Literature DB >> 32871594

Impact of first-wave COronaVIrus disease 2019 infection in patients on haemoDIALysis in Alsace: the observational COVIDIAL study.

Nicolas Keller1, François Chantrel2,3, Thierry Krummel1, Dorothée Bazin-Kara1, Anne Laure Faller4,5, Clotilde Muller4,5, Thimothée Nussbaumer6,7, Manfred Ismer6,7, Abdellatif Benmoussa8, Mohamed Brahim-Bouna8, Stéphanie Beier5, Peggy Perrin9, Theirry Hannedouche1,5.   

Abstract

BACKGROUND: There are only scarce data regarding the presentation, incidence, severity and outcomes of coronavirus disease 2019 (COVID-19) in patients undergoing long-term haemodialysis (HD). A prospective observational study was conducted in eight HD facilities in Alsace, France, to identify clinical characteristics of HD patients with COVID-19 and to assess the determinants of the risk of death.
METHODS: All HD patients tested positive for COVID-19 from 5 March to 28 April 2020 were included. Collected data included patient characteristics, clinical features at diagnosis, laboratory data, treatments and outcomes.
RESULTS: Among 1346 HD patients, 123 tested positive for COVID-19. Patients had a median age of 77 years (interquartile range 66-83), with a high number of comorbidities (3.2 ± 1.6 per patient). Symptoms were compatible in 63% of patients. Asthenia (77%), diarrhoea (34%) and anorexia (32%) were frequent at diagnosis. The delay between the onset of symptoms and diagnosis, death or complete recovery was 2 (0-5), 7 (4-11) and 32 (26.5-35) days, respectively. Treatment, including lopinavir/ritonavir, hydroxychloroquine and corticosteroids, was administered in 23% of patients. The median C-reactive protein (CRP) and lymphocyte count at diagnosis was 55 mg/L (IQR 25-106) and 690 Ly/µL (IQR 450-960), respectively. The case fatality rate was 24% and determinants associated with the risk of death were body temperature {hazard ratio [HR] 1.96 [95% confidence interval (CI) 1.11-3.44]; P = 0.02} and CRP at diagnosis [HR 1.01 (95% CI 1.005-1.017); P < 0.0001].
CONCLUSIONS: HD patients were found to be at high risk of developing COVID-19 and exhibited a high rate of mortality. While patients presented severe forms of the disease, they often displayed atypical symptoms, with the CRP level being highly associated with the risk of death.
© The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Entities:  

Keywords:  COVID-19; epidemiology; haemodialysis; mortality

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Substances:

Year:  2020        PMID: 32871594      PMCID: PMC7499735          DOI: 10.1093/ndt/gfaa170

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN: 0931-0509            Impact factor:   5.992


KEY LEARNING POINTS

What is already known on this topic? as of 28 April 2020, there were 129 859 cases of confirmed COVID-19 and 23 660 deaths in France. there are only scarce data regarding the presentation, incidence, severity and outcomes of COVID-19 in patients undergoing long-term haemodialysis (HD). What this study adds? HD patients often displayed an atypical presentation, such as gastrointestinal involvement, less hyperthermia, a much more severe form of COVID-19 and delayed viral clearance. the incidence and mortality rate of COVID-19 were much higher in HD patients than in the general population. C-reactive protein and body temperature at admission were predictive of the risk of death. What impact may this have on practice or policy? screening indications should be comprehensive in this population to ensure adequate isolation and repeated reverse transcription–polymerase chain reaction testing would be advisable before ending isolation in COVID-19 HD patients. we suggest strict implementation of ‘barrier gestures’ in these patients in whom strict containment cannot be secured due to the regular need for dialysis. because of the substantial vulnerability of our patients, the prioritized distribution of personal protective equipment in a period of relative shortage or more extensive indications for hospitalization should be considered.

INTRODUCTION

Since late December 2019, an outbreak of a novel coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan, China. The first case of coronavirus disease 2019 (COVID-19) in France was diagnosed on 24 January in Paris. A cluster was identified on 3 March, following an evangelist gathering between 17 and 21 February in Alsace, France. Since then, the northeastern regions of France have been severely struck by the pandemic (1178 in-hospital deaths in Alsace as of 28 April among 14 810 total in-hospital deaths in France and 1.89 million inhabitants in Alsace). Early reports have suggested that patients with chronic kidney disease could be more susceptible to a severe form of COVID-19 {odds ratio [OR] 3.03 [95% confidence interval (CI) 1.09–8.47]} [1, 2]. However, there are only scarce data regarding the presentation, incidence, severity and outcomes of COVID-19 in HD patients. Currently, available information is based on case reports or small case series [3-5]. Given the rapid pace of the pandemic, we were compelled to gather an epidemiologic overview of COVID-19 HD patients and their specificities to optimize medical care. Herein we report the results of an observational study in a cohort of HD patients from eight HD facilities in Alsace, France. This study provides an overview of the clinical presentation and outcomes of COVID-19 in HD patients in centres on the front line of COVID-19 during the first French wave of the epidemic.

MATERIALS AND METHODS

Data were collected from 5 March, the first confirmed dialysis case of COVID-19, to 28 April 2020 from adult (≥18 years old) patients undergoing long-term HD and testing positive for COVID-19. A positive test for COVID-19 was defined by either a positive reverse transcription–polymerase chain reaction (RT-PCR) test on a nasopharyngeal swab or compatible radiologic findings on a low-dose computed tomography (LD-CT) scan. Eight HD facilities in three cities participated in the study: Strasbourg [Clinique St Anne, Association pour l'utilisation du rein artificiel en Alsace (AURAL) Bergson, Hôpitaux Universitaires de Strasbourg], Colmar (AURAL Colmar, Hôpitaux Civils de Colmar) and Mulhouse (Hôpital Emile Muller, Diaverum private centre, AURAL Mulhouse). These eight facilities provided HD treatment for 1346 patients in Alsace. The collected data were as follows: General characteristics and demographics. Comorbidities, including age >75 years, functional disabilities, obesity (body mass index >30 kg/m2), history of cancer (<5 years), current immunosuppression (history of transplantation, autoimmune disease, chemotherapy <5 years), chronic respiratory disease (e.g. chronic obstructive pulmonary disease, sleep apnoea treated with continuous positive airway pressure, need for long-term oxygen therapy), stroke, peripheral arterial disease, ischaemic heart disease and diabetes. A histroy of high blood pressure was not taken into account, due to its nearly ubiquitous prevalence in this population. Diagnostic methods: RT-PCR on a nasopharyngeal swab, LD-CT scan indicating the extent of the impairment (minimal if <10% of the pulmonary parenchyma, mild if 10–25%, mild–severe if 25–50%, severe if 50–75%, critical if >75%). Clinical presentation at diagnosis: date of onset of symptoms, date of diagnosis and dat of hospitalization, if needed. Clinical features and the severity of the infection at the time of diagnosis were documented [asymptomatic, moderate if not requiring oxygen supply or mild symptoms either with ambulatory care or hospitalization, severe if admission required for oxygen supply or severe symptoms, critical if hospitalization in an intensive care unit (ICU) or oxygen supply >10 L/min]. Laboratory characteristics at diagnosis: C-reactive protein (CRP), procalcitonin (PCT), lymphocyte count, serum albumin, electrolyte disorders (either plasma potassium <3.5 mmol/L or serum calcium <2.20 mmol/L or serum magnesium <0.70 mmol/L). Treatment: oxygen therapy (none or need for a nasal cannula or simple face mask with flow rate in liters per minute), non-invasive ventilation or assisted ventilation, antibiotic and specific treatments (none, lopinavir/ritonavir combination, hydroxychloroquine, corticosteroids). The delay between initiation of therapy and the date of diagnosis and the onset of symptoms was also documented. Laboratory evolution: at Day 7 and Day 14 (CRP, PCT, lymphocyte count, serum albumin, lactate dehydrogenase and ferritin). Clinical outcomes: hospitalization, length of hospital stay, hospitalization in the ICU, evolution at Days 3, 7, 10, 14 and 21 after diagnosis (stability, improvement, deterioration or deceased) and weight loss. The patient’s condition on 28 April was also noted: discharged from hospital care, still hospitalized, transferred to a rehabilitation centre, ambulatory care or deceased. Recovery status and recovery time were reported. Complete recovery was defined as two consecutive negative RT-PCRs on nasopharyngeal swabs after a minimum time of 24 days after the onset of symptoms and with at least 48 h without symptoms.

Statistical analysis

Quantitative data are described as median and interquartile range (IQR) or mean and standard deviation (SD) according to the normality of the distribution. Distribution normality was tested graphically and with the Shapiro–Wilk test. Comparisons were performed using the Student’s t-test or the Mann–Whitney test, as appropriate. Qualitative data are described according to the frequency for each modality and compared with Fisher’s exact test. Risk factors for death were analysed with a multivariate Cox model including variables with a P-value <0.2 in the univariate comparison between deceased and surviving patients. Statistical significance was defined as P < 0.05. All statistical analyses were performed with STATA/MP 13.1 (StataCorp, College Station, TX, USA).

RESULTS

Between 5 March and 28 April, 123 patients undergoing long-term haemodialysis (HD) were infected with COVID-19 (Mulhouse, n = 64; Strasbourg, n = 45; Colmar, n = 14), representing 9.1% of all patients undergoing long-term HD in our centres (n = 1346). The cumulative and incident cases in included HD facilities are presented in Supplementary data, Appendix 1. Patient characteristics, demographics and comorbidities at the time of diagnosis are summarized in Table 1. Of note, a history of high blood pressure was found in 97.5% of patients.
Table 1

Patient characteristics

CharacteristicsResultsAvailable/total, n/N
Demographics at the time of diagnosis
 Age (years), median (IQR)77 (68–83)123/123
 Age >75 years, n (%)71 (58)123/123
 Gender (male), n (%)70 (57)122/123
 Functional disability, n (%)109/123
  Total autonomy37 (34)
  Partial autonomy56 (51)
  None16 (15)
 Kidney disease, n (%)117/123
  Diabetic42 (36)
  Glomerulonephritis17 (14.5)
  CIN/uropathy18 (15.5)
  Vascular14 (12)
  APKD10 (8.5)
  Unknown16 (13.5)
Comorbidity at the time of diagnosis, n (%)
 Presence of comorbidity118 (97.5)121/123
 Number of comorbidities, mean ± SD3.2 ± 1.6118/123
 Cancer24 (20)
 Immunosuppression18 (15)
 Stroke26 (22)
 Peripheral arterial disease41 (35)
 Ischaemic heart disease54 (46)
 Diabetes63 (53)119/123
 Chronic respiratory disease40 (34)119/123
 Obesity40 (36)112/123
Clinical features at the time of diagnosis, n (%)
 Fever61 (57)107/123
 Body temperature (°C), mean ± SD37.8 ± 1100/123
 Cough77 (69)112/123
 Dyspnoea55 (51)107/123
 SpO2 (%), median (IQR)95 (90–98)95/123
 SpO2 <93%42 (44)
 Asthenia82 (77)106/123
 Diarrhoea35 (34)102/123
 Anorexia33 (32)103/123
 Myalgia20 (20)102/123
 Anosmia6 (6)103/123
 Other ENT symptoms14 (14)103/123
 Headache11 (11)103/123
Severity of the disease, n (%)120/123
 Asymptomatic4 (3)
 Moderate62 (52)
 Severe43 (36)
 Critical11 (9)

CIN, chronic interstitial nephropathy; BMI, body mass index; SpO2: pulsatile saturation in oxygen; ENT, ear, nose and throat.

Patient characteristics CIN, chronic interstitial nephropathy; BMI, body mass index; SpO2: pulsatile saturation in oxygen; ENT, ear, nose and throat.

Diagnosis

The median time between first symptoms and diagnosis was 2 days (IQR 0–5). The origin of the contamination was unknown in the majority of cases (62.5%). Otherwise, the contamination mostly occurred in patients living in institutions (40%) or intrafamilial settings (29%). Of note, 21% of infections were due to nosocomial contamination (already in a hospital unit or rehabilitation unit for at least 7 days for another reason before the onset of symptoms) and 10% were related to an evangelist gathering cluster in Mulhouse. There was no evidence of either vertical or horizontal transmission within the HD units. The clinical features and severity of the disease at the time of diagnosis are presented in Table 1. Symptoms were found to be compatible with COVID-19 infection (a combination of at least two symptoms among fever, cough and dyspnoea) in 63% of patients. The primary method of diagnosis was RT-PCR of a nasopharyngeal swab for 112 patients, which was contributive in 88%. LD-CT scan was performed on 64 patients and was contributive in 88% and confirmed the diagnosis in 13 patients that had an initially negative RT-PCR. The extent of the impairment (available for 49/64 patients) on LD-CT scan was minimal in 13 (26.5%), mild in 21 (43%), mild–severe in 6 (12%), severe in 7 (14.5%) and critical in 2 (4%) patients. Laboratory findings at the time of diagnosis are provided in Table 2. Of note, the median maximal CRP level was 112 mg/L (IQR 56–203) and was reached after a median delay of 7 days (IQR 4–12) after the onset of symptoms.
Table 2

Laboratory characteristics of HD patients with COVID-19

CharacteristicsAt diagnosis (N = 123)Day 7 post-diagnosis (N = 102)Day 14 post-diagnosis (N = 83)Normal range
CRP (mg/L), median (IQR)55 (25–106),55 (15–113),19 (7–58),0–4
n = 113 n = 81 n = 58
Procalcitonin (µg/L), median (IQR)0.805 (0.475–2.115),1 (0.5–3.54),0.42 (0.2–2.03),0–0.5
n = 32 n = 31 n = 14
Lymphocyte count (Ly/µL), median (IQR)690 (450–960),635 (425–1010),870 (600–1250),1.000–4.000
n = 109 n = 76 n = 57
Serum albumin (g/L), mean ± SD35 ± 6,NC32 ± 7,35–50
n = 70 n = 39
Ferritin (µg/L), median (IQR)NA1188 (840–2060),NA23–322
n = 41
LDH (U/L), median (IQR)NA280 (215–346),NA120–246
n = 31

n, Number of available data/number of patients; LDH, lactate dehydrogenase; NA, not available.

Laboratory characteristics of HD patients with COVID-19 n, Number of available data/number of patients; LDH, lactate dehydrogenase; NA, not available.

Treatment

Sixty per cent of the patients required oxygen support therapy at the time of diagnosis. When oxygen therapy was needed, the median time between the onset of symptoms or time of diagnosis and maximal oxygen therapy was 8 days (IQR 3–11) and 2 days (IQR 0–8), respectively (data available in 29 patients). Antibiotic therapy was initiated in 77% of patients after a median delay of 0 days (IQR −1–1) and 3 days (IQR 1–5) after diagnosis and symptoms onset, respectively. A putative antiviral therapy was initiated at the discretion of the physician in 23% of patients after a median delay of 2 days (IQR 1.5–3.5) and 4.5 days (IQR 3–9.5) after diagnosis and symptoms onset, respectively. This treatment was discontinued in 4/23 patients due to intolerance or medical contraindication. The main reasons for non-prescription of a specific therapy were the clinician’s choice and the absence of guidelines in HD patients (65%). An overview of treatments is provided in Table 3.
Table 3

Treatment in HD patients with COVID-19

TreatmentResultsAvailable/total, n/N
Antibiotic treatment, n (%)76 (77)99/123
 Cephalosporin56 (78)
 Macrolide24 (33)
Specific treatment, n (%)23 (23)100/123
 Lopinavir/ritonavir10 (38.5)
 Hydroxychloroquine12 (46)
 Corticosteroid5 (19)
Oxygen therapy, n (%)68 (60)114/123
 Artificial ventilation5 (4)
 Initial oxygen therapy (L/min), median (IQR)0 (0–2)109/123
 Maximal oxygen therapy (L/min), median (IQR)2 (0–6)111/123
Treatment in HD patients with COVID-19

Outcomes at the time of writing

Hospitalization was required in 71% of patients after a median time of 2 days (IQR 0–5) after symptoms onset, seven of whom were transferred to the ICU. The median hospital stay was 9 days (IQR 4–14). At the time of writing, follow-up data on 117/123 patients were available: 39 (33%) were discharged from the hospital, 11 (9%) remained hospitalized, 27 (23%) had only ambulatory care, 11 (9%) were transferred to a rehabilitation centre and 29 (24%) had died. Complete recovery was observed in 30 (24%) patients after a median interval of 32 days (IQR 26.5–35) after the onset of symptoms. In survivors at Day 21 (n = 63), 52% had a sustained positive RT-PCR on a nasopharyngeal swab or had no control exam until this time. Supplementary data, Appendix 2 depicts the time interval until complete recovery, death or the end of the observation time. Of note, a mean weight loss of −2.4 ± 2.7 kg (SD −13–1.5) was observed.

Deceased patients

Twenty-nine (24%) patients died from COVID-19, three of whom died in the ICU. The median time between symptoms onset and death was 7 days (IQR 4–11). The Kaplan–Meier survival curve is presented in Figure 1 . A comparison of deceased and surviving patients is shown in Table 4.
FIGURE 1

Kaplan–Meier survival curves in HD patients after onset of symptoms and according to CRP quartile.

Table 4

Comparison of deceased and surviving patients

CharacteristicsDeceased patients (n = 29)
Surviving patients (n = 94)
P-value
Available in each group/total, n/N
Demographics at the time of diagnosis
 Age (years), median (IQR)80 (72–88)75.5 (64–83)0.04(29/94)/123
 Age >75 years, n (%)19 (66)52 (55)0.39123/123
 Gender (male), n (%)18 (62)52 (56)0.67122/123
 Functional disability, n (%)0.13109/123
  Total autonomy5 (20)32 (38)
  Partial autonomy14 (56)42 (50)
  None6 (24)10 (12)
 Comorbidity, n (%)28 (100)90 (97)1121/123
  Number of comorbidities, mean ± SD3.4 ± 1.33.1 ± 1.60.28(28/90)/123
 Obesity, n (%)8 (33)32 (36)1.0112/123
 Severity of the disease at diagnosis, n (%)<0.001120/123
  Asymptomatic0 (0)4 (4)
  Moderate9 (31)53 (58)
  Severe11 (38)32 (35)
  Critical9 (31)2 (2)
Clinical features at the time of diagnosis
 Body temperature, mean ± SD38.2 ± 137.7 ± 10.056(24/76)/123
 SpO2, median (IQR)92 (85–97)96 (90–98)0.07(22/73)/123
Laboratory and LD-CT scan characteristics, median (IQR)
 CRP at diagnosis (mg/L)95 (49–192)44.5 (19–92)0.0003(25/88)/123
 CRP peak (mg/L)220 (117–272)98.5 (44–147)0.0002(23/70)/123
 Procalcitonin at diagnosis (ng/mL)1.7 (0.83–5.7)0.8 (0.34–1.7)0.12(5/27)/123
 Lymphocyte count at diagnosis (Lym/µL)530 (420–910)720 (461–995)0.36(23/86)/123
 CRP at D7 (mg/L)157 (72–222)43 (14–94)0.0004(11/70)/102
 Lymphocyte count at Day 7 (WBC/µL)410 (300–550)670 (450–1040)0.017(10/66)/102
Extent of impairment on the initial LD-CT scan, n (%)0.5448/62
 Minimal2 (22)11 (28)
 Mild5 (56)16 (41)
 Mild to severe0 (0)6 (15)
 Severe1 (11)5 (13)
 Critical1 (11)1 (3)
Therapy during period of care, n (%)
 Antibiotic treatment19 (78)57 (71)0.5699/123
 Specific treatment8 (28)15 (21)0.5594/123
 Oxygen therapy24 (92)44 (50)<0.005114/123
 Artificial ventilation4 (15)1 (1)0.009114/123
 Initial oxygen therapy (mL/min), median (IQR)2 (0–4)0 (0–2)0.0028(26/83)/123
 Maximal oxygen therapy (mL/min), median (IQR)15 (4–15)0 (0–3)<0.0005(25/86)/123

SpO2, pulsatile saturation in oxygen.

Comparison of deceased and surviving patients SpO2, pulsatile saturation in oxygen. At diagnosis, deceased patients presented a significantly older age, a more severe presentation, a higher CRP level, a higher body temperature and more often required oxygen therapy and at a higher flow. Patients who died more frequently had a typical presentation of the disease at diagnosis compared with survivors (85% versus 57%; P = 0.011), including dyspnoea (70% versus 45%; P = 0.027). Clinical features at diagnosis were critical in 31% (compared with 2% in survivors) and moderate in 31% (compared with 58% in survivors). Of note, compared with survivors, deceased patients more frequently had diabetic kidney disease (48% versus 32%) or an autosomal polycystic kidney disease (APKD) (15% versus 7%). None of the specific comorbidities was associated with the risk of death, while only a history of ischaemic heart disease tended to be more frequent in deceased patients (61% versus 41%; P = 0.084). A Cox model was subsequently constructed for multivariate analysis. Included in this model were age, autonomy (total autonomy or not), pulsatile saturation in oxygen (SpO2) and oxygen therapy at diagnosis, body temperature and CRP at diagnosis. PCT was not included due to the amount of missing data. When taking into account all of the clinical symptoms, only body temperature at diagnosis was associated with the risk of death {hazard ratio [HR] 1.96 [95% confidence interval (CI) 1.11–3.44]; P = 0.02}. CRP at diagnosis was also associated with the risk of death [HR 1.01 (95% CI 1.005–1.017); P < 0.0001]. The results of the multivariate analysis are presented in Table 5, while the Kaplan–Meier survival curves according to CRP quartile are shown in Figure 1.
Table 5

Multivariate analyses of factors associated with the risk of death

FactorsHRP-valueIQR
Age1.030.180.987–1.072
Partial or no autonomy0.660.590.14–3.05
Oxygen therapy1.13 × 10161.0
SpO2 at diagnosis0.970.310.90–1.03
Body temperature at diagnosis (per 1°C)1.960.021.11–3.44
CRP at diagnosis (per 1 mg/dL)1.01<0.00011.005–1.017

Multivariate analysis performed on only 83 patients due to missing data.

SpO2, pulsatile saturation in oxygen.

Kaplan–Meier survival curves in HD patients after onset of symptoms and according to CRP quartile. Multivariate analyses of factors associated with the risk of death Multivariate analysis performed on only 83 patients due to missing data. SpO2, pulsatile saturation in oxygen.

DISCUSSION

The rapid outbreak of the COVID-19 pandemic represented an unexpected challenge for the medical community. Although the epidemic curve is descending in many countries, the imminent end of containment measures raises the risk of a second wave [6, 7], and any new disease-related information would be useful to improve care. Given the lack of knowledge relative to specific and vulnerable patients, we report herein on a series of patients undergoing long-term HD in eight facilities in Alsace, France, where the first cluster of COVID-19 occurred. The incidence of COVID-19 was much higher in our HD patients than in the background population (9.1% versus 0.16%). There are various putative explanations. First, our HD population carried comorbidities at risk of COVID-19 infection. Second, physical distancing is challenging during HD sessions, in the waiting room, during transport to HD facilities and in living facilites (many patients live in nursing homes). Finally, these patients are in contact with healthcare providers three times a week, such that screening was likely more thorough than in the general population. There was no evidence for transmission within our HD units, as the first cases occurred in patienta treated in separate rooms and containment measures were immediately applied for all suspected patients. Indeed, each patient presenting to the HD unit with any symptom suggestive of COVID-19 was admitted to a dedicated isolated room until the RT-PCR result was available. All patients with proven COVID-19 remained thereafter in an isolated room to avoid nosocomial transmission. In the first reports in the Chinese population [2, 8], only 25–50% of patients had at least one comorbidity, which is far below our findings. Compared with hospitalized US patients who had more similar clinical characteristics and a significant number of comorbidities (88% with at least one comorbidity) [9], our patients were older and slightly less obese. Notwithstanding, our patients more frequently had diabetes, chronic respiratory disease and a history of cancer. The question of whether end-stage kidney disease (ESKD) per se or the comorbidities associated with ESKD worsens the outcome remains to be determined. Compared with HD patients of the nationwide French Renal Epidemiology and Information Network (REIN) registry [10], patients in our cohort were older (74 ± 15 versus 69 ± 15 years) and were more likely to have APKD (8.5% versus 5.8%), obesity (36% versus 29%), chronic respiratory disease (34% versus 19%), cancer (20% versus 12%), ischaemic heart disease (45.6% versus 29%), stroke (22% versus 13%) and peripheral arterial disease (34.7% versus 21%). These observations highlight the substantial vulnerability of our cohort, i.e. the ‘frails upon the frails’. Moreover, the higher proportion of patients with partial (51.4% versus 8.5%) or an absence of autonomy (15% versus 8.5%) would explain both the higher vulnerability of these patients and the frequent need for external or institutional help, which could be a vector of contamination. This suggests that ‘barrier gestures’ should be strictly implemented in these patients in whom strict containment cannot be secured due to the need for dialysis. Screening indications should be comprehensive in this population to ensure adequate isolation when needed. Also, the favoured distribution of personal protective equipment in a period of relative shortage or wider indications for hospitalization should be considered. Typical symptoms of COVID-19 infection have been initially described as fever, cough and dyspnoea [11]. Fever was inconsistent in our cohort compared with previous reports (57% versus 98%) [8, 11]. A lack of fever is frequent in infected HD patients, who tend to be slightly hypothermic in baseline conditions [12]. A considerable proportion of our patients presented with less typical symptoms, mostly asthenia, diarrhoea and anorexia. The latter has been previously described in the general COVID-19 population [8, 13–15] as well as in a case report of HD patients [16] and kidney transplants [17]. For example, diarrhoea, initially described as an uncommon symptom [8], was found in 34% of our patients. The extensive screening in our patients likely enabled the detection of atypical forms, although more frequent gastrointestinal involvement in patients with ESKD cannot be excluded. Lymphopaenia was frequent in our cohort, as also previously described in the general COVID-19 population [8, 9, 11, 15], and associated with the severity of the disease [18]. This was attributed not only to a chronic endothelial dysfunction in ageing patients with chronic disease, but also to a direct cytotoxic action of the virus [15, 19]. Lymphopaenia should be considered both as part of the diagnosis and as a marker of the risk level of the disease [20]. In this study, CRP was higher than in previous studies conducted in the general COVID-19 population, even those patients with severe disease [8, 9, 11]. Of particular note, CRP was predictive of the risk of death in our cohort of COVID-19 HD patients. Such an association between CRP and disease severity was previously reported and associated with the extent of impairment on LD-CT scan (correlation coefficient 0.873, 0.734; P < 0.001) [21, 22]. Some authors have suggested the use of a predictive score based on CRP and lung volume involvement on LD-CT scan at the time of diagnosis [21, 22]. High PCT (>0.5 ng/mL), an uncommon finding in the general COVID-19 population [8, 9, 11], was more frequent in our cohort. The mortality rate in our cohort was much higher than in the general COVID-19 population: 24% compared with the 1–5% mortality in the general COVID-19 population [23] and 8–15% mortality among patients >70 years old [9, 23]. An abysmal prognosis was previously described in a small cohort of kidney transplant recipients in the USA [17], with an early mortality rate of 28% at 3 weeks. A similar mortality rate of 26% was found in Italian [24] patients admitted to the ICU who had fewer comorbidities and were younger [median age 63 years (IQR 56–70)]. These findings thus emphasize the detrimental effect of ESKD and comorbidity burden over that of age. We did not find any association between age and risk of death in our cohort, in contrast to the general population. This discrepancy could be explained by the more advanced age of our cohort, as we compared old versus very old patients, which might have attenuated the differential risk. However, one should bear in mind that our HD population had a much higher mortality rate (16%) than that found in the general COVID-19 population (0.91%), with a steeper effect of age [10, 25]. Our results suggest an estimated mortality rate of 26.7%, but the exact case fatality rate (CFR) should take into account the asymptomatic patients, whose exact percentage was unknown in our population. A noteworthy observation was the poor and prolonged viral clearance in our patients. Only 24% of our patients had viral clearance after a median of 32 days after onset of symptoms. while viral clearance was initially reported after a median time of 17–20 days in the general COVID-19 population [26, 27]. However, a recent study [28] found a viral clearance after a median of 24 days, with a maximum duration of 42 days, which is more in line with our population. Age and ESKD are well-identified causes of immune dysfunction, which could delay viral clearance [29]. In addition, the higher prevalence of a severe form of the disease could be associated with prolonged viral shedding [27]. Currently French guidelines [30] recommend the end of isolation 24 days after the onset of symptoms in immunocompromised patients, without control RT-PCR testing. Given the present data, it would seem cautious to perform another RT-PCR test before ending isolation. In our opinion, and considering the false negative rate of ∼30% [31, 32], a minimum of two consecutive negative swabs would appear to be a sound precaution. Our study has certain limitations. The cohort was modestly sized and we could not perform a proper comparison due to the lack of other reported cohorts in HD patients. The number of missing data also represents a drawback. Finally, the absence of systematic screening in both the general and specific COVID-19 populations such as ours may limit our conclusions, especially regarding the CFR. Further larger studies are necessary to estimate the risk factors in the HD population. The high mortality rate in our patients also points to the need for randomized controlled studies on antiviral therapy.

CONCLUSION

In the present report, we describe a cohort of 123 HD patients presenting with symptomatic COVID-19 together with their clinical profiles and outcomes. HD patients were found to be at high risk of developing COVID-19. Several clinical characteristics, including atypical presentation, the predictive value of elevated CRP and delayed viral clearance, were worth noting and could be specific for this population. The outcomes were abysmal in this particularly vulnerable population, with a mortality rate of 24%.

SUPPLEMENTARY DATA

Supplementary data are available at ndt online. Click here for additional data file.
  30 in total

1.  Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China.

Authors:  Jin-Jin Zhang; Xiang Dong; Yi-Yuan Cao; Ya-Dong Yuan; Yi-Bin Yang; You-Qin Yan; Cezmi A Akdis; Ya-Dong Gao
Journal:  Allergy       Date:  2020-02-27       Impact factor: 13.146

2.  2017 Annual Report Digest of the Renal Epidemiology Information Network (REIN) registry.

Authors:  Mathilde Lassalle; Elisabeth Monnet; Carole Ayav; Julien Hogan; Olivier Moranne; Cécile Couchoud
Journal:  Transpl Int       Date:  2019-07-04       Impact factor: 3.782

3.  Estimating the burden of SARS-CoV-2 in France.

Authors:  Henrik Salje; Cécile Tran Kiem; Noémie Lefrancq; Noémie Courtejoie; Paolo Bosetti; Juliette Paireau; Alessio Andronico; Nathanaël Hozé; Jehanne Richet; Claire-Lise Dubost; Yann Le Strat; Justin Lessler; Daniel Levy-Bruhl; Arnaud Fontanet; Lulla Opatowski; Pierre-Yves Boelle; Simon Cauchemez
Journal:  Science       Date:  2020-05-13       Impact factor: 47.728

4.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

5.  Clinical Characteristics and Outcomes of Older Patients with Coronavirus Disease 2019 (COVID-19) in Wuhan, China: A Single-Centered, Retrospective Study.

Authors:  TieLong Chen; Zhe Dai; Pingzheng Mo; Xinyu Li; Zhiyong Ma; Shihui Song; Xiaoping Chen; Mingqi Luo; Ke Liang; Shicheng Gao; Yongxi Zhang; Liping Deng; Yong Xiong
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2020-09-16       Impact factor: 6.053

6.  First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment.

Authors:  Kathy Leung; Joseph T Wu; Di Liu; Gabriel M Leung
Journal:  Lancet       Date:  2020-04-08       Impact factor: 79.321

7.  Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study.

Authors:  Li Tan; Qi Wang; Duanyang Zhang; Jinya Ding; Qianchuan Huang; Yi-Quan Tang; Qiongshu Wang; Hongming Miao
Journal:  Signal Transduct Target Ther       Date:  2020-03-27

8.  A Case of Novel Coronavirus Disease 19 in a Chronic Hemodialysis Patient Presenting with Gastroenteritis and Developing Severe Pulmonary Disease.

Authors:  Antoney J Ferrey; Grace Choi; Ramy M Hanna; Yongen Chang; Ekamol Tantisattamo; Kaushik Ivaturi; Elisa Park; Lawrence Nguyen; Brian Wang; Sam Tonthat; Connie M Rhee; Uttam Reddy; Wei Ling Lau; Susan S Huang; Shruti Gohil; Alpesh N Amin; Lanny Hsieh; Timmy T Cheng; Richard A Lee; Kamyar Kalantar-Zadeh
Journal:  Am J Nephrol       Date:  2020-03-28       Impact factor: 3.754

9.  Lymphopenic community acquired pneumonia as signature of severe COVID-19 infection.

Authors:  Jesús F Bermejo-Martin; Raquel Almansa; Rosario Menéndez; Raúl Mendez; David J Kelvin; Antoni Torres
Journal:  J Infect       Date:  2020-03-05       Impact factor: 6.072

10.  Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention.

Authors:  Zunyou Wu; Jennifer M McGoogan
Journal:  JAMA       Date:  2020-04-07       Impact factor: 56.272

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  17 in total

Review 1.  Risks and Benefits of Kidney Transplantation during the COVID-19 Pandemic: Transplant or Not Transplant?

Authors:  Maria Ajaimy; Luz Liriano-Ward; Jay A Graham; Enver Akalin
Journal:  Kidney360       Date:  2021-05-13

Review 2.  The frail world of haemodialysis patients in the COVID-19 pandemic era: a systematic scoping review.

Authors:  Gaetano Alfano; Annachiara Ferrari; Riccardo Magistroni; Francesco Fontana; Gianni Cappelli; Carlo Basile
Journal:  J Nephrol       Date:  2021-08-21       Impact factor: 3.902

3.  Trajectories of clinical and laboratory characteristics associated with COVID-19 in hemodialysis patients by survival.

Authors:  Sheetal Chaudhuri; Rachel Lasky; Yue Jiao; John Larkin; Caitlin Monaghan; Anke Winter; Luca Neri; Peter Kotanko; Jeffrey Hymes; Sangho Lee; Yuedong Wang; Jeroen P Kooman; Franklin Maddux; Len Usvyat
Journal:  Hemodial Int       Date:  2021-08-10       Impact factor: 1.543

Review 4.  Novel coronavirus disease in patients with end-stage kidney disease.

Authors:  Noriaki Shimada; Hiroaki Shimada; Yoshiaki Itaya; Yasuhiko Tomino
Journal:  Ther Apher Dial       Date:  2020-10-27       Impact factor: 2.195

Review 5.  [Experiences from the German COVID-19 register].

Authors:  Elion Hoxha
Journal:  Nephrologe       Date:  2020-12-09

6.  Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings.

Authors:  Mathias Haarhaus; Carla Santos; Michael Haase; Pedro Mota Veiga; Carlos Lucas; Fernando Macario
Journal:  Clin Kidney J       Date:  2021-02-05

7.  National survey on deceased donor organ transplantation during the COVID-19 pandemic in Japan.

Authors:  Taihei Ito; Takashi Kenmochi; Atsuhiko Ota; Kaori Kuramitsu; Akihiko Soyama; Osamu Kinoshita; Susumu Eguchi; Kenji Yuzawa; Hiroto Egawa
Journal:  Surg Today       Date:  2021-10-23       Impact factor: 2.549

8.  Risk of COVID-19 Disease, Dialysis Unit Attributes, and Infection Control Strategy among London In-Center Hemodialysis Patients.

Authors:  Ben Caplin; Damien Ashby; Kieran McCafferty; Richard Hull; Elham Asgari; Martin L Ford; Nicholas Cole; Marilina Antonelou; Sarah A Blakey; Vinay Srinivasa; Dandisonba C B Braide-Azikwe; Tayeba Roper; Grace Clark; Helen Cronin; Nathan J Hayes; Bethia Manson; Alexander Sarnowski; Richard Corbett; Kate Bramham; Eirini Lioudaki; Nicola Kumar; Andrew Frankel; David Makanjuola; Claire C Sharpe; Debasish Banerjee; Alan D Salama
Journal:  Clin J Am Soc Nephrol       Date:  2021-06-01       Impact factor: 10.614

9.  SARS-CoV-2 Infection in Patients on Dialysis: Incidence and Outcomes in the Lazio Region, Italy.

Authors:  Claudia Marino; Laura Angelici; Valentina Pistolesi; Santo Morabito; Anteo Di Napoli; Enrico Calandrini; Silvia Cascini; Anna Maria Bargagli; Nicola Petrosillo; Nera Agabiti; Marina Davoli
Journal:  J Clin Med       Date:  2021-12-13       Impact factor: 4.241

10.  The Global Impact of the COVID-19 Pandemic on In-Center Hemodialysis Services: An ISN-Dialysis Outcomes Practice Patterns Study Survey.

Authors:  Ryan Aylward; Brian Bieber; Murilo Guedes; Ronald Pisoni; Elliot Koranteng Tannor; Gavin Dreyer; Adrian Liew; Valerie Luyckx; Dibya Singh Shah; Chimota Phiri; Rhys Evans; Rehab Albakr; Jeffrey Perl; Vivekanand Jha; Roberto Pecoits-Filho; Bruce Robinson; Fergus J Caskey
Journal:  Kidney Int Rep       Date:  2021-12-13
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