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Original Clinical Science—General

Biomarkers of Cytokine Release Syndrome Predict Disease Severity and Mortality From COVID-19 in Kidney Transplant Recipients

Benotmane, Ilies MD1,2,3; Perrin, Peggy MD1,3; Vargas, Gabriela Gautier MD1; Bassand, Xavier MD1; Keller, Nicolas MD4; Lavaux, Thomas MD5; Ohana, Mickael MD6; Bedo, Dimitri1; Baldacini, Clément1; Sagnard, Mylene1; Bozman, Dogan-Firat MD1; Chiesa, Margaux Della1; Cognard, Noëlle MD1; Olagne, Jérôme MD1; Delagreverie, Héloïse MD, PhD2; Marx, David MD1; Heibel, Françoise MD1; Braun, Laura MD1; Moulin, Bruno MD, PhD1,3; Fafi-Kremer, Samira MD, PhD2,3; Caillard, Sophie MD, PhD1,3

Author Information
doi: 10.1097/TP.0000000000003480

Abstract

INTRODUCTION

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a zoonotic beta-coronavirus that emerged from China in December 2019 and rapidly gave rise to a pandemic.1,2 Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has lower mortality than other diseases caused by related betacoronavirus strains – that is, SARS; caused by SARS-CoV and Middle East respiratory syndrome (MERS; caused by MERS-CoV). Unfortunately, the crude death tool of COVID-19 is already higher than that attributable to SARS and MERS combined3 because SARS-CoV-2 has more rapid human-to-human spread.4

The clinical course of COVID-19 is generally more severe in elderly subjects and patients with comorbid conditions.5 However, the manifestations and prognosis of the disease in fragile immunocompromized patients remain poorly investigated. In this context, kidney transplant recipients (KTR) may be particularly vulnerable to severe manifestations and death because of their high comorbidity burden (ie, hypertension, diabetes, and cardiovascular disease). However, the impact of immunosuppression on the clinical course of COVID-19 remains controversial.6 On the one hand, immunosuppressive drugs could promote viral replication but, on the other hand, immunosuppression may mitigate or even prevent the onset of SARS-CoV-2-induced hyperinflammation. There is indeed mounting evidence that a dysregulated inflammatory response is pathophysiologically linked to the hallmark features of COVID-19 – including the acute respiratory distress syndrome (ARDS) and the cytokine release syndrome (CRS).7 The occurrence of CRS in patients with COVID-19 – as reflected by increased interleukin (IL)-6 serum levels – is clinically associated with respiratory failure, ARDS, and severe outcomes.8 Elevated serum levels of C-reactive protein (CRP) are also a marker of severe betacoronavirus infections.9,10 However, the occurrence and prognostic impact of CRS in immunocompromised KTR with COVID-19 remains unclear.

This single-center study conducted in a well-characterized cohort of KTR from Alsace, Grand-Est, France, was designed to address this issue. Specifically, biomarkers of CRS were investigated in relation to the occurrence of severe COVID-19 and mortality.

MATERIALS AND METHODS

Study Population

The study sample consisted of 49 adult KTR with COVID-19 who were recruited in our transplant center between March 4 and April 7, 2020. COVID-19 was diagnosed in patients with clinical symptoms and positive reverse transcriptase-polymerase chain reaction (RT-PCR) results on nasopharyngeal swab specimens and/or typical lung lesions on chest computed tomography (CT). Patients presenting with fever, flu-like or respiratory symptoms, anosmia/ageusia, digestive disorders, and a known personal contact with a confirmed case were considered highly suspected for COVID-19. In accordance with the published literature,11-13 disease severity was categorized as follows: (1) mild disease manageable in an outpatient setting, (2) nonsevere disease requiring hospitalization but without oxygen requirement or oxygen need <6 L/min, and (3) severe disease requiring hospitalization with an oxygen need >6 L/min or mechanical ventilation. Data were retrieved from digital medical records from the day of admission to the date of the last follow-up (April 30, 2020). The following variables were collected: patient characteristics, symptoms and time of presentation, immunosuppressive therapy and management, laboratory parameters, chest CT findings, and administered drugs. High-dose steroids included methylprednisolone or dexamethasone. The main study outcomes were as follows: death, intensive care unit (ICU) admissions, acute kidney injury (AKI), graft loss, venous thromboembolic events, as well as neurological and myocardial complications. Ethical approval was granted by the local Institutional Review Board (approval number: DC-2013-1990).

Laboratory Diagnosis of SARS-CoV-2 Infection

Laboratory identification of SARS-CoV-2 was performed by RT-PCR testing of nasopharyngeal swab specimens according to current guidelines (Institut Pasteur, Paris, France; WHO technical guidance).14 The assay targets 2 regions of the viral RNA-dependent RNA polymerase (RdRp) gene, and the threshold limit of detection was 10 copies per reaction.

Serum Laboratory Markers

Laboratory follow-up examinations in hospitalized patients were performed in a standardized fashion. CRP, procalcitonin, lactate dehydrogenase (LDH), high-sensitivity (hs)-troponin I, D-dimer, and fibrinogen were measured with standard techniques. Serum IL-6 levels were quantified with a chemiluminescent immunoassay (Lumipulse G600 II; Fujirebio, Tokyo, Japan).15 A total of 132 specimens underwent IL-6 quantification (80 prospectively and 52 retrospectively using stored serum samples). All laboratory parameters were measured on admission and the peak values observed within the first 3 weeks of symptom onset were recorded. Routine biological monitoring was generally performed every 2 days during hospitalization. However, this time interval was modifiable at the physician’s discretion (ie, more or less frequently) by taking into account the clinical course of COVID-19 for each patient. Lymphopenia was defined as a lymphocyte count <1000/mm3, eosinopenia as an eosinophil count <50/mm3, and thrombocytopenia as a platelet count <150 000/mm3.

Chest CT Imaging

When clinically feasible, all patients underwent chest CT imaging on admission. Repeated CT scans were performed when clinically indicated as it has been suggested that chest CT may have a higher sensitivity than RT-PCR.16 All CT images were interpreted by a single experienced chest radiologist. Typical CT findings—consisting of bilateral ground-glass opacities with peripheral distribution—were graded according to the European Society of Radiology and the European Society of Thoracic Imaging guidelines,17 as follows: no lesion, minimal lesions (<10%), moderate lesions (10–25%), important lesions (25–50%), severe lesions (50–75%), and critical lesions (>75%).

Statistical Analysis

Continuous data are given as medians and interquartile ranges (IQR) and analyzed with the Mann-Whitney U test. Categorical variables are expressed as counts and percentages and compared with the Fisher exact test. The associations between hypoxia and laboratory markers of inflammatory markers, cell lysis, and coagulation were determined by calculating Spearman’s correlation coefficients (ρ). Receiver operating characteristic (ROC) curves were constructed to investigate serum biomarker levels in relation to disease severity and COVID-19-related mortality. Kaplan-Meier plots of severe COVID-19-free survival and COVID-19-specific survival were constructed according to levels of inflammation markers (CRP and IL-6), cell lysis markers (LDH, hs-troponin I), and coagulation markers (D-dimer, fibrinogen). Comparisons of Kaplan-Meier curves were performed with the log-rank test. Severe COVID-19 was defined as oxygen requirement >6 L/min, need for ICU admission, or patient death. Patients were censored on the date of the last follow-up (April 30, 2020). All calculations were performed with GraphPad Prism 8.0 (GraphPad Inc., San Diego, CA, USA). Two-tailed P values <0.05 were considered statistically significant.

RESULTS

General Characteristics of KTR With COVID-19

The general characteristics of the 49 KTR included in the study are shown in Table 1. Eight (16.3%) were managed in outpatient facilities, whereas 41 (83.7%) required hospitalization. Most patients were Caucasian (n = 48, 98%), men (n = 37, 75.5%), and aged >60 years (n = 27, 55.1%). Hypertension was the most common comorbidity (n = 41, 83.7%), followed by diabetes (n = 23, 46.9%), and obesity (n = 22, 44.9%). The median interval between transplantation and the onset of COVID-19 symptoms was 7.1 years (IQR: 2.9–14.4 y). At the time of COVID-19 diagnosis, the following immunosuppressive drugs were being used: calcineurin inhibitors (CNI), n = 42 (85.8%); mycophenolate mofetil (MMF) or mycophenolic acid (MPA), n = 38 (77.6%); and mammalian target of rapamycin (mTOR) inhibitors, n = 11 (22.5%). The most common symptom at diagnosis was fever (n = 42, 85.7%), followed by cough (n = 28, 57.1%) and diarrhea (n = 27, 55.1%). Nineteen patients (38.8%) had dyspnea.

TABLE 1. - Demographic and clinical characteristics of hospitalized and nonhospitalized patients at admission and during follow-up
Entire cohort (n = 49) Nonhospitalized (n = 8) Hospitalized (n = 41) P
Men 37 (75.5%) 5 (62.5%) 32 (78%) 0.39
Age (y) 62.2 (52.3–67.8) 53.1 (50.8–57.7) 63.9 (55.2–69) 0.02
 >60 y 27 (55.1%) 1 (12.5%) 26 (63.4%) 0.02
Comorbidities
 BMI (kg/m2) 28 (23–32) 23 (21.8–26.5) 30 (24–33) 0.05
 <25 kg/m2 17 (34.7%) 5 (62.5%) 12 (29.3%) 0.08
 25–30 kg/m2 10 (20.4%) 2 (25%) 8 (19.5%)
 >30 kg/m2 22 (44.9%) 1 (12.5%) 21 (51.2%)
 Cardiovascular disease 18 (36.8%) 1 (12.5%) 17 (41.5%) 0.23
 Respiratory disease 9 (18.4%) 0 9 (22%) 0.32
 Obstructive sleep apnea 7 (14.3%) 0 7 (17.1%) 0.58
 Diabetes 23 (46.9%) 4 (50%) 19 (46.3%) 1
 Active cancer 1 (2%) 1 (12.5%) 0 0.16
 Hypertension 41 (83.7%) 7 (87.5%) 34 (82.9%) 1
 RAAS inhibitor use 21 (42.9%) 6 (75%) 15 (36.6%) 0.06
  ACE inhibitor use 12 (24.5%) 3 (37.5%) 9 (22%) 0.39
  ARB use 9 (18.4%) 3 (37.5%) 6 (14.6%) 0.15
ABO blood group system 0.06
 A 28 (58.3%) 5 (62.5%) 23 (57.5%)
 B 6 (12.5%) 3 (37.5%) 3 (7.5%)
 O 12 (25%) 0 12 (29.3%)
 AB 2 (4.2%) 0 2 (4.9%)
Primary nephropathy 0.2
 Diabetic nephropathy 6 (12.2%) 3 (37.5%) 3 (7.3%)
 Chronic tubulointerstitial disease 10 (20.4%) 1 (12.5%) 9 (22%)
 Polycystic kidney disease 7 (14.3%) 0 7 (17.1%)
 Vascular nephropathy 5 (10.2%) 0 5 (12.2%)
 Glomerular nephropathy 19 (38.8%) 4 (50%) 15 (36.6%)
 Unknown 2 (4.1%) 0 2 (4.9%)
First transplantation 44 (89.9%) 6 (75%) 38 (92.7%) 0.18
Interval from kidney transplantation (y) 7.1 (2.9–14.4) 7.78 (4.3–12.8) 7.1 (2.9–14.6) 0.86
Immunosuppressive therapy
Induction immunosuppression
 Anti-thymocyte globulin 25 (52.1%) 7 (87.5%) 18 (45%) 0.11
 Anti-CD25 20 (41.7%) 1 (12.5%) 19 (47.5%)
 No induction 3 (6.3%) 0 3 (7.5%)
Maintenance immunosuppression
 Tacrolimus 26 (53.1%) 4 (50%) 22 (53.6%) 1
 Ciclosporin 16 (32.7%) 2 (25%) 14 (34.2%) 1
 MMF/MPA 38 (77.6%) 3 (37.5%) 35 (85.4%) 0.01
 mTOR inhibitors 11 (22.5%) 5 (62.5%) 6 (14.6%) 0.01
 Azathioprine 1 (2%) 0 1 (2.4%) 1
 Steroids 28 (57.1%) 4 (50%) 24 (58.5%) 0.71
 Belatacept 2 (4.1%) 0 2 (4.9%) 1
 Eculizumab 2 (4.1%) 1(12.5%) 1 (2.4%) 0.3
Clinical signs at diagnosis
 Dyspnea 19 (38.8%) 1 (12.5%) 18 (43.9%) 0.13
 Cough 28 (57.1%) 4 (50%) 24 (58.5%) 0.71
 Fever 42 (85.7%) 4 (50%) 38 (92.7%) 0.01
 Myalgia 25 (52.1%) 4 (50%) 21 (52.5%) 1
 Headache 9 (18.8%) 1 (12.5%) 8 (19.5%) 1
 Diarrhea 27 (55.1%) 4 (50%) 23 (56.1%) 1
 Vomiting 7 (15.2%) 0 7 (17.1%) 1
 Anosmia/ageusia 11 (24.4%) 5 (50%) 7 (17.1%) 0.09
 Neurological manifestations 2 (4.1%) 0 2 (4.9%) 1
Clinical signs during follow-up
 Dyspnea 30 (61.2%) 1 (12.5%) 29 (70.7%) 0.003
 Cough 36 (73.5%) 5 (62.5%) 31 (75.6%) 0.42
 Fever 43 (87.8%) 4 (50%) 39 (95.1%) 0.004
 Myalgia 26 (53.1%) 4 (50%) 22 (53.7%) 1
 Headache 13 (26.5%) 1 (12.5%) 12 (29.3%) 0.66
 Diarrhea 36 (73.5%) 5 (62.5%) 31 (75.6%) 0.42
 Vomiting 7 (14.3%) 0 7 (17.1%) 0.58
 Anosmia/ageusia 12 (24.5%) 4 (50%) 8 (19.5%) 0.09
 Neurological manifestations 17 (34.7%) 1 (12.5%) 16 (39%) 0.14
Continuous variables are presented as medians (interquartile ranges), whereas categorical variables are given as counts (percentages).
ACE, angiotensin converting enzyme; ARB, angiotensin receptor blocker; BMI, body mass index; MMF, mycophenolate mofetil; MPA, mycophenolic acid, mTOR: mammalian target of rapamycin; RAAS, renin–angiotensin–aldosterone system.

KTR With COVID-19 Who Did Not Require Hospitalization

Of the 8 KTR who did not require hospitalization, COVID-19 was confirmed by RT-PCR in 5 cases and seroconversion in 2 patients. The remaining case presented with highly suggestive clinical symptoms (ie, fever, anosmia/ageusia, respiratory, and digestive symptoms). Table 1 compares the general characteristics of patients who required hospitalization versus those who did not. Those in the latter group were younger and had a lower body mass index. Moreover, they less frequently received MMF/MPA (37.5% versus 85.4%, respectively, P = 0.01) but were more commonly treated with mTOR inhibitors (62.5% versus 14.6%, respectively, P = 0.01). Symptoms were milder, with a lower occurrence of fever and dyspnea.

KTR With COVID-19 Who Required Hospitalization

Most of the hospitalized patients (n = 41) were men (78.0%), aged >60 years (63.4%), and obese (51.2%). Interestingly, diarrhea (75.6%) occurred as frequently as cough (70.7%; Table 2). A total of 39 (95.1%) patients had an RT-PCR-confirmed diagnosis and 2 (4.9%) had highly suspected clinical symptoms and imaging results. Laboratory findings are illustrated in Table 3. Lymphopenia (n = 30/38, 79%) and eosinopenia were common on admission (n = 32/35, 91.4%), whereas 9 patients (22%) showed thrombocytopenia. Median serum creatinine levels were 166 µmol/L (IQR: 130–231 µmol/L).

TABLE 2. - Demographics and clinical characteristics of hospitalized patients according to disease severity
Hospitalized patients (n = 41) Nonsevere patients (n = 21) Severe patients (n = 20) P
Men 32 (78%) 19 (90.5%) 13 (65%) 0.06
Age (y) 63.9 (55.2–69.0) 58.4 (50.9–64.3) 65.6 (63.2–70.6) 0.01
 >60 y 26 (63.4%) 9 (42.9%) 17 (85%) 0.01
Comorbidities
 BMI (kg/m2) 30 (24–33) 25 (23–32) 31 (27.5–33) 0.07
 <25 kg/m2 13 (31.7%) 11 (52.4%) 2 (10%) 0.02
 25–30 kg/m2 8 (19.5%) 4 (19.1%) 4 (20%)
 >30 kg/m2 21 (51.2%) 7 (33.3%) 14 (70%)
 Cardiovascular disease 17 (41.5%) 8 (38.1%) 9 (45%) 0.76
 Respiratory disease 9 (22.0%) 5 (23.8%) 4 (20%) 1
 Obstructive sleep apnea 7 (17.1%) 4 (19.1%) 3 (15%) 1
 Diabetes 19 (46.4%) 8 (38.1%) 11 (55%) 0.35
 Active cancer 0 0 0
 Hypertension 34 (82.9%) 15 (71.4%) 19 (95%) 0.09
 RAAS inhibitor use 15 (36.5%) 7 (33.3%) 8 (40%) 0.75
  ACE inhibitor use 9 (21.9%) 3 (14.3%) 6 (30%) 0.28
  ARB use 6 (14.6%) 4 (19.1%) 2 (10%) 0.66
 Interval from kidney transplantation (y) 7.1 (2.9–14.6) 3.8 (2.1–12.6) 8.3 (5.6–14.7) 0.18
Immunosuppressive therapy
Induction immunosuppression
 Anti-thymocyte globulin 18 (43.9%) 10 (47.6%) 8 (42.1%) 0.9
 Anti-CD25 19 (46.3%) 9 (42.9%) 10 (52.6%)
 No induction 3 (7.3%) 2 (9.5%) 1 (5%)
Maintenance immunosuppression
 Tacrolimus 22 (53.6%) 10 (47.6%) 12 (60%) 0.54
 Ciclosporin 14 (34.2%) 7 (33.3%) 7 (35%) 1
 MMF/MPA 35 (85.4%) 19 (90.5%) 16 (80%) 0.41
 mTOR inhibitors 6 (14.6%) 4 (19.1%) 2 (10%) 0.66
 Azathioprine 1 (2.4%) 0 1 (5%) 0.49
 Steroids 24 (58.5%) 12 (57.1%) 12 (60%) 1
 Belatacept 2 (4.9%) 2 (9.5%) 0 0.49
 Eculizumab 1 (2.4%) 0 1 (5%) 0.49
Clinical symptoms during hospitalization
 Dyspnea 29 (70.7%) 9 (42.9%) 20 (100%) <0.0001
 Cough 31 (75.6%) 15 (71.4%) 16 (80%) 0.72
 Fever 39 (95.1%) 20 (95.2%) 19 (95%) 1
 Myalgia 22 (53.7%) 14 (66.7%) 8 (40%) 0.12
 Headache 12 (29.3%) 9 (42.8%) 3 (15%) 0.09
 Diarrhea 31 (75.6%) 19 (90.5%) 12 (60%) 0.03
 Vomiting 7 (17.1%) 5 (23.8%) 2 (10%) 0.41
 Anosmia/ageusia 8 (19.5%) 6 (28.6%) 2 (10%) 0.24
 Neurological manifestations 16 (39%) 8 (38.1%) 8 (40%) 1
O2 need
 O2 need at admission (L/min) 0 (0–3) 0 (0–0) 2.5 (1.5–4) <0.0001
 Maximum O2 need (L/min) 5 (0–15) 0 (0–2) 15 (9.75–15) <0.0001
 O2 need (%) 30 (73.2%) 10 (47.6%) 20 (100%) 0.0002
Continuous variables are presented as medians (interquartile ranges), whereas categorical variables are given as counts (percentages).
ACE, angiotensin converting enzyme; ARB, angiotensin receptor blockers; BMI, body mass index; RAAS, renin–angiotensin–aldosterone system; MMF, mycophenolate mofetil; MPA, mycophenolic acid, mTOR: mammalian target of rapamycin.

TABLE 3. - Biochemical markers on admission and peak values in hospitalized patients according to disease severity
n Hospitalized patients (n = 41) Nonsevere patients (n = 21) Severe patients (n = 20) P
Biochemical markers on admission
 Interval from symptom onset (d) 4 (2–7) 3 (2–7) 7 (3.8–7.3) 0.10
 C-reactive protein (mg/L) 39 56 (24.5–94.7) 29.5 (41.8–61.5) 67 (54–187) 0.0018
 IL-6 (ng/L) 28 24.3 (16.5–53.3) 18.9 (12.6–45.4) 36.6 (21.9–70.2) 0.04
 Procalcitonin (µg/L) 28 0.17 (0.14–0.28) 0.16 (0.13–0.21) 0.21 (0.15–0.41) 0.26
 Ferritin (µg/L) 17 394.5 (165.3–924.8) 540.5 (300.3–912) 178.5 (164.8–1029.8) 0.80
 Albuminemia (g/L) 35 41 (38–42) 41 (40–44) 39.5 (37–41) 0.03
 High-sensitivity troponin I (ng/L) 32 20.5 (8.4–38.3) 6.6 (5.1–12) 40.5 (14.6–86.3) 0.01
 Lactate dehydrogenase (UI/L) 32 264.5 (199–340) 231 (179–340) 287 (242–330) 0.23
 Creatine phosphokinase (U/L) 33 101 (60–286) 88 (58.5–267.5) 143 (75–297.5) 0.60
 Creatininemia (µmol/L) 41 166 (130–231) 159 (130–200) 179 (138–251) 0.45
 Platelet count (/mm3) 41 181 000 (156 000–227 000) 188 000 (148 000–214 000) 177 500 (156 000–231 250) 0.66
 Neutrophil count (/mm3) 36 4010 (3077.5–5167.5) 3590 (2690–4520) 5140 (3840–5970) 0.02
 Lymphocyte count (/mm3) 38 635 (397.5–930) 660 (420–940) 630 (350–870) 0.88
 CD4 (/mm3) 24 256 (138.3–385.8) 256 (193.5–303) 221.5 (112.8–483.8) 0.84
 CD8 (/mm3) 24 138 (84.3–196.8) 153 (86.8–195) 138 (84.5–186) 0.71
 IgG (g/L) 28 8.5 (6.9–8.4) 8.3 (7–9.1) 8.7 (6.6–10.1) 0.80
 D-dimer (µg/L) 30 1020 (587.5–1460) 990 (615–1440) 1380 (735–1545) 0.56
 Fibrinogen (g/L) 29 6 (5–6.8) 5.7 (5–6.46) 6.6 (5.4–7.2) 0.16
 PaO2 (mm Hg) 34 81.5 (73.12–96) 87.7 (81–101) 73.5 (62–82) 0.0088
 Viral load in nasopharyngeal swabs (log10 copies/reaction) 38 5.2 (3.8–6.7) 5.2 (3.7–6) 6.2 (4.6–7) 0.32
Biochemical markers at peak values
 C-reactive protein (mg/L) 39 94 (48–207) 55 (30.4–90.2) 174 (99.3–299) <0.0001
 IL-6 (ng/L) 34 51.7 (25.8–121.4) 27.5 (18.2–52.8) 131.7 (66.7–469.3) <0.0001
 Procalcitonin (µg/L) 32 0.31 (0.18–0.82) 0.22 (0.17–0.42) 0.48 (0.18–4.00) 0.23
 Ferritin (µg/L) 27 1128 (546–1630) 1128 (675–1602) 1027 (512–2621) 0.98
 Albuminemia (g/L) 32 34 (31.3–38) 35 (32.5–38.5) 32 (24–36) 0.044
 High-sensitivity troponin I (ng/L) 34 29.1 (8.8–44.3) 13 (6.6–29.5) 57.15 (34.2–92.7) 0.0003
 Lactate dehydrogenase (UI/L) 36 356.5 (267.3–504.3) 295 (226.5–420.5) 450 (337–549) 0.013
 Creatine phosphokinase (U/L) 34 153 (70.8–338.5) 97 (55.5–282.8) 185 (80.8–497) 0.16
 Neutrophil count (/mm3) 36 6215 (3593–9565) 4800 (2845–7340) 9400 (5970–10 850) 0.003
 D-dimer (µg/L) 34 1410 (837.5–2463) 960 (565–1755) 1830 (1315–3430) 0.019
 Fibrinogen (g/L) 34 6.7 (5.6–8.3) 6.15 (4.9–7.5) 7.82 (6.5–9) 0.016
Continuous variables are presented as medians (interquartile ranges), whereas categorical variables are given as counts (percentages).
IL, interleukin; Ig, immunoglobulin.
Reference levels for biochemical markers: IL-6 <4 ng/L; procalcitonin <0.05 µg/L; ferritin 22–322 µg/L; high-sensitivity troponin I <79 ng/L; lactate dehydrogenase 120–246 UI/L; creatine phosphokinase: 46–171 U/L; D-dimer <500 µg/L; fibrinogen: 2–4 g/L.

A total of 31 (75.6%) patients had a CT (median interval from symptom onset: 7 d; IQR: 4–10 d). Lesions affecting >50% of the lung parenchyma were observed in 13 patients (42%; Figure S1, SDC, https://links.lww.com/TP/C20).

With regard to the management of immunosuppression on admission (Table 4), MMF/MPA and mTOR inhibitors were withdrawn in all patients. Scheduled belatacept administration was delayed in 1 of 2 cases. CNI were temporarily withdrawn in 15 (36.6%) patients. Treatment for COVID-19 consisted of hydroxychloroquine in 15 (36.6%) and azithromycin in 26 (65%) patients, respectively (Figure 1). Lopinavir–ritonavir was given to 5 patients only because of significant pharmacokinetic interactions with CNI and mTOR inhibitors. High-dose corticosteroids were used to treat CRS in 14 cases (46.7%) who required oxygen therapy and in 9 patients before progression to severe stage. In the latter group, 5 had favorable outcomes and 4 progressed to the severe stage (of whom 2 required mechanical ventilation and 1 died of disease). The anti-IL-6 receptor monoclonal antibody tocilizumab was used in 4 patients. Of them, 3 patients showed a rapid improvement whereas 1 died 6 days after injection. The individual clinical outcomes in relation to the temporal course of inflammatory markers and COVID-19 treatments are illustrated in Figures S2a (CRP) and S2b (IL-6), SDC, https://links.lww.com/TP/C20.

TABLE 4. - Drugs given to hospitalized patients stratified according to disease severity
Hospitalized patients (n = 41) Nonsevere patients (n = 21) Severe patients (n = 20)
Azithromycin 26 (65%) 15 (71.4%) 11 (57.9%)
Others antibiotics 41 (100%) 21 (100%) 20 (100%)
Azole 1 (2.5%) 0 1 (5.3%)
Lopinavir–ritonavir 5 (12.2%) 1 (4.76%) 4 (20%)
Hydroxychloroquine 15 (36.6%) 9 (42.9%) 6 (30%)
Tocilizumab 4 (9.8%) 1 (4.8%) 3 (15%)
High-dose corticosteroidsa 14 (34.2%) 5 (23.8%) 9 (45%)
Immunosuppressive drugs management
 MMF/MPA withdrawal 35/35 (100%) 17 (100%) 18 (100%)
 Calcineurin inhibitors withdrawal 15/36 (41.7%) 2 (11.8%) 13 (68.4)
 mTOR inhibitors withdrawal 6/6 (100%) 4 (100%) 2 (100%)
 Delayed belatacept administration 1/2 (50%) 1 0
aHigh-dose corticosteroids included intravenous dexamethasone and intravenous methylprednisolone. Continuous variables are presented as medians (interquartile ranges), whereas categorical variables are given as counts (percentages).
MMF, mycophenolate mofetil; MPA, mycophenolic acid; mTOR, mammalian target of rapamycin.

F1
FIGURE 1.:
Flow of the 49 patients through the study according to treatments and outcomes.

Fourteen (34.2%) patients were admitted to ICU after a median interval from symptom onset of 9.5 days (IQR: 7.5–11.8 d; Table 5). Of them, 11 improved following mechanical ventilation. Three cases with severe oxygen needs were not eligible for ICU admission because of advanced age and a significant burden of comorbidities. AKI was frequent (75.6%) but generally completely reversible (73.9%). There were no cases of graft loss. Other complications included mild-to-severe neurological manifestations (n = 16), deep vein thrombosis (n = 1), and myocarditis (n = 1). Nine patients died (Table 5) and the 30-day mortality rate was 19.5% (Figure S3, SDC, https://links.lww.com/TP/C20).

TABLE 5. - Clinical outcomes of hospitalized patients according to disease severity
Hospitalized patients (n = 41) Nonsevere patients (n = 21) Severe patients (n = 20) P
ICU admission 14 (34.2%) 0 14 (70%)a <0.0001
Delay from symptom onset to ICU (d) 9.5 (7.5–11.8) N/A 9.5 (7.5–11.8) N/A
Renal outcome
 AKI 31 (75.6%) 14 (66.7%) 19 (95%) 0.045
 Dialysis 4/31 (12.9%) 1 (4.8%) 3 (15%) 0.61
 Complete kidney recovery 19/23b (82.6%) 12 (85.7%) 7 (77.8%) 1
Patients outcome <0.0001
 Discharge 31(75.6%) 21 (100%) 10 (50%)
 Currently hospitalized 1 (2.4%) 0 1 (5%)
 Death 9 (22%) 0 9 (45%)
 Duration of hospitalization (d) 12 (7–18.5) 8 (5–13) 22.5 (18.3–28.8) 0.0001
 Interval from onset symptoms to death (d) 10 (8–16) N/A 10 (8–16) N/A
aICU admission was denied for 3 patients.
bOnly survivor’s patients were taken to account.
Continuous variables are presented as medians (interquartile ranges), whereas categorical variables are given as counts (percentages).
AKI, acute kidney injury; ICU, intensive care unit; N/A, not available.

Factors Associated With Severe COVID-19 and Death

Among hospitalized patients, nonsevere and severe COVID-19 was diagnosed in 21 (51.2%) and 20 (48.8%) patients, respectively. Of the latter group, oxygen therapy ≥6 L/min or mechanical ventilation was required on admission and at follow-up (between 1 and 15 d from admission) in 4 and 16 patients, respectively. The general characteristics of patients with nonsevere and severe COVID-19 are shown in Table 2. Severe patients were more frequently aged >60 years (85% versus 42.9%, respectively, P = 0.01) and were more commonly obese (70% versus 33.3%, respectively, P = 0.02). With regard to symptoms, dyspnea was more frequent (100% versus 42.9%, respectively, P < 0.0001) and diarrhea less common in severe than in nonsevere patients (60% versus 90.5%, respectively, P = 0.03).

On admission, severe patients had higher CRP, IL-6, and hs-troponin I levels, an increased neutrophil count, and a lower PaO2 (Table 3). There were no intergroup differences with regard to D-dimer, procalcitonin, LDH, creatinine levels, lymphocyte count, and SARS-CoV-2 nasopharyngeal viral load.

We next sought to investigate the temporal course of laboratory parameters—by taking into account their peak values—in relation to the clinical evolution of COVID-19. Peak levels of CRP were significantly higher in KTR aged >60 years (124 mg/L versus 55 mg/L, respectively, P = 0.019) and with overweight (101 mg/L versus 55 mg/L, respectively, P = 0.049). Similarly, peak levels of IL-6 were significantly higher in KTR overweight (68 ng/L versus 27.5 ng/L, respectively, P = 0.02). Interestingly, peak values of inflammatory biomarkers showed strong associations with oxygen requirements—with maximum oxygen need being correlated with both peak IL-6 (ρ = 0.740, P < 0.0001) and CRP (ρ = 0.687, P < 0.0001). IL-6 concentrations were also associated with hs-troponin I, LDH, fibrinogen, and D-dimer levels (Table 6).

TABLE 6. - Spearman’s correlation coefficients (ρ) between hypoxia-related parameters and laboratory variables (biomarkers of inflammation and cell lysis and coagulation parameters)
CRP IL-6 LDH Hs-troponin I Fibrinogen D-dimer Maximum O2 need PO2 at admission
CRP 0.743*** 0.645*** 0.583*** 0.801*** 0.344* 0.687*** –0.712***
IL-6 0.743*** 0.502** 0.370* 0.654*** 0.493** 0.740*** –0.547**
LDH 0.645*** 0.502** 0.292 0.626*** 0.368* 0.557** –0.345
Hs-troponin I 0.583*** 0.370* 0.292 0.396* 0.362* 0.598*** –0.505**
Fibrinogen 0.801*** 0.654*** 0.626*** 0.396* 0.386* 0.646*** –0.611***
D-dimer 0.344* 0.493** 0.368* 0.362* 0.386* 0.474** –0.152
Maximum O2 need 0.687*** 0.740*** 0.557** 0.598*** 0.646*** 0.474** –0.507**
PaO2 on admission –0.712*** –0.547** –0.345 –0.505** –0.611*** –0.152 –0.507**
*P < 0.05, ** P < 0.01, ***P < 0.001.
CRP, C-reactive protein; IL, interleukin; LDH, lactate dehydrogenase; hs, high-sensitivity.

Peak inflammatory markers were also related to disease severity and clinical outcomes during hospitalization (Table 3). ROC curve analysis revealed that peak IL-6 was strongly associated with both severe COVID-19 (AUC = 0.921, P < 0.0001; Figure 2A) and mortality (AUC = 0.821, P = 0.015). Peak IL-6—which occurred between day 7 and day 19 after admission—was markedly higher in patients with severe disease (Figure 2B). Further, there were clear associations between IL-6 (cutoff: 65 ng/L), CRP (cutoff: 100 mg/L), and severe COVID-19 and mortality (Figure 2C–F). Markers of cell lysis showed similar associations with outcomes. Specifically, ROC curve analysis revealed that hs-troponin I levels were associated with mortality (AUC = 0.920, P = 0.0002). Moreover, there were associations between hs-troponin I (cutoff: 30 ng/L) and LDH (cutoff: 300 UI/L) with severe COVID-19 and mortality (Figure 3A–D). With regard to coagulation parameters, we found associations between fibrinogen (cutoff: 6 g/L) and D-dimer (cutoff: 960 ng/mL) with severe COVID-19 and mortality (Figure 4A–D). Notably, none of the patients with hs-troponin I <30 ng/L (n = 18), LDH <300 UI/L (n = 13), D-dimer <960 ng/mL (n = 11), and fibrinogen <6 g/L (n = 11) died of COVID-19. As expected, severe patients had more extensive lung involvement on chest CT than nonsevere patients (61.5% versus 27.8%, respectively, P = 0.07; Figure S1, SDC, https://links.lww.com/TP/C20).

F2
FIGURE 2.:
Circulating levels of inflammatory markers are associated with COVID-19 severity and mortality. A, Receiver operating characteristic curve analysis of COVID-19 severity according to serum interleukin (IL)-6 levels. Area under curve (AUC) = 0.921, P < 0.0001. B, Scatter plot of IL-6 levels (peak values) against days from symptom onset in patients categorized according to COVID-19 severity. C, Kaplan-Meier plots of severe COVID-19-free survival according to IL-6 levels. IL-6 >65 ng/L (red curve) vs IL-6 <65 ng/L (blue curve), P < 0.0001. D, Kaplan-Meier plots of COVID-19-free survival according to IL-6 levels. IL-6 >65 ng/L (red curve) vs IL-6 <65 ng/L (blue curve), P = 0.07. E, Kaplan-Meier plots of severe COVID-19-free survival according to C- reactive protein (CRP) levels. CRP >100 mg/L (red curve) vs CRP <100 mg/L (blue curve), P = 0.0004. F, Kaplan-Meier plots of COVID-19-free survival according to CRP levels. CRP >100 mg/L (red curve) vs CRP <100 mg/L (blue curve), P = 0.041.
F3
FIGURE 3.:
Circulating levels of cell lysis markers are associated with COVID-19 severity and mortality. A, Kaplan-Meier plots of severe COVID-19-free survival according to high-sensitivity (hs)-troponin I levels. Hs-troponin I >30 ng/L (red curve) vs hs-troponin I <30 ng/L (blue curve), P = 0.0002. B, Kaplan-Meier plots of COVID-19-free survival according to hs-troponin I levels. Hs-troponin I >30 ng/L (red curve) vs hs-troponin I <30 ng/L (blue curve), P = 0.0002. C, Kaplan-Meier plots severe COVID-19-free survival according to lactate dehydrogenase (LDH) levels. LDH>300 UI/L (red curve) vs LDH <300 UI/L (blue curve), P = 0.031. D, Kaplan-Meier plots of COVID-19-free survival according to LDH levels. LDH>300 UI/L (red curve) vs LDH <300 UI/L (blue curve), P = 0.038.
F4
FIGURE 4.:
Circulating levels of coagulation markers are associated with COVID-19 severity and mortality. A, Kaplan-Meier plots of severe COVID-19-free survival according to D-dimer levels. D-dimer >960 µg/L (red curve) vs D-dimer ≤960 µg/L (blue curve), P = 0.003. B, Kaplan-Meier plots of COVID-19-free survival according to D-dimer levels. D-dimer >960 µg/L (red curve) vs D-dimer ≤960 µg/L (blue curve), P = 0.029. C, Kaplan-Meier plots of severe COVID-19-free survival according to fibrinogen levels. Fibrinogen >6 g/L (red curve) vs fibrinogen <6 g/L (blue curve), P = 0.016. D, Kaplan-Meier plots of COVID-19-free survival according to fibrinogen levels. Fibrinogen >6 g/L (red curve) vs fibrinogen <6 g/L (blue curve), P = 0.05.

Clinical Outcomes in Severe Versus Nonsevere Patients

At the time of analysis, the median follow-up time was 42 days (IQR: 35.2–45 d). Patients with severe COVID-19 had a higher risk of acute kidney injury (95% versus 66.7%, respectively, P = 0.04) and their mortality rate was as high as 42.9% (n = 9). All patients with nonsevere disease were successfully discharged as compared with 8 patients only (40%) in the severe group (P < 0.0001; Table 5).

DISCUSSION

There is an urgent need to shed further light on the clinical course and improve the prognostic stratification of COVID-19 in specific frail populations—including transplant recipients. We conducted the current study to address these issues and investigate whether biomarkers of CRS may predict outcomes.

Here, we show that KTR with COVID-19 was frequently aged >60 years and had a high burden of comorbidities. The clinical presentation was similar to that reported in the general population—with fever and cough being the 2 most common clinical signs.18-20 However, diarrhea in our sample was as frequent as cough (73.5%) and its prevalence was markedly higher than that described for the general population (3.8%–24%).18-20 Notably, other published series of KTR have reported a high prevalence of gastrointestinal symptoms (17%–55%).21-24 It is thus possible that the gastrointestinal manifestations of COVID-19 can occur more frequently in KTR—in whom they may cause acute renal injury and severe electrolyte disturbances. SARS-CoV-2 proactively infects human gut enterocytes25 and can be detected in stools from patients with diarrhea in 73.3%–85.7% of cases.26,27 In our study, only 2 patients underwent search of SARS-CoV-2 in fecal samples and 1 of them tested positive.

A remarkable finding of our study is that patients who were taking MMF/MPA as immunosuppressive drugs were more likely to be hospitalized than those on mTOR inhibitors. Whether this observation could be related to different activities of these drugs on SARS-CoV-2 replication remains unclear. Although an in vitro investigation has shown that MPA inhibits MERS-CoV replication, studies on marmosets have linked MMF use with severe and even fatal disease.28,29 Preliminary data indicate that mTOR inhibitor may potentially be useful to tackle SARS-CoV-2 infection.30

Overweight, age >60 years, and dyspnea at onset were associated with severe COVID-19 in our KTR, a finding in line with the general population.19,31,32 Nonetheless, KTR pose special challenges with regard to immunosuppression management. Because guidelines recommend reducing immunosuppressive therapy,33 MMF/MPA and mTOR inhibitors were withdrawn in all patients. Further, CNI were preferentially discontinued in severe patients. These results are largely in accordance with those of previous studies focusing on COVID-19 in KTR—in which antimetabolites and CNI were withdrawn in 68%–100% and 15%–22.9% of patients, respectively.21-23,34,35 In the present study, lopinavir-ritonavir was given to 4 patients only because of known pharmacokinetics interaction with CNI and mTOR inhibitors.34,36 The use of hydroxychloroquine was less frequent in our cohort (36.6%) than in published reports (60%–95%)21,34,35,37,38 because of frequent treatment-related adverse effects in KTR and inconclusive evidence on its efficacy from the current literature.

An interesting observation from our study is that the inflammatory biomarkers IL-6 and CRP predict severe COVID-19 and COVID-19-related mortality in KTR, a finding in line with those previously obtained in the general and KTR population.18-21,39 These results point to a key role for proinflammatory mediators in the pathogenesis of severe COVID-19—which is currently conceptualized as a condition in which a dysregulated hyperinflammatory reaction of the host’s immune system to SARS-Cov-2 infection occurs.7,9,40 Here, we identified for the first time the optimal cutoff for IL-6 in the prediction of severe disease and mortality (65 ng/L)—a value in line with that previously reported to be associated with respiratory failure (80 ng/L).41 Interestingly, we also demonstrate that IL-6 was higher in overweight patients—who are prone to develop severe COVID-19 manifestations. Adipose tissue is an immune organ capable of secreting IL-6,42,43 especially under hypoxic conditions.44 This observation offers a potential explanation for the severe disease course of COVID-19 in overweight/obesity.

Here, we provide pilot evidence that hs-troponin I—a biomarker specific for myocardial injury—may serve as an early marker of disease severity and mortality. This is in line with the presence of cardiac involvement in ~20% of hospitalized patients with COVID-19.45 The association between IL-6 and hs-troponin I may also suggest a role for CRS in the pathogenesis of cardiac injury induced by SARS-CoV-2. Autopsy studies of patients with SARS caused by SARS-CoV found evidence of myocarditis and cardiomyocyte hypertrophy even though there was no direct evidence of viral RNA in the myocytes. These findings suggested that cardiac damage was not a direct consequence of cardiomyocyte infection.46 Further, IL-6 signaling reduces basal cardiac contractility and is capable of inducing hypertrophy.47 Serum levels of IL-6 and IL-6 gene polymorphisms have also been associated with myocarditis,48 endothelial dysfunction,49 and cardiovascular disease.50-55

D-dimer is a known biomarker of severe COVID-19 where it reflects a high thrombotic risk.56 We found that IL-6 increased early during the course of severe disease whereas D-dimer peaked in later phases. Further, we identified a correlation between IL-6 and D-dimer in COVID-19—an association that reflects a potential link between inflammation and thrombosis. Increased IL-6 levels have been previously associated with hypercoagulation,57 deep vein thrombosis,58 and cardiovascular disease.59 IL-6 is also capable of inducing platelet aggregation and adhesion.60

Owing to the paramount role of CRS in the deterioration of respiratory state, 14 (34%) KTR received high-dose steroids upon the identification of increased CRS biomarkers. The timing of steroids administration is probably paramount to optimize outcomes as data from observational studies have been conflicting. Large randomized controlled trials aimed at clarifying the benefits and risks of corticosteroids in COVID-19 are currently ongoing. IL-6 blockade with tocilizumab is another strategy to effectively tackle CRS and yielded promising results in small series of KTR and in the general population with COVID-19.35,39 Here, we show that 3 of the 4 patients with CRS who received tocilizumab had favorable outcomes. The patient who did not benefit from the drug received it in a late critical stage when ICU admission was denied. Despite a high mortality rate (32.5%), a recent observational study conducted in 80 KTR patients treated with tocilizumab concluded that this drug is potentially useful to attenuate the adverse consequences of CRS in patients with severe COVID-19.61

Our data do not support a prognostic impact of viral load measured on admission in nasopharyngeal swabs. There are conflicting data on this topic in the literature with most40,62,63 but not all64 studies indicating a lack of association between viral load and disease severity and/or prognosis of COVID-19. Our findings from a well-characterized cohort of KTR suggest that CRS biomarkers may be superior to viral load for predicting outcomes.

The mortality rate of COVID-19 in our KTR was 16% after a median follow-up of 34 days (30-d mortality in hospitalized patients: 19.5%). Previous studies conducted in KTR reported mortality rates between 6.66% and 33%.22,24,65,66 Such unfavorable mortality figures are likely reflective of the significant comorbidity burden typical of this frail patient population.

To our knowledge, this study is one of the largest to describe the clinical course of COVID-19 in KTR, with a special focus on the prognostic significance of CRS biomarkers. Our data indicate that biomarkers of inflammation, cardiac injury, and coagulopathy all have prognostic significance in this clinical entity. Taken together, our findings suggest that anti-inflammatory strategies (eg, high-dose steroids and IL-6 blockade) and anticoagulant therapy may serve as potential therapeutic tools to reduce disease severity and mortality in KTR with COVID-19.

ACKNOWLEDGMENTS

We thank the nephrologists of Colmar Hospital, Haguenau Hospital, and Mulhouse Hospital.

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