverse (40% non-white British).18,19 In contrast, 68% (19/28) of transplant and 70% (22/31) of waitlisted patients were from BAME background. This finding is consistent with the reported data in the literature.20,21 But our total transplant and waitlisted population has significantly more BAME representation (50% and 80%). A bigger, more representative dataset of the UK population will be more informative of the real burden of COVID-19 on BAME populations.
Far more patients had new-onset lymphopenia in the transplant group (89% versus 47%). Various mechanisms have been proposed for lymphopenia22-24 but we are unable to explain the reason why almost all transplant recipients had new-onset lymphopenia compared to half of the waitlisted population. Perhaps this is a consequence of immunomodulatory effect of chronic immunosuppression.
qSOFA score is a good prognostic tool of mortality for critically ill patients.25,26 The correlation of 48 h qSOFA score with mortality shows some promise but this has to be validated in much larger cohorts.
There are certain limitations to our study. This is a single-center experience in one of the worst affected areas of the UK with a very unique population. With varying swabbing practices across different organizations and the 2 groups, the denominator is unlikely to be accurate. Treatment of our patients has been mostly supportive as the novel medicine trials have only started recruiting in the latter half of the study and those who were included were randomized to standard of care arm, with 1 patient receiving hydrocortisone. Bart’s health transplant department is the referral center for the transplant patients from its nephrology networks. Patients admitted in the sister hospitals of Bart’s health renal network, are either transferred to the referral center or seen by the local nephrology teams, hence the capture of positively diagnosed patients in our database was very accurate. The only exception could be of transplant patients who might be traveling and admitted outside London. Finally, we only looked at the outcomes of confirmed swab positive patients which would have excluded false negative patients. Despite these limitations, this study provides valuable data in the 2 comparable groups, which is helpful in restarting transplantation in significantly affected areas. Given the high mortality rates for both waitlisted and transplant population and the suggestion from our data of worse overall mortality rates in the waitlisted cohort (likely due to increased incidence of contracting COVID-19) safer options for these patients perhaps is to undergo transplantation. Individual patient selection, balancing the risks of transplantation with heightened immunosuppression against continuing on dialysis, has never been more important and it is important to resist generalizations.
In conclusion, waitlisted patients were at a higher risk of acquiring COVID-19 compared to transplant patients. Mortality is very high in both groups on contracting the disease hence in the absence of effective treatments, shielding remains the only nonpharmacological strategy that is protective for these patients. With a higher incidence of disease in the waitlisted population, carefully selected patients may be are more likely to have better outcomes by having a transplant with strict postoperative shielding.
We acknowledge the tireless work of Hussain Zina in tracking all the patients tested positive for SARS-CoV-2. All the nephrology and ITU doctors; nurses and staff are involved in the management of these patients.
1. Coronavirus (COVID-19) cases in the UK. Gov.uk website. Available at https://coronavirus.data.gov.uk/
. Accessed May 7, 2020.
2. Akalin E, Azzi Y, Bartash R, et al. Covid-19 and kidney transplantation. N Engl J Med. 2020;382:2475–2477.
3. Fernández-Ruiz M, Andrés A, Loinaz C, et al. COVID-19 in solid organ transplant recipients: a single-center case series from Spain. Am J Transplant. 2020;20:1849–1858.
4. Kim Y, Kwon O, Paek JH, et al. Two distinct cases with COVID-19 in kidney transplant recipients. Am J Transplant. 2020;20:2269–2275.
5. Meziyerh S, Zwart TC, van Etten RW, et al. Severe COVID-19 in a renal transplant recipient: a focus on pharmacokinetics. Am J Transplant. 2020;20:1896–1901.
6. Syed SM, Gardner J, Roll G, et al. COVID-19 and abdominal transplant: a stepwise approach to practice during pandemic conditions [published online ahead of print, 2020 Jun 29]. Transplantation. 2020. 10.1097/TP.0000000000003387. doi:10.1097/TP.0000000000003387
7. Zidan A, Alabbad S, Ali T, et al. Position statement of transplant activity in the Middle East in era of COVID-19 pandemic. [published online ahead of print, 2020 Jun 9]. Transplantation. 2020. 10.1097/TP.0000000000003348. doi:10.1097/TP.0000000000003348
8. Ahn C, Amer H, Anglicheau D, et al. Global transplantation COVID report March 2020 [published online ahead of print, 2020 Apr 1]. Transplantation. 2020. 10.1097/TP.0000000000003258. doi:10.1097/TP.0000000000003258
9. CDC. Centers for Disease Control and Prevention. Coronavirus Disease 2019 (COVID-19). Centers for Disease Control and Prevention website. 2020. Available at https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/social-distancing.html
. Accessed July 12, 2020.
11. Randomised Evaluation of COVID-19 Therapy (RECOVERY). Health Research Authority website. hra.nhs.uk/covid-19-research/approved-covid-19-research/281712/
. Accessed May 6, 2020.
12. Section 2: AKI Definition. Kidney Int Suppl (2011). 2012;2:19–36.
13. Chan JWM, Ng CK, Chan Y, et al. Short term outcome and risk factors for adverse clinical outcomes in adults with severe acute respiratory syndrome (SARS). Thorax. 2003;58:686–689.
14. Arabi YM, Balkhy HH, Hayden FG, et al. Middle East respiratory syndrome. N Engl J Med
15. Vincent J-L, Taccone FS. Understanding pathways to death in patients with COVID-19. Lancet Respir Med. 2020;8:430–432.
16. Verity R, Okell LC, Dorigatti I, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis. 2020;20:669–677.
17. Park SE. Epidemiology, virology, and clinical features of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2; Coronavirus Disease-19). Clin Exp Pediatr. 2020;63:119–124.
20. ICNARC – Reports. Available at https://www.icnarc.org/Our-Audit/Audits/Cmp/Reports
. Accessed May 4, 2020.
21. Pareek M, Bangash MN, Pareek N, et al. Ethnicity and COVID-19: an urgent public health research priority. Lancet. 2020;395:1421–1422.
22. Liao Y-C, Liang W-G, Chen F-W, et al. IL-19 induces production of IL-6 and TNF-α and results in cell apoptosis through TNF-α. J Immunol. 2002;169:4288–4297.
23. Xu H, Zhong L, Deng J, et al. High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa. Int J Oral Sci. 2020;12:1–5.
24. Tan L, Wang Q, Zhang D, et al. Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study. Signal Transduct Target Ther. 2020;5:33
25. Zhang Y, Luo H, Wang H, et al. Validation of prognostic accuracy of the SOFA score, SIRS criteria, and qSOFA score for in-hospital mortality among cardiac-, thoracic-, and vascular-surgery patients admitted to a cardiothoracic intensive care unit. J Card Surg. 2020;35:118–127.
26. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062.