Skip to main content
NCBI home page
Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
. 2021 Nov 1;57:103359. doi: 10.1016/j.msard.2021.103359

COVID-19 susceptibility and outcomes among patients with neuromyelitis optica spectrum disorder (NMOSD): A systematic review and meta-analysis

Mahdi Barzegar a,b, Omid Mirmosayyeb a,b, Narges Ebrahimi b, Sara Bagherieh b, Alireza Afshari-Safavi b,c, Ali Mahdi Hosseinabadi b, Vahid Shaygannejad a,b, Nasrin Asgari d,⁎
PMCID: PMC8558105  PMID: 35158468

Abstract

Background

We conducted this systematic review and meta-analysis to assess the risk of coronavirus disease (COVID-19), clinical features and outcome among patients with neuromyelitis optica spectrum disorder (NMOSD).

Methods

We systematically searched PubMed, Scopus, Web of Science, and Embase from December 1, 2019, to July 2, 2021. The gray literature including the references of original studies, review studies, conference abstracts, and WHO COVID-19 database was also searched. We included any type of studies that reported NMOSD patients with COVID-19, prevalence of COVID-19 among NMOSD patients or the infection outcome (hospitalization, intensive care unit [ICU] admission, or mortality).

Results

Out of 540 records, a total of 23 studies (19 published articles and 4 conference abstracts) including 112 NMOSD patients with COVID-19 met the inclusion criteria. Nine studies reporting risk of COVID-19 and nine studies on outcome were included in a quantitative synthesis. The pooled prevalence of COVID-19 was 1.2% (95% CI: 0.001%–0.030%; I2 = 92%, p< 0.001), with hospitalization of 33.7% (95% CI: 23.3–44.8%; I2 = 9.1%, p = 0.360) with 52.9% on rituximab treatment. ICU admission was 15.4% (95% CI: 7.6%-24.7%; I2 = 20.7%, p = 0.272) and mortality was 3.3% (95% CI: 0–9.7%; I2 = 21.3%, p = 0.253). Thirty-eight patients (48.7%) reported at least one comorbidity. The mean age of the included patients was 40.8 (10.63) years, female/male ratio was 3.35:1. The most common COVID-19 symptom was fever (54.5%), followed by fatigue/asthenia (42.9%), headache (41.6%), and cough (40.3%). Four patients developed neurological worsening. The Begg's and Egger's tests showed no evidence of publication bias.

Conclusion

The analysis suggests that comorbidity and treatment with rituximab may be risk factors for COVID-19 infection in NMOSD patients.

Keywords: Neuromyelitis optica spectrum disorder, Coronavirus, COVID-19, Infection, Prevalence, Outcome

1. Introduction

The outbreak of Coronavirus Disease 2019 (COVID-19), which is caused by Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2), has led to the tragic loss of over 4 million people as of June 23, 2021 with more than 18 million infected cases worldwide (World Health Organization, 2021). From the early stages of the outbreak, it has been suggested that patients with suppressed immune systems may be at an elevated risk of contracting the virus, experiencing more severe forms of the disease (World Health Organization, 2020).

Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune inflammatory disease of the central nervous system (CNS) that mainly presents with optic neuritis and myelitis (Wingerchuk et al., 2007). For many years, NMOSD was considered as a variant of multiple sclerosis (MS) (Wingerchuk et al., 2007). However, the discovery of anti-aquaporin 4 antibody (AQP4 Ab) and further immunological and pathological evidence characterised it a distinct entity different from MS, and defined NMOSD as an autoimmune astrocytopathy (Lennon et al., 2004; Lucchinetti et al., 2014). The disabling nature of NMOSD and the treatment with immunosuppressive therapies (e.g., azathioprine [AZA], mycophenolate mofetil [MMF], rituximab [RTX], and corticosteroids) predispose these patients to bacterial and viral infections (Luna et al., 2020; Ritter and Pirofski, 2009; Seksik et al., 2009). This raised a concern about the risk of severe COVID-19 in patients with NMOSD.

Available data suggests that mortality and hospitalization rates of COVID-19 among MS patients could be slightly higher than the general population (Barzegar et al., 2021b; Prosperini et al., 2021). Findings in patients with MS strengthen the assumption that NMOSD patients also may be at an increased risk of developing severe COVID-19. Current evidence on the effects of COVID-19 infection on NMOSD mostly is found in case reports and small observational studies. A systematic review by Sharifian-Dorche summarized the cases of COVID-19 with MS and NMOSD (Sharifian-Dorche et al., 2021). However, this study was conducted in the early stage of the pandemic, limited to a relatively small sample size, and did not include a meta-analysis. Moreover, the authors only searched the database PubMed and did not determine the risk of the infection in the NMOSD population.

Therefore, we conducted this systematic review and meta-analysis to bring together the existing evidence on the characteristics of COVID-19 infection in patients with NMOSD. The purposes of our systematic review were to characterize NMOSD patients with COVID-19, and to estimate the risk of COVID-19 and the outcomes of the infection among NMOSD patients.

2. Methods

2.1. Literature search

We searched PubMed, Scopus, web of science, and Embase from December 1, 2019, to July 2, 2021. We also searched the gray literature including the references of the included studies, review studies, conference abstracts, and WHO COVID-19 database. The following search strategy was used: (("NMO Spectrum Disorder" OR NMOSD OR NMO OR "Devic Disease" OR "Devic Syndrome" OR neuromyelitis optica" OR "neuromyelitis optica spectrum disorder) AND (“COVID 19″ OR “COVID-19 Virus Disease” OR “COVID 19 Virus Disease*” OR “Coronavirus Disease-19″ OR “Coronavirus Disease 19″ OR “2019 Novel Coronavirus Disease” OR “2019 Novel Coronavirus Infection” OR “2019-nCoV Disease” OR “2019 nCoV Disease” OR “2019-nCoV Diseases” OR “COVID-19 Virus Disease*”)). We customized our search syntax (query) for each data bank. This study was carried out following Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) guideline (Moher et al., 2015). The PRISMA check list is documented in Supplementary file.

2.2. Inclusion and exclusion criteria

All types of studies including case report/series, cross-sectional, case-control, and cohort studies that reported COVID-19 in patients with a previous NMOSD diagnosis were included. The outcomes were demographic and clinical characteristics of infected patients, COVID-19-related symptoms, susceptibility to COVID-19, COVID-19 outcomes (hospitalization, intensive care unit [ICU] admission, and mortality) in infected patients, and hospitalization status by different therapies. Cross-sectional, case-control, and cohort studies that reported COVID-19 susceptibility or outcomes (hospitalization, intensive care unit [ICU] admission, or death) were included in the meta-analysis. The exclusion criteria were as follows: (a) preprinted articles, (b) studies pertaining to other demyelinating diseases such as MS and myelin oligodendrocyte glycoprotein antibody disorders (MOGAD), (c) reviews, animal studies, hypotheses, in-vitro studies, (d) SARS or MERS related articles, and (e) inability to extract data on NMOSD in studies reporting a mixed sample of NMOSD with other inflammatory demyelinating disorders of CNS.

2.3. Study selection and data extraction

Two researchers (NE and MB) independently screened the articles. If there was a disagreement between the reviewers, it was addressed by a senior researcher (AAS). Two authors independently extracted the data (SB, AM). Extracted data included author, date of first publication, study type, location of study, study sample, number of patients with suspected/confirmed COVID-19, age, sex, comorbidities (heart diseases, hypertension, diabetes mellitus, pulmonary diseases, malignancies, obesity, smoking, and autoimmune diseases), aquaporin-4 antibody (AQP4-Ab) status, COVID-19 symptoms (fever, cough, dyspnea/shortness of breath, fatigue/asthenia, cough, headache, nausea/vomiting, diarrhea, anosmia, and ageusia), expanded disability status scale (EDSS), maintenance therapies (rituximab, azathioprine, mycophenolate mofetil, corticosteroid, ofatumumab, tocilizumab, inebilizumab, eculizumab, methotrexate, no therapy), and the number of patients who required hospitalization, ICU admission, and died of COVID-19. Corresponding authors were contacted to retrieve demographical and clinical data of patients.

2.4. Quality assessment

Two authors (MB and OM) independently assessed the quality of the included published articles (cross-sectional and cohort studies) using the Newcastle-Ottawa scale (NOS) quality tests (Stang, 2010). We rated the quality of included studies by giving stars to the three parameters selection, comparability, and outcome according to the NOS guidelines. Each star meant one score. To calculate overall quality, all scores were summed. Studies with score less than 5 were considered low quality, score 5–7 were considered moderate quality, and studies with score more than 7 were considered high quality. Any disagreement between researchers was resolved by a senior researcher (AAS).

2.5. Statistical analysis

Descriptive analysis including mean (standard deviation [SD]) for continuous variables and frequency (%) for categorical variables was used to report demographic and clinical characteristics of patients. The data was weighted when we combined aggregated data with those reported individually. Meta-analysis was conducted with Stata software (version 14, Stata Corporation, College station, Texas, USA). Statistical heterogeneity across the included studies was assessed using chi-square-based Q statistics and I-square (I2) index. Fixed effect model was used to estimate the rates of hospitalization, ICU admission, and death. Because of high heterogeneity (I2≥50%), the random effect model using DerSimonian-Larid method was conducted to estimate the prevalence of COVID-19 among NMOSD patients. To estimate the prevalence of COVID-19 among NMOSD patients, we pooled the proportions of NMOSD patients with the infection among people with NMOSD. To estimate the rates of hospitalization, ICU admission, and death, we pooled the proportion of NMOSD patients in need of hospitalization, ICU, and death among NMOSD patients with the infection. We used Forest plots to visually evaluate the prevalence of COVID-19, the rate of hospitalization, and the rate of death in each study and the pooled estimate of each prevalence with their 95% confidence intervals (95% CI). Funnel plot, Begg's test, and Egger's test were used to investigate the publication bias. Begg's and Egger's tests P <  0.05 indicate potential publication bias. However, some possible publication bias may remain undetected, because these tests have low statistical power when the number of included studies is small.

3. Results

3.1. Study characteristics

PRISMA flow chart is shown in Fig. 1 . The literature search found 540 studies. After eliminating duplicates, we screened 361 records. Of these, 67 studies were assessed with full-text review. Finally, 23 studies met the inclusion criteria including 19 published articles (Alonso et al., 2021; Cabal-Herrera and Mateen, 2021; Ciampi et al., 2020; Creed et al., 2020; Fan et al., 2020; Friedli et al., 2021; Louapre et al., 2020b; Maillart et al., 2020; Mantero et al., 2020; Mirmosayyeb et al., 2020; Montero-Escribano et al., 2020; Parrotta et al., 2020; Sahraian et al., 2020; Stastna et al., 2021; Tomczak and Han, 2020; Viswanathan, 2020; Woo et al., 2021; Yin et al., 2021; Zeidan et al., 2021) and 4 conference abstracts (Boaventura et al., 2020; Graham et al., 2020; Kurihara and Bharat, 2021; Mehdipour and Ashtari, 2020) reporting 112 NMOSD patients with COVID-19. The search included nine studies on risk of COVID-19 and nine studies on outcome, with a total of 6243 NMOSD patients. Characteristics of each included study is summarized in Table 1 . Regarding type of studies, 11 were case report/series (Cabal-Herrera and Mateen, 2021; Ciampi et al., 2020; Creed et al., 2020; Friedli et al., 2021; Graham et al., 2020; Kurihara and Bharat, 2021; Maillart et al., 2020; Mantero et al., 2020; Montero-Escribano et al., 2020; Parrotta et al., 2020; Woo et al., 2021), 6 were cross sectional studies (Mehdipour and Ashtari, 2020; Mirmosayyeb et al., 2020; Sahraian et al., 2020; Tomczak and Han, 2020; Yin et al., 2021; Zeidan et al., 2021), and six were cohort studies (Alonso et al., 2021; Boaventura et al., 2020; Fan et al., 2020; Louapre et al., 2020b; Stastna et al., 2021; Viswanathan, 2020). Six studies were from North America (Cabal-Herrera and Mateen, 2021; Creed et al., 2020; Graham et al., 2020; Kurihara and Bharat, 2021; Parrotta et al., 2020; Tomczak and Han, 2020), 3 from France (Louapre et al., 2020b; Maillart et al., 2020; Zeidan et al., 2021) and Iran (Mehdipour and Ashtari, 2020; Mirmosayyeb et al., 2020; Sahraian et al., 2020), two from China (Fan et al., 2020; Yin et al., 2021) and one each from Spain (Montero-Escribano et al., 2020), Brazil (Boaventura et al., 2020), Germany (Woo et al., 2021), Italy (Mantero et al., 2020), Switzerland (Friedli et al., 2021), Chile (Ciampi et al., 2020), Czechia (Stastna et al., 2021), Latin America (Alonso et al., 2021), and Malaysia (Viswanathan, 2020). Quality assessment of each published article is documented in Supplementary Tables 2 –3 .

Fig. 1.

Fig. 1

Open in a new tab

Study selection.

Table 1.

Characteristics of included studies.

Refs. Location Type of publishing Date of first publication Type of study Sample size Suspected/confirmed COVID-19 Quality score
(Montero-Escribano et al., 2020) Spain Published article 05./07/2020 Case report/series 5 1 –
(Creed et al., 2020) USA Published article 05/19/2020 Case report/series 1 1 –
(Mantero et al., 2020) Italy Published article 07/07/2020 Case report/series 1 1 –
(Graham et al., 2020) USA Conference abstract 12/07/2020 Case report/series 2 2 –
(Maillart et al., 2020) France Published article 09/03/2020 Case report/series 1 1 –
(Woo et al., 2021) Germany Published article 07/11/2020 Case report/series 1 1 –
(Cabal-Herrera and Mateen, 2021) USA Published article 04/27/2021 Case report/series 1 1 –
(Ciampi et al., 2020) Chile Published article 07/12/2020 Case report/series 5 4 –
(Kurihara and Bharat, 2021) USA Conference abstract 05/20/2021 Case report/series 1 1 –
(Friedli et al., 2021) Switzerland Published article 05/18/2020 Case report/series 1 1 –
(Parrotta et al., 2020) USA Published article 07/09/2020 Case report/series 1 1 –
(Mirmosayyeb et al., 2020) Iran Published article 09/14/2020 Cross sectional 157 6 6/10
(Mehdipour and Ashtari, 2020) Iran Conference abstract 12/07/2020 Cross sectional 140 6 –
(Sahraian et al., 2020) Iran Published article 06/01/2020 Cross sectional 130 5 7/10
(Yin et al., 2021) China Published article 03/22/2021 Cross sectional 535 0 8/10
(Tomczak and Han, 2020) USA Published article 06/30/2020 Cross sectional 14 0 4/10
(Zeidan et al., 2021) France Published article 09/12/2020 Cross sectional 75 5 7/10
(Boaventura et al., 2020) Brazil Conference abstract 12/07/2020 Cohort 2061 34 –
(Alonso et al., 2021) USA Published article 05/07/2021 Cohort 16 16 3/9
(Louapre et al., 2020b) France Published article 10/26/2020 Cohort 10 10 3/9
(Fan et al., 2020) China Published article 06/04/2020 Cohort 3060 2 6/9
(Stastna et al., 2021) Czechia Published article 06/23/2021 Cohort 13 13 5/9
(Viswanathan, 2020) Malaysia Published article 07/03/2020 Cohort 71 0 7/9
Open in a new tab

Table 2.

Demographic and clinical features of NMOSD patients with COVID-19.

Characteristics N (%) or Mean (SD) Number of patients with determined status
Demographic and clinical
Age, mean (SD) 40.80 (10.63) 106
Sex, female/male, n (ratio) 77/23 (3.35: 1) 100
Disease duration, mean (SD) 8.09 (4.63) 99
EDSS, mean (SD) 3.39 (1.24) 70
AQP4-Ab, positive, n (%) 39 (54.2) 72
COVID-19 symptoms
Fever 42 (54.5) 77
Cough 31 (40.3)
Fatigue/asthenia 33 (42.9)
Shortness of breath/Dyspnea 24 (31.2)
Headache 32 (41.6)
Nausea/vomiting 4 (5.2)
Diarrhea 10 (13.0)
Anosmia 23 (31.9) 72
Ageusia 9 (12.5)
Neurological worsening 4 (15.4) 26
Comorbidity
At least one comorbidity 38 (48.7) 78
Hypertension 11 (14.1)
Hart diseases 2 (2.6)
Diabetes mellitus 7 (8.9)
Pulmonary disease 5 (6.4)
Malignancy 3 (3.8)
Autoimmune diseases 11 (14.1%)
Smoking 5 (5.3) 94
Obesity 20 (21.3)
Treatment
Rituximab 58 (54.7) 106
Corticosteroid 17 (16.0)
Mycophenolate mofetil 9 (8.5)
Azathioprine 25 (23.6)
Ofatumumab 2 (1.9)
Tocilizumab 1 (0.9)
Inebilizumab 1 (0.9)
Eculizumab 1 (0.9)
Methotrexate 1 (0.9)
No treatment 5 (4.7)
Open in a new tab

N: number; SD: standard division; EDSS: expanded disability status scale; AQP4-Ab: aquaporin-4 antibody.

Table 3.

Characteristics of NMOSD patients with COVID-19 based on hospitalization status.

Characteristics Hospitalized Non-hospitalized
Age, mean (SD) n = 37
46.54 (14.87)		 n = 55
37.36 (8.57)
Sex, female, n (%) n = 35
25 (71.4)		 n = 55
46 (83.6)
Disease duration, mean (SD) n = 34
9.35 (6.70)		 n = 55
7.57 (3.12)
EDSS, mean (SD) n = 21
4.50 (1.97)		 n = 47
2.94 (0.89)
AQP4-Ab, positive, n (%) n = 10
9 (90)		 n = 13
6 (46.1)
Comorbidity n = 24 n = 48
At least one comorbidity, n (%) 13 (54.2) 23 (47.9)
Hypertension, n (%) 6 (25.0) 5 (10.4)
Heart diseases, n (%) 2 (8.3) 1 (2.1)
Diabetes mellitus, n (%) 4 (16.7) 3 (6.2)
Pulmonary disease, n (%) 2 (8.3) 3 (6.2)
Malignancy, n (%) 1 (4.2) 2 (4.2)
Autoimmune diseases, n (%) 4 (16.7) 5 (10.4)
Obesity, n (%) n = 25
9 (37.5)		 n = 55
11 (20.0)
Smoking, n (%) n = 25
1 (4.0)		 n = 55
3 (5.4)
Treatment n = 37 n = 55
Rituximab, n (%) 26 (70.3) 22 (40.0)
Corticosteroid, n (%) 4 (10.8) 11(20.0)
Mycophenolate mofetil, n (%) 4 (10.8) 5 (9.1)
Azathioprine, n (%) 6 (16.2) 19 (34.5)
Ofatumumab, n (%) 0 1 (1.8)
Inebilizumab, n (%) 0 1 (1.8)
Eculizumab, n (%) 0 1 (1.8)
Methotrexate, n (%) 0 1 (1.8)
No treatment, n (%) 1 (2.7) 3 (5.4)
Open in a new tab

n: number; SD: standard division; EDSS: expanded disability status scale; AQP4-Ab: aquaporin-4 antibody.

3.2. COVID-19 prevalence among patients with NMOSD

Night studies (7 published articles and 2 conference abstracts) reported the prevalence of COVID-19 (Boaventura et al., 2020; Fan et al., 2020; Mehdipour and Ashtari, 2020; Mirmosayyeb et al., 2020; Sahraian et al., 2020; Tomczak and Han, 2020; Viswanathan, 2020; Yin et al., 2021; Zeidan et al., 2021). The lowest prevalence of COVID-19 was 0% in China (based on 535 samples), 0% in USA (based on 14 samples), and 0% (based on 71 samples) in Malaysia and the highest prevalence was 6.7% in France (based on 75 samples). The pooled estimate of the prevalence of COVID-19 was 1.2% (95% CI: 0.001%−0.030%; I2 =92 %, p< 0.001) in a total sample of 6243 NMOSD patients (Fig. 2 ). The Begg's (p = 0.602) and Egger's (p = 0.116) tests showed no evidence of publication bias (Fig. 1 in the Supplementary appendix).

Fig. 2.

Fig. 2

Open in a new tab

COVID-19 prevalence among patients with NMOSD.

3.2.1. Hospitalization of NMOSD patients with COVID-19

Seven studies reported hospital admission data (Alonso et al., 2021; Boaventura et al., 2020; Louapre et al., 2020b; Mirmosayyeb et al., 2020; Sahraian et al., 2020; Stastna et al., 2021; Zeidan et al., 2021). Of 89 NMOSD patients, 31 cases needed hospitalization with a pooled rate of 33.7% (95% CI: 23.3%−44.8%; I2 = 9.1%, p = 0.360) (Fig. 3 ). We did not observe potential publication bias in Begg's (p = 0.879) and Egger's (p = 0.427) tests (Fig. 2 in the Supplementary appendix).

Fig. 3.

Fig. 3

Open in a new tab

Rate of hospitalization among NMOSD patients with COVID-19.

3.2.2. ICU admission of NMOSD patients with COVID-19

Seven studies reported the prevalence of ICU admission ranging from 0 to 43.8% (Alonso et al., 2021; Boaventura et al., 2020; Louapre et al., 2020b; Mehdipour and Ashtari, 2020; Mirmosayyeb et al., 2020; Stastna et al., 2021; Zeidan et al., 2021). The pooled rate of ICU admission was 15.4% (95% CI: 7.6%−24.7%; I2=20.7%, p = 0.272) (Fig. 4 ). We did not observe potential publication bias in Begg's (p = 1.000) and Egger's (p = 0.835) tests (Fig. 3 in the Supplementary appendix).

Fig. 4.

Fig. 4

Open in a new tab

Rate of ICU admission among NMOSD patients with COVID-19.

3.2.3. Mortality of NMOSD patients with COVID-19

Nine studies reported mortality, with a range from 0 to 31.3% (Alonso et al., 2021; Boaventura et al., 2020; Fan et al., 2020; Louapre et al., 2020b; Mehdipour and Ashtari, 2020; Mirmosayyeb et al., 2020; Sahraian et al., 2020; Stastna et al., 2021; Zeidan et al., 2021) . The overall rate of death was estimated as 3.3% (95% CI: 0–9.7%; I2 = 21.3%, p = 0.253) (Fig. 5 ). The Begg's (p = 0.466) and Egger's (p = 0.544) tests showed no evidence of publication bias (Fig. 4 in the Supplementary appendix).

Fig. 5.

Fig. 5

Open in a new tab

Rate of death among NMOSD patients with COVID-19.

3.3. Patients' characteristics and COVID-19 related symptoms

Table 2 presents demographic and clinical data of NMOSD patients with COVID-19 included in this study. The mean age of NMOSD patients with COVID-19 was 40.8 (SD 10.6) years, female/male ratio was 3.35:1, disease duration was 8.1 (SD 4.6) years and mean EDSS score was 3.39 (1.24). The most common COVID-19-related symptom was fever (54.5%), following by fatigue/asthenia (42.9%), headache (41.6%), shortness of breath/dyspnea (31.2%), and anosmia (31.9%). Ageusia was found in 12.5% of patients, diarrhea in 13.0%, and nausea/vomiting in 5.2%. Four of 26 (15.4%) infected patients had neurological worsening (Boaventura et al., 2020; Mantero et al., 2020). One developed pseudo-relapse with worsening of paresthesias in the lower limbs, without other serious complications (Mantero et al., 2020). Two patients needed hospitalization and another one required admission to ICU (Boaventura et al., 2020). All four patients recovered. Thirty-eight patients (out of 78, 48.7%) reported at least one comorbidity. The most common comorbidities were hypertension (14.1%) and autoimmune diseases (14.1%), followed by diabetes mellitus (8.9%), pulmonary diseases (6.4%), and malignancy (3.8%). Data on autoimmune diseases in 8 patients were reported in detail. Myasthenia gravis and psoriasis were reported in two patients and each of the following comorbidities was reported in one patient: autoimmune hepatitis, autoimmune myositis, systemic lupus erythematous, Sjögren's disease, myositis, rheumatoid arthritis, and pernicious anemia. Obesity was reported in 20 (21.3%) patients, 5 patients were smokers (5.3%). Patients' characteristics according to hospitalization status is presented in Table 3.

3.4. NMOSD treatment and the risk of COVID-19

Information on therapies was available for 106 patients. The most commonly used therapies was rituximab (54.7%), followed by azathioprine (23.6%), long-term corticosteroid (16.0%), and mycophenolate mofetil (8.5%). Hospitalization was needed in 27 of 51 (52.9%) patients who received RTX, 6 of 25 (24.0%) patients who received AZA, 4 (44.5%) of 9 patients on MMF, and 3 (20.0%) of 15 patients treated with long-term corticosteroid. Demographic and clinical features of patients separated by therapies are documented in Table 4 . Six out of nine patients who died of COVID-19 were on RTX (Alonso et al., 2021; Stastna et al., 2021), two were on prednisone (Ciampi et al., 2020; Stastna et al., 2021), and one was on combination therapy of AZA and prednisone (Boaventura et al., 2020). The mean age of deceased cases was 58.2 (SD 7.04) years, 7 (77.8%) were female, and mean of disease duration and EDSS score were 13.0 (SD 7.0) years and 4.5 (1.8), respectively. Information on the comorbidity of the deceased was available for four patients in detail. All four deceased cases had comorbidity including hypertension in three patients, and one case each had a cardiovascular condition, diabetes mellitus, dyslipidemia, malignancy, and rheumatoid arthritis. Regarding the other five cases, obesity and diabetes mellitus was each reported by two patients.

Table 4.

Characteristics of patients were treated with rituximab, azathioprine, mycophenolate mofetil, or corticosteroids.

RTX AZA
 MMF
 Corticosteroids
All Hospitalized All Hospitalized All Hospitalized All Hospitalized
Age, mean (SD) n = 41
41.6 (15.1)		 n = 22
46.3 (16.8)		 n = 10
34.8 (10.4)		 n = 5
39.6 (11.7)		 n = 7
39.8 (12.5)		 n = 3
41.3 (14.0)		 n = 9
47.1 (15.6)		 n = 2
46.6 (16.7)
Sex, female, n (%) n = 35
25/35 (71.4)		 n = 22
17 (77.3)		 n = 10
9 (90.0)		 n = 5
4 (80.0)		 n = 7
6 (85.7)		 n = 3
2 (66.7)		 n = 9
5 (55.6)		 n = 2
0
EDSS score, mean (SD) n = 25
3.5 (1.5)		 n = 18
3.9 (1.5)		 n = 10
3.3 (1.9)		 n = 5
4.3 (1.8)		 n = 5
2.1 (1.0)		 n = 1
1.0		 n = 6
3.7 (2.2)		 n = 2
3.7 (2.2)
Disease duration, mean (SD) n = 38
8.1 (5.4)		 n = 20
8.9 (6.4)		 n = 10
7.5 (5.8)		 n = 5
5.8 (3.6)		 n = 5
5.8 (5.3)		 n = 1
2.0		 n = 7
5.9 (7.1)		 n = 2
5.9 (7.1)
Comorbidity, n (%) n = 27
12 (44.4)		 n = 15
8 (53.3)		 n = 10
2 (20.0)		 n = 5
2 (40.0)		 n = 7
6 (85.7)		 n = 3
2 (66.7)		 n = 7
6/7 (85.7)		 n = 2
2 (100)
Open in a new tab

n: number; SD: standard division; EDSS: expanded disability status scale; RTX: rituximab; AZA: azathioprine; MMF: mycophenolate mofetil.

4. Discussion

In this systematic review and meta-analysis, we comprehensively assessed available studies on NMOSD patients infected with COVID-19. The pooled prevalence of COVID-19 was 1.2% (95% CI: 0.001%−0.030%), based on a total of 6243 NMOSD patients with female predominance. Of those 33.7% needed hospitalization, 15.4% ICU admission and the mortality was 3.3%. More than half of rituximab-treated patients needed hospital admission and 2/3 of those died. Approximately half of the NMOSD patients with COVID-19 had at least one comorbidity. The data suggest that comorbidity and treatment with rituximab are risk factors for COVID-19 infection in NMOSD patients.

The most common COVID-19-related symptom was fever (54.5%), followed by fatigue/asthenia (42.9%), headache (41.6%), and cough (40.3%). Anosmia and dyspnea were found in about 30%. These data are in accordance with the findings in the general population (Boaventura et al., 2020; Salter et al., 2021) and in MS patients (Louapre et al., 2020a; Salter et al., 2021). Neurological worsening was reported by 15.4% of infected NMOSD patients (Boaventura et al., 2020; Mantero et al., 2020). Recent evidence suggests that COVID-19 may trigger exacerbation of MS (Barzegar et al., 2021d; Garjani et al., 2021). However, due to short follow-up and absence of control group, it could not be possible to determine the probable association between COVID-19 and risk of relapse in NMOSD patients.

This meta-analysis provided an estimation on the prevalence of COVID-19 of NMOSD patients. Three studies from China, USA, and Malaysia found no NMOSD patients with COVID-19 (Tomczak and Han, 2020; Viswanathan, 2020; Yin et al., 2021). The highest risk of COVID-19 was found in studies from France (6.7%). This discrepancy could be attributed to the differences in study settings, health policies, level of adherence to preventive protocols, and the phase of the pandemic in which the study had been conducted. Our estimated prevalence is not inconsistent with the prevalence of COVID-19 reported by a systematic review and meta-analysis in MS patients 1–13% (Moghadasi et al., 2021) and in other autoimmune diseases 1.1% (Akiyama et al., 2021), respectively. A higher prevalence of COVID-19 among patients with autoimmune disease was observed (Akiyama et al., 2021). As the pandemic continue to spread, the prevalence of COVID-19 among NMOSD population could be changed. Therefore, it is possible that the prevalence of the infection in the countries with low prevalence would increase.

The rate of hospitalization that was estimated in this study (33.7%) is higher than 20.7% reported in a systematic review on MS patients (Barzegar et al., 2021b). There is a large variation in the rate of hospitalization in primary studies, even between studies from a same country. The hospitalization rates in two surveys from Iran reported 33.3% (Mirmosayyeb et al., 2020) and 60% (Sahraian et al., 2020), in two studies from France were 40% (Louapre et al., 2020b) and 20.0% (Zeidan et al., 2021), in studies from Latin America were 23.5% (Boaventura et al., 2020) and 56% (Alonso et al., 2021), and in a study from Czechia was 30.8% (Stastna et al., 2021). The reasons for this variation are similar with those mentioned for variation in the prevalence of COVID-19.

The risk of hospitalization due to COVID-19 increases with age, with hospitalization rate being 7.4% in adults between 18 and 64 years of age, but 13.8% at age 65 years and above (Garg et al., 2020). The rate of ICU admission reported from 0 to 43.8%, with a pooled rate of 15.4%. Risk of ICU admission among adults 20–54 years of age was reported from 2 to 10.4%, increasing to 31% in adults aged 75–84 years (Statista, 2021). The mortality in our study (3.3%) is in accordance with a mortality rate of 3.0 reported in MS patients with COVID-19 (Barzegar et al., 2021b). A broad range has been reported for the risk of death due to COVID-19 in NMOSD patients. A multi-centric registry study from LATAM with 16 NMOSD patients reported the risk of death as 31.2% (Alonso et al., 2021). The COVID-19 mortality rate among NMOSD patients in the Brazilian registry was 2.9%, (Boaventura et al., 2020). On the contrary, the French Covisep registry and other observational studies found no cases of death due to the infection (Louapre et al., 2020b). In adults aged 25–55 years, the infection fatality rate (IFR) was in a range of 0.0% to 0.4% and raised to 1.4% in adults aged ≥ 65 years (Levin et al., 2020).

It is expected that female predominance and age of infected patients and those needed hospitalization (40 and 45 years, respectively) put them at a decreased risk of poor COVID-19 outcome (Galbadage et al., 2020; Levin et al., 2020). However, when we compare the COVID-19 outcomes between NMOSD patients and general population, it seems that risk of severe COVID-19 in NMOSD patients may be higher than that of general population at the same age. The possible increased risk could be related to the high prevalence of comorbidities, the dysregulated immune system and the maintenance therapies used.

Our findings are in the line with studies on MS population, which showed that older age, male sex, greater EDSS, and having comorbidities are associated with increased risk of COVID-19 severity and mortality (Alonso et al., 2021; Barzegar et al., 2021a; Louapre et al., 2020b; Salter et al., 2021). In the present study comorbidity was common. The most common comorbidity among all patients was obesity, followed by hypertension, autoimmune diseases, and diabetes mellitus. These conditions are highly prevalent in NMOSD patients (Ajmera et al., 2018; Barzegar et al., 2021c; Shahmohammadi et al., 2019), and also independently associated with worse COVID-19 outcomes (Gupta et al., 2020; Sanyaolu et al., 2020). Aging is known as an important risk factor for being hospitalized, ICU admission, and death from COVID-19 (Grasselli et al., 2020; Gupta et al., 2020). There is also an increasing trend in hospitalization and mortality rates with higher age groups in infected patients with comorbidity (Thakur et al., 2021; Tisminetzky et al., 2020).

Race and ethnicity have been suggested as contributing factors to COVID-19 outcomes (Mathur et al., 2021; Sze et al., 2020). African Americans are at an increased risk of developing severe NMOSD relapse and mortality (Mealy et al., 2018; Zhao-Fleming et al., 2021). However, no study has attempted to investigate the effect of race-ethnicity on infection outcome among NMOSD population. Therefore, we could not provide data to elucidate the impact of race-ethnicity on COVID-19 outcome among NMOSD patients. Current data suggest as an explanation that race-ethnicity minority populations experience social and financial inequity and have inadequate access to healthcare services (Kabarriti et al., 2020; Ogedegbe et al., 2020)

One of the greatest challenges physicians are facing during the pandemic is managing immunosuppressive therapies in patients with autoimmune diseases. NMOSD in most cases follows a relapsing course and may lead to neurological disability and morbidity as a consequence of cumulative sequelae of attacks, justifying early initiation of immunosuppressive treatment (Kim et al., 2021; Zhao-Fleming et al., 2021). Azathioprine and mycophenolate mofetil are two common immunosuppressive agents used for the treatment of NMOSD patients. About 22% and 44.5% of NMOSD patients who were on azathioprine and mycophenolate mofetil needed hospitalization. The effect of MMF and AZA on COVID-19 outcome is currently a subject of debate. Although a study in myasthenia gravis patients found no association between MMF and severity of COVID-19 (Michala et al., 2021), another in liver transplant patients found that MMF increased the risk of severe infection, especially at doses higher than 1 g/day (Colmenero et al., 2021). Since a limited number of patients are being treated with AZA and MMF, a definitive conclusion on the effect of these drugs on COVID-19 outcomes in NMOSD patients awaits further research.

Long-term oral corticosteroid as monotherapy or combination therapy is occasionally used to manage NMOSD in the chronic phase. Two reported deceased cases were on prednisone and one was treated with a combination of prednisone and AZA. Previous studies on MS patients have shown that the use of corticosteroids prior to COVID-19 can increase the risk of severe infection (Sormani et al., 2021b). However, it could be associated with better outcome when used in critically ill patients (Sterne et al., 2020). Few published data exist on the outcome of COVID-19 in NMOSD patients treated with monoclonal antibodies targeting interleukin (IL)−6 receptor (such as tocilizumab and satralizumab) and the complement system (eculizumab). Primary observational studies reported that tocilizumab can control cytokine storm in the COVID-19 patients and therefore can be used as a therapy in infected patients, especially in those with severe illness (Luo et al., 2020; Xu et al., 2020). Further clinical trial studies verified the safety of tocilizumab in COVID-19 patients; however, the effectiveness of this agent still remains unclear (Gordon et al., 2021; Rosas et al., 2021; Veiga et al., 2021).

We found that more than half of rituximab-treated patients needed hospital admission. Six out of 9 deceased cases were also treated with rituximab. These findings, while preliminary, suggest that NMOSD patients treated with rituximab may be more vulnerable to develop severe forms of COVID-19 infection. This is in accordance with studies on MS and other autoimmune diseases that have shown an increased risk of severe COVID-19 in patients using rituximab (Avouac et al., 2021; Michala et al., 2021; Salter et al., 2021; Sormani et al., 2021 a). This possible relation could be related to general practice that patients treated with rituximab are usually older and have more disability, which increase the risk of serious infection. However, the mean of age and EDSS score of patients treating with rituximab was not substantially different with other NMOSD patients. The role of rituximab could be due to the B cell-depleting effect of rituximab that attenuates antibody responses, resulting in compromised antiviral immunity. It also diminishes T-cell counts, mainly CD4+ and to a lesser degree CD8+ (Liossis and Sfikakis, 2008; Mélet et al., 2013), which have crucial role in the response to SAR-COV2 (Cao, 2020).

Of particular concern is the effect of disease-modifying therapies (DMTs) and immunosuppressive therapies on vaccine effectiveness. Studies show poor antibody production following the COVID-19 infection and administration of mRNA vaccine in MS and NMOSD patients treated with anti-CD20 agents (Apostolidis et al., 2021; Bigaut et al., 2021; Brill et al., 2021; Louapre et al., 2021). On the othe hand these patients generated robust SARS-CoV-2 specific T-cell responses following the vaccination (Apostolidis et al., 2021; Brill et al., 2021). Treatment with DMTs has not been linked to an impaired response to SARS-CoV-2 vaccine (Jena et al., 2021). Notwithstanding the aforementioned disadvantages, the efficacy of rituximab is higher than azathioprine and MMF (Huang et al., 2019; Nikoo et al., 2017). Moreover, drug discontinuation could predispose NMOSD patients to potentially-life-threatening attacks (Kim et al., 2021; Zhao-Fleming et al., 2021). Therefore, the administration of rituximab should be weighed against the risk of severe infection on a case-by-case basis.

Our study has some limitations. First, none of the included patients were asymptomatic. Therefore, we could not determine the rate of asymptomatic COVID-19 infection among NMOSD patients. This could also confound our interpretation of COVID-19 severity among NMOSD patients. Second, we included case report/series which are not representative of the NMOSD population. However, we did not include these studies in quantitative synthesis. Third, some of included studies in meta-analysis on COVID-19 outcome reported small number of infected patients which can affect our estimation. Fourth, a small group of patients were treated with therapies rather than rituximab and azathioprine. As such, we were unable to draw any conclusion on the impact of the aforementioned agents on COVID-19 outcomes. The fifth limitation of our study is the inclusion of conference abstracts with insufficient data, whose validity was not assessed carefully. However, including conference abstracts reduced publication bias and made our study more comprehensive. Sixth, the articles from languages other than English were not included. It should be noticed that none of primary studies has enrolled an age-sex-comorbidity matched control group from general population. Therefore, it is impossible to precisely illustrate the effect of NMOSD on COVID-19 susceptibility and outcomes. Caution should be applied in comparison of COVID-19 outcomes (risk of hospitalization, ICU admission, and mortality) between NMOSD patients and the general population.

In conclusion, our systematic review and meta-analysis suggests that NMOSD patients, particularly those who were treated with rituximab and had comorbidity need more attention. Further studies with an age-sex-comorbidity-matched control group from the general population are needed to determine whether NMOSD patients are at increased risk of contracting COVID-19 and developing severe infection.

Funding

None

Ethical considerations

Not applicable

Consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and material

All data will be available for secondary analysis in necessary cases from the corresponding author through an email address.

CRediT authorship contribution statement

Mahdi Barzegar: Conceptualization, Formal analysis, Investigation, Validation, Writing – original draft, Writing – review & editing. Omid Mirmosayyeb: Data curation, Methodology, Visualization, Writing – review & editing. Narges Ebrahimi: Investigation, Methodology, Writing – review & editing. Sara Bagherieh: Investigation, Methodology, Writing – original draft, Writing – review & editing. Alireza Afshari-Safavi: Data curation, Formal analysis, Validation, Visualization, Writing – review & editing. Ali Mahdi Hosseinabadi: Investigation, Methodology, Writing – review & editing. Vahid Shaygannejad: Conceptualization, Project administration, Writing – review & editing. Nasrin Asgari: Conceptualization, Project administration, Writing – review & editing.

Declaration of Competing Interest

The Authors declare that there is no conflict of interest relevant to the study.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.msard.2021.103359.

Appendix. Supplementary materials

mmc1.docx (66.6KB, docx)

References

  1. Ajmera M.R., Boscoe A., Mauskopf J., Candrilli S.D., Levy M. Evaluation of comorbidities and health care resource use among patients with highly active neuromyelitis optica. J. Neurol. Sci. 2018;384:96–103. doi: 10.1016/j.jns.2017.11.022. [DOI] [PubMed] [Google Scholar]
  2. Akiyama S., Hamdeh S., Micic D., Sakuraba A. Prevalence and clinical outcomes of COVID-19 in patients with autoimmune diseases: a systematic review and meta-analysis. Ann. Rheum. Dis. 2021;80:384–391. doi: 10.1136/annrheumdis-2020-218946. 2020/10/13. [DOI] [PubMed] [Google Scholar]
  3. Alonso R., Silva B., Garcea O., Diaz P.E.C., Dos Passos G.R., Navarro D.A.R., Valle L.A.G., Salinas L.C.R., Negrotto L., Luetic G. COVID-19 in multiple sclerosis and neuromyelitis optica spectrum disorder patients in Latin America: COVID-19 in MS and NMOSD patients in LATAM. Mult. Scler. Relat. Disord. 2021;51 doi: 10.1016/j.msard.2021.102886. 2021/3/7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Apostolidis S.A., Kakara M., Painter M.M., Goel R.R., Mathew D., Lenzi K., Rezk A., Patterson K.R., Espinoza D.A., Kadri J.C. Cellular and humoral immune responses following SARS-CoV-2 mRNA vaccination in patients with multiple sclerosis on anti-CD20 therapy. Nat. Med. 2021:1–12. doi: 10.1038/s41591-021-01507-2. 2021/9/14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Avouac J., Drumez E., Hachulla E., Seror R., Georgin-Lavialle S., El Mahou S., Pertuiset E., Pham T., Marotte H., Servettaz A. COVID-19 outcomes in patients with inflammatory rheumatic and musculoskeletal diseases treated with rituximab: a cohort study. Lancet Rheumatol. 2021;3:e419–e426. doi: 10.1016/s2665-9913(21)00059-x. 2021/3/25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Barzegar, M., Bagherieh, S., Houshi, S., Hashemi, M.S., Pishgahi, G., Afshari-Safavi, A., Mirmosayyeb, O., Shaygannejad, V., Zabeti, A., 2021. Factors associated with COVID-19 susceptibility and severity in patients with multiple sclerosis: A systematic review. medRxiv. 21258765. 10.1101/2021.06.11.21258765. 2021/6/15. [DOI] [PMC free article] [PubMed]
  7. Barzegar M., Mirmosayyeb O., Gajarzadeh M., Afshari-Safavi A., Nehzat N., Vaheb S., Shaygannejad V., Maghzi A.H. COVID-19 Among patients with multiple sclerosis: a systematic review. Neurol. Neuroimmunol. Neuroinflamm. 2021;8 doi: 10.1212/NXI.0000000000001001. 2021/05/20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Barzegar M., Mirmosayyeb O., Nehzat N., Vaheb S., Shaygannejad V., Asgari N. Frequency of comorbidities in neuromyelitis optica spectrum disorder. Mult. Scler. Relat. Disord. 2021;48 doi: 10.1016/j.msard.2020.102685. 2021/02/01. [DOI] [PubMed] [Google Scholar]
  9. Barzegar M., Vaheb S., Mirmosayyeb O., Afshari-Safavi A., Nehzat N., Shaygannejad V. Can coronavirus disease 2019 (COVID-19) trigger exacerbation of multiple sclerosis? A retrospective study. Mult. Scler. Relat. Disord. 2021;52 doi: 10.1016/j.msard.2021.102947. 2021/4/11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bigaut K., Kremer L., Fabacher T., Lanotte L., Fleury M.C., Collongues N., de Seze J. Impact of disease-modifying treatments of multiple sclerosis on anti–SARS-CoV-2 antibodies: an observational study. Neurol. Neuroimmunol. Neuroinflamm. 2021;8 doi: 10.1212/NXI.0000000000001055. 2021/7/28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Boaventura M., Apostolos-Pereira S., Ferreira L., Sousa N., Martins G., D'Almeida J., Pitombeira M., Mendes L., Fukuda T., Rocha L. Clinical features of COVID-19 in patients with neuromyelitis optica spectrum disorders. Mult. Scler. J. 2020:99–100. doi: 10.1212/NXI.0000000000001060. 2021/8/26. [DOI] [Google Scholar]
  12. Brill L., Rechtman A., Zveik O., Haham N., Oiknine-Djian E., Wolf D.G., Levin N., Raposo C., Vaknin-Dembinsky A. Humoral and T-cell response to SARS-CoV-2 vaccination in patients with multiple sclerosis treated with ocrelizumab. JAMA Neurol. 2021 doi: 10.1001/jamaneurol.2021.3599. 2021/9/23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Cabal-Herrera A.M., Mateen F.J. COVID-19 in a patient treated with eculizumab for aquaporin-4 neuromyelitis optica. J. Neurol. 2021:1–4. doi: 10.1007/s00415-021-10578-7. 2021/4/27. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Cao X. COVID-19: immunopathology and its implications for therapy. Nat. Rev. Immunol. 2020;20:269–270. doi: 10.1002/path.5642. 2020/4/9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Ciampi E., Uribe-San-Martín R., Soler B., Fernández R., García P., Navarrete-Asenjo C., Tirapegui J.M., Torres R., Polanco J., Suárez F. COVID-19 in MS and NMOSD: a multicentric online national survey in Chile. Mult. Scler. Relat. Disord. 2020;45 doi: 10.1016/j.msard.2020. 102392. 2020/7/12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Colmenero J., Rodríguez-Perálvarez M., Salcedo M., Arias-Milla A., Muñoz-Serrano A., Graus J., Nuño J., Gastaca M., Bustamante-Schneider J., Cachero A. Epidemiological pattern, incidence, and outcomes of COVID-19 in liver transplant patients. J. Hepatol.. 2021;74:148–155. doi: 10.1016/j.jhep.2020.07.040. 2020/8/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Creed M.A., Ballesteros E., Greenfield L.J., Imitola J. Mild COVID-19 infection despite chronic B cell depletion in a patient with aquaporin-4-positive neuromyelitis optica spectrum disorder. Mult. Scler. Relat. Disord. 2020;44 doi: 10.1016/j.msard.2020.102199. 10.1016%2Fj.msard.2020.1021992020/5/19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Fan M., Qiu W., Bu B., Xu Y., Yang H., Huang D., Lau A.Y., Guo J., Zhang M.N., Zhang X. Risk of COVID-19 infection in MS and neuromyelitis optica spectrum disorders. Neurol.Neuroimmunol. Neuroinflamm. 2020;7 doi: 10.1212/NXI.0000000000000787. 2020/6/4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Friedli C., Diem L., Hammer H., Kamber N., Suter-Riniker F., Leib S., Chan A., Hirzel C., Hoepner R., Salmen A. Negative SARS-CoV2-antibodies after positive COVID-19-PCR nasopharyngeal swab in patients treated with anti-CD20 therapies. Ther. Adv. Neurol. Disord. 2021;14 doi: 10.1177/17562864211016641. 175628642110166412021/5/18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Galbadage T., Peterson B.M., Awada J., Buck A.S., Ramirez D.A., Wilson J., Gunasekera R.S. Systematic review and meta-analysis of sex-specific COVID-19 clinical outcomes. Front. Med. 2020;7:348. doi: 10.3389/fmed.2020.00348. 2020/6/23, doi:10.338/fmed.2020.00348. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Garg S., Kim L., Whitaker M., O'Halloran A., Cummings C., Holstein R., Prill M., Chai S.J., Kirley P.D., Alden N.B. Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed coronavirus disease 2019—COVID-NET, 14 States, March 1–30, 2020. Morb. Mortal. Wkly. Rep. 2020;69:458. doi: 10.15585/mmwr.mm6915e3. 10.15585%2Fmmwr.mm6932e32020/4/17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Garjani A., Middleton R.M., Hunter R., Tuite-Dalton K.A., Coles A., Dobson R., Duddy M., Hughes S., Pearson O.R., Rog D. COVID-19 is associated with new symptoms of multiple sclerosis that are prevented by disease modifying therapies. Mult. Scler. Relat. Disord. 2021;52 doi: 10.1016/j.msard.2021.102939. 2021/5/5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Gordon A.C., Mouncey P.R., Al-Beidh F., Rowan K.M., Nichol A.D., Arabi Y.M., Annane D., Beane A., Berry L.R., Bhimani Z. Interleukin-6 receptor antagonists in critically ill patients with Covid-19. N. Engl. J. Med. 2021 doi: 10.1056/NEJMoa2100433. 2021/4/22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Graham E., Datar J., Bevan C., Grebenciucova E., Koralnik I., Cohen B., Balabanov R. Use of IVIG in three immunosuppressed patients hospitalized with COVID-19. Mult. Scler. J. 2020 doi: 10.1159/000511376. 62-622021/1/1. [DOI] [Google Scholar]
  25. Grasselli G., Greco M., Zanella A., Albano G., Antonelli M., Bellani G., Bonanomi E., Cabrini L., Carlesso E., Castelli G. Risk factors associated with mortality among patients with COVID-19 in intensive care units in Lombardy, Italy. JAMA Intern. Med. 2020;180:1345–1355. doi: 10.1001/jamainternmed.2020.3539. 2020/10/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Gupta S., Hayek S.S., Wang W., Chan L., Mathews K.S., Melamed M.L., Brenner S.K., Leonberg-Yoo A., Schenck E.J., Radbel J. Factors associated with death in critically ill patients with coronavirus disease 2019 in the US. JAMA Intern. Med. 2020;180:1436–1446. doi: 10.1001/jamainternmed.2020.3596. 2020/7/15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Huang W., Wang L., Zhang B., Zhou L., Zhang T., Quan C. Effectiveness and tolerability of immunosuppressants and monoclonal antibodies in preventive treatment of neuromyelitis optica spectrum disorders: a systematic review and network meta-analysis. Mult. Scler. Relat. Disord. 2019;35:246–252. doi: 10.1016/j.msard.2019.08.009. 2019/8/9. [DOI] [PubMed] [Google Scholar]
  28. Jena A., Mishra S., Deepak P., Kumar-M P., Sharma A., Patel Y.I., Kennedy N.A., Kim A.H., Sharma V., Sebastian S. Response to SARS-CoV-2 vaccination in immune mediated inflammatory diseases: systematic review and meta-analysis. Autoimmun. Rev. 2021 doi: 10.1016/j.autrev.2021.102927. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Kabarriti R., Brodin N.P., Maron M.I., Guha C., Kalnicki S., Garg M.K., Racine A.D. Association of race and ethnicity with comorbidities and survival among patients with COVID-19 at an urban medical center in New York. JAMA Netw. Open. 2020;3 doi: 10.1001/jamanetworkopen.2020.19795. 2020/9/25, e2019795–e2019795, doi:10.1001/jamanetworkopen.2020.19795. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Kim S.H., Jang H., Park N.Y., Kim Y., Kim S.Y., Lee M.Y., Hyun J.W., Kim H.J. Discontinuation of immunosuppressive therapy in patients with neuromyelitis optica spectrum disorder with aquaporin-4 antibodies. Neurol. Neuroimmunol. Neuroinflamm. 2021;8 doi: 10.1212/NXI.0000000000000947. 2021/2/23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kurihara C., Bharat A. First successful lung transplantation for pulmonary fibrosis due to severe COVID-19 infection in the US. J. Heart Lung Transplant. 2021;40:S499–S500. 10.1016%2Fj.healun.2021.01.20332021/3/20. [Google Scholar]
  32. Lennon V.A., Wingerchuk D.M., Kryzer T.J., Pittock S.J., Lucchinetti C.F., Fujihara K., Nakashima I., Weinshenker B.G. A serum autoantibody marker of neuromyelitis optica: distinction from multiple sclerosis. Lancet. 2004;364:2106–2112. doi: 10.1016/s0140-6736(04)17551-x. 2004/12/11. [DOI] [PubMed] [Google Scholar]
  33. Levin A.T., Hanage W.P., Owusu-Boaitey N., Cochran K.B., Walsh S.P., Meyerowitz-Katz G. Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications. Eur. J. Epidemiol. 2020:1–16. doi: 10.1007/s10654-020-00698-1. 2020/12/8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Liossis S.N.C., Sfikakis P.P. Rituximab-induced B cell depletion in autoimmune diseases: potential effects on T cells. Clin. Immunol. 2008;127:280–285. doi: 10.1016/j.clim.2008.01.011. 2008/3/11. [DOI] [PubMed] [Google Scholar]
  35. Louapre C., Collongues N., Stankoff B., Giannesini C., Papeix C., Bensa C., Deschamps R., Créange A., Wahab A., Pelletier J. Clinical characteristics and outcomes in patients with coronavirus disease 2019 and multiple sclerosis. JAMA Neurol. 2020;77:1079–1088. doi: 10.1001/jamaneurol.2020.2581. 2020/6/26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Louapre C., Ibrahim M., Maillart E., Abdi B., Papeix C., Stankoff B., Dubessy A.L., Bensa-Koscher C., Créange A., Chamekh Z. Anti-CD20 therapies decrease HUMORAL immune response to SARS-CoV-2 in patients with multiple sclerosis or neuromyelitis optica spectrum disorders. J. Neurol. Neurosurg. Psychiatry. 2021 doi: 10.1136/jnnp-2021-326904. 2021/8/2. [DOI] [PubMed] [Google Scholar]
  37. Louapre C., Maillart E., Papeix C., Zeidan S., Biotti D., Lepine Z., Wahab A., Zedet M., Labauge P., Tilikete C. Outcomes of coronavirus disease 2019 in patients with neuromyelitis optica and associated disorders. Eur. J. Neurol. 2020 doi: 10.1111/ene.14612. 2020/11/27. [DOI] [PubMed] [Google Scholar]
  38. Lucchinetti C.F., Guo Y., Popescu B.F.G., Fujihara K., Itoyama Y., Misu T. The pathology of an autoimmune Astrocytopathy: lessons learned from neuromyelitis optica. Brain Pathol. 2014;24:83–97. doi: 10.1111/bpa.12099. 2014/1/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Luna G., Alping P., Burman J., Fink K., Fogdell-Hahn A., Gunnarsson M., Hillert J., Langer-Gould A., Lycke J., Nilsson P. Infection risks among patients with multiple sclerosis treated with fingolimod, natalizumab, rituximab, and injectable therapies. JAMA Neurol. 2020;77:184–191. doi: 10.1001/jamaneurol.2019.3365. 2020/3/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Luo P., Liu Y., Qiu L., Liu X., Liu D., Li J. Tocilizumab treatment in COVID-19: a single center experience. J. Med. Virol. 2020;92:814–818. doi: 10.1002/jmv.25801. 2020/4/15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Maillart E., Papeix C., Lubetzki C., Roux T., Pourcher V., Louapre C. Beyond COVID-19: DO MS/NMO-SD patients treated with anti-CD20 therapies develop SARS-CoV2 antibodies? Mult. Scler. Relat. Disord. 2020;46 doi: 10.1016/j.msard.2020.102482. 2020/9/3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Mantero V., Rigamonti A., Basilico P., Crespi M., Balgera R., Salmaggi A. Mild COVID-19 infection in an NMO patient treated with tocilizumab: a confirmation of anti-IL-6 protective role? J. Neurol. 2020;267:3465–3466. doi: 10.1007/s00415-020-10039-7. 2020/7/7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Mathur R., Rentsch C.T., Morton C.E., Hulme W.J., Schultze A., MacKenna B., Eggo R.M., Bhaskaran K., Wong A.Y., Williamson E.J. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalization, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet. 2021;397:1711–1724. doi: 10.1016/s0140-6736(21)00634-6. 2021/4/30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Mealy M.A., Kessler R.A., Rimler Z., Reid A., Totonis L., Cutter G., Kister I., Levy M. Mortality in neuromyelitis optica is strongly associated with African ancestry. Neurol. Neuroimmunol. Neuroinflamm. 2018;5 doi: 10.1212/NXI.0000000000000468. 2018/6/7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Mehdipour R., Ashtari F. The impact of COVID19 pandemic on neuromyelitis optica spectrum disorder patients in Isfahan, Iran. Mult. Scler. J. 2020;103 doi: 10.1177/1352458520974938. -103. [DOI] [Google Scholar]
  46. Mélet J., Mulleman D., Goupille P., Ribourtout B., Watier H., Thibault G. Rituximab-induced T cell depletion in patients with rheumatoid arthritis: association with clinical response. Arthritis Rheum. 2013;65:2783–2790. doi: 10.1002/art.38107. 2013/11/1. [DOI] [PubMed] [Google Scholar]
  47. Michala J., Michaela T., Magda H., Daniela V., Irena R., Iveta N., Kristyna D., Pavel D., Jiri P., Stanislav V. Predictive factors for a severe course of COVID-19 infection in myasthenia gravis patients with an overall impact on myasthenic outcome status and survival. Eur. J. Neurol. 2021 doi: 10.1111/ene.14951. 2021/6/25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Mirmosayyeb O., Vaheb S., Barzegar M., Shaygannejad V., Bonavita S., Ghajarzadeh M. Screening neuromyelitis optica patients for COVID-19 infection. Autoimmun. Rev. 2020;19 doi: 10.1016/j.autrev.2020.102669. 10.1016%2Fj.autrev.2020.1026692020/9/14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Moghadasi A.N., Mirmosayyeb O., Barzegar M., Sahraian M.A., Ghajarzadeh M. The prevalence of COVID-19 infection in patients with multiple sclerosis (MS): a systematic review and meta-analysis. Neurol. Sci. 2021:1–7. doi: 10.1007/s10072-021-05373-1. 2021/6/7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Moher D., Shamseer L., Clarke M., Ghersi D., Liberati A., Petticrew M., Shekelle P., Stewart L.A. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015;4:1–9. doi: 10.1186/2046-4053-4-1. 2015/1/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Montero-Escribano P., Matías-Guiu J., Gómez-Iglesias P., Porta-Etessam J., Pytel V., Matias-Guiu J.A. Anti-CD20 and COVID-19 in multiple sclerosis and related disorders: a case series of 60 patients from Madrid, Spain. Mult. Scler. Relat. Disord. 2020;42 doi: 10.1016/j.msard.2020.102185. 2020/5/7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Nikoo Z., Badihian S., Shaygannejad V., Asgari N., Ashtari F. Comparison of the efficacy of azathioprine and rituximab in neuromyelitis optica spectrum disorder: a randomized clinical trial. J. Neurol. 2017;264:2003–2009. doi: 10.1007/s00415-017-8590-0. 2017/8/22. [DOI] [PubMed] [Google Scholar]
  53. Ogedegbe G., Ravenell J., Adhikari S., Butler M., Cook T., Francois F., Iturrate E., Jean-Louis G., Jones S.A., Onakomaiya D. Assessment of racial/ethnic disparities in hospitalization and mortality in patients with COVID-19 in New York City. JAMA Netw. Open. 2020;3 doi: 10.1001/jamanetworkopen.2020.26881. e2026881-e20268812020/12/4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. World Health Organization . World Health Organization; 2020. Getting Your Workplace Ready for COVID-19: How COVID-19 Spreads, 19 March 2020.https://apps.who.int/iris/handle/10665/331584 2020/3/3. [Google Scholar]
  55. World Health Organization, 2021. Coronavirus disease (COVID-19) Weekly Epidemiological Update and Weekly Operational Update. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports. (accessed 20 July 2021).
  56. Parrotta E., Kister I., Charvet L., Sammarco C., Saha V., Charlson R.E., Howard J., Gutman J.M., Gottesman M., Abou-Fayssal N. COVID-19 outcomes in MS: observational study of early experience from NYU multiple sclerosis comprehensive care center. Neurol. Neuroimmunol. Neuroinflamm. 2020;7 doi: 10.1212/nxi.0000000000000835. 2020/7/9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Prosperini L., Tortorella C., Haggiag S., Ruggieri S., Galgani S., Gasperini C. Increased risk of death from COVID-19 in multiple sclerosis: a meta-analysis of observational studies. J. Neurol. Sci. 2021:429. doi: 10.1007/s00415-021-10803-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Ritter M., Pirofski L. Mycophenolate mofetil: effects on cellular immune subsets, infectious complications, and antimicrobial activity. Transpl. Infect. Dis. 2009;11:290–297. doi: 10.1111/j.1399-3062.2009.00407.x. 2009/5/29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Rosas I.O., Bräu N., Waters M., Go R.C., Hunter B.D., Bhagani S., Skiest D., Aziz M.S., Cooper N., Douglas I.S. Tocilizumab in hospitalized patients with severe Covid-19 pneumonia. N. Engl. J. Med. 2021;384:1503–1516. doi: 10.1056/NEJMoa2028700. 2021/4/22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Sahraian M.A., Azimi A., Navardi S., Rezaeimanesh N., Moghadasi A.N. Evaluation of COVID-19 infection in patients with neuromyelitis optica spectrum disorder (NMOSD): a report from Iran. Mult. Scler. Relat. Disord. 2020;44 doi: 10.1016/j.msard.2020.102245. 2020/6/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Salter A., Fox R.J., Newsome S.D., Halper J., Li D.K., Kanellis P., Costello K., Bebo B., Rammohan K., Cutter G.R. Outcomes and risk factors associated with SARS-CoV-2 infection in a North American registry of patients with multiple sclerosis. JAMA Neurol. 2021;78:699–708. doi: 10.1001/jamaneurol.2021.0688. 2021/6/1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Sanyaolu A., Okorie C., Marinkovic A., Patidar R., Younis K., Desai P., Hosein Z., Padda I., Mangat J., Altaf M. Comorbidity and its impact on patients with COVID-19. SN Compr. Clin. Med. 2020:1–8. doi: 10.1007/s42399-020-00363-4. 10.1007%2Fs42399-020-00363-42020/6/25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Seksik P., Cosnes J., Sokol H., Nion-Larmurier I., GENDRE J.P., Beaugerie L. Incidence of benign upper respiratory tract infections, HSV and HPV cutaneous infections in inflammatory bowel disease patients treated with azathioprine. Aliment. Pharmacol. Ther. 2009;29:1106–1113. doi: 10.1111/j.1365-2036.2009.03973.x. 2009/5/15. [DOI] [PubMed] [Google Scholar]
  64. Shahmohammadi S., Doosti R., Shahmohammadi A., Mohammadianinejad S.E., Sahraian M.A., Azimi A.R., Harirchian M.H., Asgari N., Moghadasi A.N. Autoimmune diseases associated with neuromyelitis optica spectrum disorders: a literature review. Mult. Scler. Relat. Disord. 2019;27:350–363. doi: 10.1016/j.msard.2018.11.008. 2018/11/16. [DOI] [PubMed] [Google Scholar]
  65. Sharifian-Dorche M., Sahraian M.A., Fadda G., Osherov M., Sharifian-Dorche A., Karaminia M., Saveriano A.W., La Piana R., Antel J.P., Giacomini P.S. COVID-19 and disease-modifying therapies in patients with demyelinating diseases of the central nervous system: a systematic review. Mult. Scler. Relat. Disord. 2021 doi: 10.1016/j.msard.2021.102800. 2021/1/29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Sormani M.P., De Rossi N., Schiavetti I., Carmisciano L., Cordioli C., Moiola L., Radaelli M., Immovilli P., Capobianco M., Trojano M. Disease-modifying therapies and coronavirus disease 2019 severity in multiple sclerosis. Ann. Neurol. 2021;89:780–789. doi: 10.1002/ana.26028. 2021/02/09. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Sormani M.P., Salvetti M., Labauge P., Schiavetti I., Zephir H., Carmisciano L., Bensa C., De Rossi N., Pelletier J., Cordioli C. DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France. Ann. Clin. Transl. Neurol. 2021 doi: 10.1002/acn3.51408. 2021/7/7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyzes. Eur. J. Epidemiol. 2010;25:603–605. doi: 10.1007/s10654-010-9491-z. 2010/7/22. [DOI] [PubMed] [Google Scholar]
  69. Stastna D., Menkyova I., Drahota J., Mazouchova A., Adamkova J., Ampapa R., Grunermelova M., Peterka M., Recmanova E., Rockova P., Rous M., Stetkarova I., Valis M., Vachova M., Woznicova I., Horakova D. Multiple sclerosis, neuromyelitis optica spectrum disorder and COVID-19: a pandemic year in Czechia. Mult. Scler. Relat. Disord. 2021;54 doi: 10.1016/j.msard.2021.103104. 2021/6/24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Statista, 2021. Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group. https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/. (accessed 14 August 2021).
  71. Sterne J.A., Murthy S., Diaz J.V., Slutsky A.S., Villar J., Angus D.C., Annane D., Azevedo L.C.P., Berwanger O., Cavalcanti A.B. Association between administration of systemic corticosteroids and mortality among critically ill patients with COVID-19: a meta-analysis. JAMA. 2020;324:1330–1341. doi: 10.1001/jama.2020.17023. 2020/10/6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Sze S., Pan D., Nevill C.R., Gray L.J., Martin C.A., Nazareth J., Minhas J.S., Divall P., Khunti K., Abrams K.R. Ethnicity and clinical outcomes in COVID-19: a systematic review and meta-analysis. EClinicalMedicine. 2020 doi: 10.1016/j.eclinm.2020.100630. 2020/11/12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Thakur B., Dubey P., Benitez J., Torres J.P., Reddy S., Shokar N., Aung K., Mukherjee D., Dwivedi A.K. A systematic review and meta-analysis of geographic differences in comorbidities and associated severity and mortality among individuals with COVID-19. Sci. Rep. 2021;11:1–13. doi: 10.1038/s41598-021-88130-w. 2021/4/20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Tisminetzky M., Delude C., Hebert T., Carr C., Goldberg R.J., Gurwitz J.H. Age, multiple chronic conditions, and COVID-19: a literature review. J. Gerontol. Ser. A. 2020 doi: 10.1093/gerona/glaa320. 2020/12/24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Tomczak A., Han M.H. The impact of COVID-19 on patients with neuromyelitis optica spectrum disorder; a pilot study. Mult. Scler. Relat. Disord. 2020;45 doi: 10.1016/j.msard.2020.102347. 2020/6/30. [DOI] [PubMed] [Google Scholar]
  76. Veiga V.C., Prats J.A., Farias D.L., Rosa R.G., Dourado L.K., Zampieri F.G., Machado F.R., Lopes R.D., Berwanger O., Azevedo L.C. Effect of tocilizumab on clinical outcomes at 15 days in patients with severe or critical coronavirus disease 2019: randomised controlled trial. BMJ. 2021;372 doi: 10.1136/bmj.n84. 2021/1/20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Viswanathan S. Management of idiopathic CNS inflammatory diseases during the COVID-19 pandemic: perspectives and strategies for continuity of care from a South East Asian Center with limited resources. Mult. Scler. Relat. Disord. 2020;44 doi: 10.1016/j.msard.2020.102353. 2020/07/03. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Wingerchuk D.M., Lennon V.A., Lucchinetti C.F., Pittock S.J., Weinshenker B.G. The spectrum of neuromyelitis optica. Lancet Neurol. 2007;6:805–815. doi: 10.1016/s1474-4422(07)70216-8. 2007/9/1. [DOI] [PubMed] [Google Scholar]
  79. Woo M.S., Steins D., Häußler V., Kohsar M., Haag F., Elias-Hamp B., Heesen C., Lütgehetmann M., Zur Wiesch J.S., Friese M.A. Control of SARS-CoV-2 infection in rituximab-treated neuroimmunological patients. J. Neurol. 2021;268:5–7. doi: 10.1007/s00415-020-10046-8. 10.1007%2Fs00415-020-10046-82020/7/11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Xu X., Han M., Li T., Sun W., Wang D., Fu B., Zhou Y., Zheng X., Yang Y., Li X. Effective treatment of severe COVID-19 patients with tocilizumab. Proc. Natl. Acad. Sci. 2020;117:10970–10975. doi: 10.1073/pnas.2005615117. 2020/5/19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Yin H., Zhang Y., Xu Y., Peng B., Cui L., Zhang S. The impact of COVID-19 on patients with neuromyelitis optica spectrum disorder beyond infection risk. Front. Neurol. 2021;12:351. doi: 10.3389/fneur.2021.657037. 2021/3/22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Zeidan S., Maillart E., Louapre C., Roux T., Lubetzki C., Papeix C. COVID-19 infection in NMO/SD patients: a French survey. J. Neurol. 2021;268:1188–1190. doi: 10.1007/s00415-020-10112-1. 10.1007%2Fs00415-020-10112-12020/9/12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Zhao-Fleming H.H., Sanchez C.V., Sechi E., Inbarasu J., Wijdicks E.F., Pittock S.J., Chen J.J., Wingerchuk D.M., Weinshenker B.G., Lopez-Chiriboga S. CNS demyelinating attacks requiring ventilatory support with myelin oligodendrocyte glycoprotein or aquaporin-4 antibodies. Neurology. 2021;97:e1351–e1358. doi: 10.1212/WNL.0000000000012599. 2021/9/28. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx (66.6KB, docx)

Data Availability Statement

All data will be available for secondary analysis in necessary cases from the corresponding author through an email address.

Articles from Multiple Sclerosis and Related Disorders are provided here courtesy of Elsevier

RESOURCES