Abstract
Background and Objectives
Infections are associated with an increased risk of relapse and pseudo-relapse in persons with multiple sclerosis (MS). However, the relationship with relapses and pseudo-relapses after SARS-CoV-2 infections (COVID) vs other infections in MS is poorly understood. Therefore, we compared the occurrence of relapse and pseudo-relapse after COVID and other infections with noninfected participants with MS.
Methods
In spring 2023, we surveyed participants from the North American Research Committee on Multiple Sclerosis Registry regarding whether they had had a COVID infection, other infections, relapses, and pseudo-relapses. Recent infections, occurring in the 6 months before the survey, were used to categorize participants into groups: recent COVID, non-COVID infection (with no history of ever having COVID), COVID and non-COVID infections, or uninfected.
Results
Of the 4,787 participants eligible for analysis, 2,927 participants were included, of whom 294 (10%) had a recent COVID infection; 853 (29.1%) had 1 recent infection other than COVID; 246 (8.4%) had a recent COVID and non-COVID infection; and 1,534 (52.4%) had no infection with COVID nor any infection within the past 6 months (uninfected). Compared with no infections, non-COVID infection was associated with a 39% increased likelihood of relapse (1.39, 95% CI [1.04–1.87]), whereas a recent COVID infection was associated with a decreased likelihood of relapse (0.45 [0.23, 0.87]), adjusting for covariates. All infection groups were associated with increased odds of pseudo-relapse compared with the uninfected group (non-COVID infections: 1.78 [1.44, 2.20]; COVID infection: 1.80 [1.32, 2.45]; COVID and non-COVID infection: 3.04 [2.24, 4.12]).
Discussion
Because individuals with MS are at increased risk of infections, the association of infections with relapses and pseudo-relapses is clinically important. The high prevalence of acute worsening after infection, regardless of the type of infection, compared with those with no reported infection, needs to be considered in the management of persons with MS.
Introduction
Infections confer an increased risk of relapse in people with multiple sclerosis (MS), and relapses contribute to the accumulation of disability. Among 170 participants with MS, investigators identified nearly three-fold higher annual relapse rates in the two-week period preceding onset of infection through 5 weeks afterward compared with periods unrelated to infection.1 Over one-quarter (27%) of these relapses were related to infection. Other studies have noted that influenza infection is associated with an increased risk of relapse.2 Since the emergence of the SARS-CoV-2 infection (COVID, COVID pandemic), the effects of infection have received greater attention generally and in people with MS. Several studies in MS have reported the association between COVID infection and relapses, and most of these have reported that COVID infection was not associated with relapses using pre-post or controlled postinfection designs.3-5 However, most of these studies had relatively modest sample sizes.
In addition to relapses, infection may cause pseudo-relapses. Pseudo-relapses involve temporary worsening of MS-related symptoms secondary to factors such as systemic illness, including infection.6 Much less attention has been paid to pseudo-relapses despite their adverse effects on daily function and quality of life. In a study of 111 people with MS, 17% (19/111) of individuals were described as worse post-COVID with the etiology of the worsening ascribed to pseudo-relapses.7 Thus, we know little about the rates of pseudo-relapses in association with COVID infection, and we do not know whether these rates differ from those related to other infections more generally. Differentiating between immune-mediated relapses and pseudo-relapses is clinically important. Relapses may warrant changes in disease-modifying therapy (DMT), whereas this would be inappropriate for pseudo-relapses where the target should be the underlying illness.
Given the frequency with which infections occur in people with MS and the increased risk of infections among those who are immunosuppressed, it is important to understand the association of infections with relapses and pseudo-relapses. Therefore, we aimed to evaluate the association of COVID infection with the rate of relapses and pseudo-relapses in a large cohort and compare this with the association of non-COVID infection with those outcomes. We hypothesized that a greater proportion of those in infection groups would report a relapse or pseudo-relapse compared with those uninfected.
Methods
Study Design and Data Source
Cross-sectional data from the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry were used for this study. The NARCOMS Registry is a self-report registry for people with MS, who complete questionnaires at enrollment as well as semiannually to update their sociodemographic and clinical information.8 Questionnaires are completed by mail or online, according to participant preference. Key components used in the NARCOMS Registry have been validated including self-reported diagnoses of MS and the disability measures.9-12
Standard Protocol Approvals, Registrations, and Participant Consents
Participants agreed to the use of their deidentified information for research. The registry was approved by the Institutional Review Board at UT Southwestern when this study was conducted.
Infections
The Spring 2023 semiannual survey was administered to participants from April to May 2023 and included questions regarding infections that occurred between November 2022 and April 2023. This time window was chosen to reflect previous reports that relapses occur within approximately 2 weeks before infection to 5–6 weeks after infection.1 Participants reported whether they had any of the following infections in the past 6 months: influenza, common cold, gastrointestinal tract infection, pneumonia, zoster (shingles), strep throat, urinary tract infection (UTI), skin infection, osteomyelitis, and joint infection. Participants also reported whether they had ever had a SARS-CoV-2 infection and, if they had, were asked to report the dates of their first and most recent infections and whether infection was confirmed using an at-home or laboratory test. Information on hospitalizations and the reason for hospitalization is collected routinely; however, only a small number of participants reported (n = 16; 6 with recent COVID, 10 with COVID + non-COVID) being hospitalized because of a COVID infection, which precluded further analysis.
Relapses and Pseudo-Relapses
After providing detailed descriptions of relapses and pseudo-relapses (Figure 1), participants were asked to report whether they had a relapse within the past 6 months, how many relapses they had, and whether they had been treated with corticosteroids for their relapse. Participants who reported experiencing a pseudo-relapse were asked to report the number of pseudo-relapses they had experienced. In addition, they were asked what symptoms were associated with their most recent pseudo-relapse, including fatigue, memory or thinking problems, vision changes, dizziness/vertigo, speech changes, chewing/swallowing, bladder problems, bowel problems, hand/arm weakness, leg/foot weakness, muscle tightness or stiffness, difficulty walking, sexual problems, pain, coordination (tripping or dropping things), and others. Participants who had a COVID and/or 1 other infection and reported experiencing a relapse or pseudo-relapse were sent an additional follow-up survey to determine the month of their relapse(s) and pseudo-relapse(s).
Figure 1. Definitions of Relapse and Pseudo-Relapse.
Sociodemographic and Clinical Characteristics
Information regarding date of birth (used to derive age), race, ethnicity, level of education attained, sex, and age at MS diagnosis (used to derive disease duration) was reported in the enrollment questionnaire. Annual household income, severity of disability as well as current clinical course, and DMT were provided in the Spring 2023 questionnaire. We categorized race as White, African American/Black, and other; the number of participants reporting Hispanic ethnicity was too small for analysis (<50). Education level was categorized as high school/general educational development test, and postsecondary level (associate degree, bachelor's degree, postgraduate education, and technical degree). Annual household income was categorized as <$50,000; >$50,00; and “I do not wish to answer.” Disability status was measured using the patient-determined disease steps (PDDSs), a single-item measure with 8 potential responses ranging from 0 (normal) to 8 (bedridden).13,14 The PDDS correlates strongly with the physician-scored Expanded Disability Status Scale.9,15 DMTs were categorized as anti-CD20s, S1P modulators, other, and none/not answered based on their association with developing COVID infection.16
Statistical Analysis
We included survey responders with a confirmed diagnosis of MS, living in the United States, aged older than 18 years, and who responded to the infection-related questions. We divided respondents into 4 groups based on the reported infections: a COVID infection in the past 6 months (recent COVID); 1 infection other than COVID in the past 6 months (recent non-COVID); a recent COVID infection and 1 infection other than COVID in the past 6 months (recent COVID and non-COVID); and those reporting no COVID or non-COVID infection (uninfected). Participants included in the uninfected group reported never having a positive COVID test during the period between spring 2020 and spring 2023. Participant characteristics were summarized using mean (SD), median (interquartile range), and frequency (percent). We assessed differences in demographic and clinical characteristics between infection groups using analysis of variance (with Tukey adjustment for pairwise comparisons) or the Kruskal-Wallis test (with Dwass, Steel, Critchlow-Flinger pairwise tests), for continuous variables as appropriate, and χ2 tests or the Fisher exact test, as appropriate, for categorical variables. Nonresponders were characterized using descriptive statistics, and differences between responders and nonresponders were evaluated similarly.
Differences in the prevalence of relapses and pseudo-relapses between groups were examined using univariate and multivariable logistic regression adjusted for age at the time of the survey, sex (reference = female), race (reference = White), education (reference = less than a bachelor's degree), annual income (reference = ≤$50,000), PDDSs at the time of the survey, and COVID vaccination status (reference = yes). The unadjusted and adjusted odds ratio and its 95% CI are reported. Missing data were not imputed. For those participants with timing information, differences in the proportion of relapses occurring 1 month before, around, and 1 month after infection between the infection groups were evaluated using χ2 tests and binomial proportions with Agresti-Coull CIs. Statistical analyses were conducted in SAS v9.4 (SAS Institute, Cary, NC).
Complementary Analyses
In an exploratory analysis, we tested whether the type of DMT modified the association between infection and outcome (relapses and pseudo-relapses) by adding an interaction term in the models.
Data Availability
Individual participant data that underlie the results reported in this article, after deidentification, will be made available for replication on request. Proposals should be directed to msregistry@narcoms.org; to gain access, data requestors will need to sign a data access agreement.
Results
Participants
The Spring 2023 survey invitations were distributed to 7,782 participants, of whom 5,239 (67.3%) responded. Compared with responders, nonresponders were on average 1 year younger, were less likely to self-identify as White, had a lower level of education, and had a higher level of disability at enrollment (eTable 1). After excluding 452 respondents not eligible for the analysis, 4,787 participants were classified into 4 groups. Of which, a total of 2,927 participants with a single recent infection, with both a COVID and a non-COVID infection, or with no infection were included (eFigure 1). There were 294 participants (10.0%) who had a COVID infection in the past 6 months; 853 (29.1%) had 1 infection other than COVID in the past 6 months; 246 (8.4%) had both a COVID and a non-COVID infection; and 1,534 (52.4%) had no infection (COVID ever nor any other infection within the past 6 months). In those participants reporting a non-COVID infection in the previous 6 months, the most frequent non-COVID infections were cold (38.3%), UTI (38.1%), gastrointestinal infection (7.4%), influenza (6.4%), skin infection (5.7%), shingles (1.8%), pneumonia (1.2%), strep infection (0.7%), bone infection (0.24%), and joint infection (0.1%).
Participants with a recent COVID infection were more likely to be younger (p < 0.001), have lower PDDSs (p < 0.001), and be taking a DMT (p < 0.001) than those with no infections and those with a non-COVID infection. The group with a recent COVID infection was more likely to be associated with higher education (p = 0.001), income of greater than $50,000 (p < 0.0001), and married/cohabitation (p = 0.006) than those with no infections but did not differ from those with a non-COVID infection. Those participants with no infections were older at diagnosis (p = 0.003) and had longer disease duration (p = 0.003) compared with those with recent COVID infection, but not those with a non-COVID infection. Participants with recent COVID and one non-COVID infection were more likely to be younger than those with no infections (p < 0.001) and those with a non-COVID infection (p = 0.005), had higher PDDSs than those with only one non-COVID infection (p = 0.007), and were more likely to be married (p = 0.005) than participants with no infections (Table 1).
Table 1.
Demographic and Clinical Characteristics Overall and by Infection Group
| No infections (N = 1,534) | Recent COVID (N = 294) | One infection only (N = 853) | COVID + one infection (N = 246) | Total (N = 2,927) | p Value | |
| Age, mean (SD) | 67.2 (8.89) | 63.0 (10.38) | 66.9 (9.29) | 64.2 (11.16) | 66.4 (9.47) | <0.001a |
| Sex, n (%) | 0.045b | |||||
| Female | 1,199 (78.2) | 235 (79.9) | 707 (83.0) | 200 (81.3) | 2,341 (80.0) | |
| Male | 334 (21.8) | 59 (20.1) | 145 (17.0) | 46 (18.7) | 584 (20.0) | |
| Race, n (%) | 0.35b | |||||
| White/Caucasian | 1,324 (93.0) | 255 (95.1) | 748 (94.8) | 221 (95.3) | 2,548 (93.9) | |
| Black/African American | 51 (3.6) | 7 (2.6) | 19 (2.4) | 8 (3.4) | 85 (3.1) | |
| Other | 49 (3.4) | 6 (2.2) | 22 (2.8) | 3 (1.3) | 80 (2.9) | |
| Education level, n (%) | 0.001b | |||||
| Bachelor's or higher | 866 (57.1) | 187 (65.6) | 463 (55.3) | 158 (65.8) | 1,674 (58.1) | |
| Nonbachelor's | 651 (42.9) | 98 (34.4) | 374 (44.7) | 82 (34.2) | 1,205 (41.9) | |
| Annual income, n (%) | <0.001b | |||||
| $50,000 or greater | 618 (40.8) | 157 (53.6) | 361 (42.8) | 124 (50.6) | 1,260 (43.5) | |
| <$50,000 | 519 (34.2) | 61 (20.8) | 281 (33.3) | 61 (24.9) | 922 (31.8) | |
| Do not wish to answer | 379 (25.0) | 75 (25.6) | 201 (23.8) | 60 (24.5) | 715 (24.7) | |
| Marital status, n (%) | 0.006b | |||||
| Married/partner | 951 (62.1) | 204 (69.6) | 542 (64.0) | 175 (71.4) | 1872 (64.2) | |
| Single | 581 (37.9) | 89 (30.4) | 305 (36.0) | 70 (28.6) | 1,045 (35.8) | |
| Age at symptom onset, mean (SD) | 32.5 (10.20) | 31.0 (9.63) | 31.3 (9.80) | 31.4 (10.42) | 31.9 (10.06) | 0.01a |
| Age at diagnosis, mean (SD) | 40.0 (10.01) | 37.9 (9.72) | 39.0 (9.91) | 38.7 (10.50) | 39.4 (10.01) | 0.003a |
| Disease duration, mean (SD) | 40.0 (10.05) | 37.9 (9.72) | 39.0 (9.91) | 38.7 (10.50) | 39.4 (10.04) | 0.003a |
| PDDS, median (IQR) | 4.0 (1.0, 6.0) | 3.0 (1.0, 5.0) | 4.0 (2.0, 6.0) | 4.0 (1.0, 6.0) | 4.0 (1.0, 6.0) | <0.001a |
| DMT reported currently taking in spring 2023, n (%) | <0.001b | |||||
| Low | 431 (28.1) | 91 (31.0) | 229 (26.8) | 56 (22.8) | 807 (27.6) | |
| S1P modulators | 50 (3.3) | 21 (7.1) | 17 (2.0) | 10 (4.1) | 98 (3.3) | |
| CD20 | 179 (11.7) | 64 (21.8) | 123 (14.4) | 53 (21.5) | 419 (14.3) | |
| None | 874 (57.0) | 118 (40.1) | 484 (56.7) | 127 (51.6) | 1,603 (54.8) | |
| COVID vaccination status, n (%) | 0.13c | |||||
| Yes | 1,404 (91.8) | 273 (93.2) | 796 (93.8) | 237 (96.7) | 2,710 (92.9) | |
| No | 117 (7.6) | 19 (6.5) | 50 (5.9) | 8 (3.3) | 194 (6.7) | |
| Do not know | 9 (0.6) | 1 (0.3) | 3 (0.4) | 0 (0.0) | 13 (0.4) |
Abbreviations: DMT = disease-modifying therapy; IQR = interquartile range; PDDSs = patient-determined disease steps.
Analysis of variance F test p value.
Chi-squared p value.
Fisher exact test.
Missing data: sex = 2, race = 214, education level = 48, annual income = 30, marital status = 10, age at diagnosis = 17, disease duration = 15, and COVID vaccination status = 10.
In the Spring 2023 survey, there were 882 participants from the infection cohorts who reported having an infection and either a pseudo-relapse, relapse, or both. Overall, 715 (81%) responded; of those, 431 were in the analysis infection groups (recent COVID infection group, 78/271, 28.8%; non-COVID infection, 239/308, 77.6%; COVID and non-COVID infection group, 96/303, 31.7%; eTable 2). Participants in the infection groups who provided a date for their infection and relapse and/or pseudo-relapse were included in the timing cohort analysis (n = 226).
Relapses
Overall, 292 participants (10.0%) reported experiencing a relapse within the previous 6 months. Of those with a recent COVID infection and a non-COVID infection, 13.5% reported a relapse; in those with non-COVID infection, 12.4% reported a relapse, while 9.1% of those with no infection and 5.1% with a recent COVID infection reported a relapse (Table 2, p < 0.001). Most of these relapses were not treated with steroids (Table 2). Compared with no infections, a non-COVID infection was associated with 38% increased odds of relapse (aOR: 1.38, 95% CI [1.04–1.85], p = 0.03), whereas a recent COVID infection was associated with decreased odds of relapse (aOR: 0.44, 95% CI [0.23–0.85], p = 0.02) after adjusting for covariates. Participants with recent COVID and one non-COVID infection were not significantly associated with a relapse (aOR: 1.55, 95% CI [0.99–2.42, p = 0.05]). Focusing on DMTs, there was nominal decrease in relapses and relapses treated with steroids compared with the other infection groups (eFigure 2, A and B). No differences in the proportion with relapses were identified between the infection groups and DMT category (p = 0.90).
Table 2.
Frequency of Relapses and Pseudo-Relapses Overall and by Infection Group
| No infections (N = 1,534) | Recent COVID (N = 294) | One infection only (N = 853) | Recent COVID + one infection (N = 246) | Total (N = 2,927) | p Value | |
| Relapse in past 6 mo, n (%) | <0.001a | |||||
| Yes | 139 (9.1) | 15 (5.1) | 105 (12.4) | 33 (13.5) | 292 (10.0) | |
| No | 1,394 (90.9) | 279 (94.9) | 744 (87.6) | 212 (86.5) | 2,629 (90.0) | |
| Number of relapses, median (IQR) | 0.0 (0.0, 0.0) | 0.0 (0.0, 0.0) | 0.0 (0.0, 0.0) | 0.0 (0.0, 0.0) | 0.0 (0.0, 0.0) | 0.03b |
| Relapse treated with steroids, n (%) | <0.001a | |||||
| Yes | 26 (1.7) | 2 (0.7) | 26 (3.0) | 14 (5.7) | 68 (2.3) | |
| No | 1,508 (98.3) | 292 (99.3) | 827 (97.0) | 232 (94.3) | 2,859 (97.7) | |
| Pseudo-relapse in past 6 mo, n (%) | <0.001a | |||||
| Yes | 287 (18.8) | 82 (27.9) | 253 (29.9) | 102 (41.5) | 724 (24.8) | |
| No | 1,242 (81.2) | 212 (72.1) | 594 (70.1) | 144 (58.5) | 2,192 (75.2) |
Abbreviation: IQR = interquartile range.
Chi-squared p value.
Analysis of variance F test p value; missing data: relapses = 6 and pseudo-relapses = 11.
Pseudo-Relapses
In total, 724 participants (24.8%) reported experiencing a pseudo-relapse. All infection groups had a higher proportion of participants report experiencing a pseudo-relapse compared to the no infection group (Table 2, p < 0.001). After adjustment, all infection groups were associated with an increased odds of pseudo-relapse compared with the uninfected group. Non-COVID infection was associated with 78% increased odds of pseudo-relapse (aOR: 1.78, 95% CI [1.44–2.19], p < 0.0001) compared with no infection, and COVID infection was associated with 79% increased odds of pseudo-relapse (aOR: 1.79, 95% CI [1.31–2.44], p = 0.0003); the recent COVID and non-COVID infection group had 3-fold increased odds of pseudo-relapse (aOR: 3.04, 95% CI [2.24–4.13], p < 0.0001) compared with those uninfected. Specifically, for DMTs, there was nominal increase in pseudo-relapses in comparing the uninfected, a single infection, and the COVID and non-COVID infection groups (eFigure 2C). No differences in the proportion with pseudo-relapses were identified between the infection groups and DMT category (p = 0.96).
Pseudo-Relapse Symptoms
Participants who reported experiencing a pseudo-relapse most often reported the following pseudo-relapse symptoms: fatigue (80.5%), leg/foot weakness (55.9%), coordination (48.2%), difficulty walking (46.7%), memory or thinking problems (41.3%), and muscle tightness/stiffness (39.0%). After adjusting for age, sex, race, education, income, disability, and COVID vaccination status, bladder problems were almost 2-fold more likely to be reported in the non-COVID infection group compared with those with no infection (aOR: 1.91, 95% CI [1.30–2.81], p = 0.001, Table 3). Those with recent COVID were 2.1-fold less likely to experience muscle tightness/stiffness symptoms [aOR: 0.44, 95% CI [0.25, 0.79], p = 0.01) and 2.5-fold more likely to experience chewing/swallowing symptoms (aOR: 2.5, 95% CI [1.20–5.12], p = 0.01) compared with those with no infection. Those with recent COVID and non-COVID infection were almost 2-fold more likely to experience bladder problems (aOR: 1.88, [1.13, 3.14], p = 0.01). No differences in other symptoms between groups after adjusting for covariates were observed (Table 3).
Table 3.
Association of Infection Group With Pseudo-Relapse Symptoms
| Pseudo-relapse symptoms | One infection vs no infections | Recent COVID vs no infections | Recent COVID + non-COVID vs no infections | |||
| Unadjusted | Adjusteda | Unadjusted | Adjusteda | Unadjusted | Adjusteda | |
| OR 95% CI | OR 95% CI | OR 95% CI | OR 95% CI | OR 95% CI | OR 95% CI | |
| Fatigue | 0.78 (0.51–1.18) | 0.82 (0.53–1.29) | 1.67 (0.81–3.44) | 1.73 (0.80–3.75) | 1.01 (0.57–1.81) | 1.07 (0.58–2.00) |
| Memory or thinking problems | 1.11 (0.79–1.57) | 1.17 (0.80–1.71) | 0.88 (0.53–1.45) | 0.74 (0.42–1.30) | 1.35 (0.86–2.13) | 1.36 (0.83–2.24) |
| Vision changes | 0.74 (0.49–1.11) | 0.68 (0.43–1.05) | 0.72 (0.39–1.33) | 0.81 (0.43–1.53) | 0.97 (0.57–1.64) | 0.95 (0.54–1.67) |
| Dizziness/vertigo | 0.97 (0.67–1.40) | 0.92 (0.62–1.38) | 1.22 (0.73–2.04) | 1.09 (0.62–1.92) | 0.72 (0.43–1.21) | 0.65 (0.37–1.13) |
| Speech changes | 0.89 (0.54–1.47) | 0.89 (0.51–1.58) | 1.09 (0.54–2.19) | 1.06 (0.47–2.41) | 1.1 (0.58–2.09) | 1.15 (0.55–2.39) |
| Chewing/swallowing | 1.12 (0.68–1.84) | 1.13 (0.64–1.98) | 1.56 (0.81–3.02) | 2.48 (1.20–5.12) | 1.02 (0.52–2.01) | 1.32 (0.63–2.79) |
| Bladder problems | 1.98 (1.39–2.83) | 1.91 (1.30–2.81) | 0.54 (0.29–1.00) | 0.58 (0.30–1.13) | 1.76 (1.10–2.81) | 1.88 (1.13–3.14) |
| Bowel problems | 1.99 (1.29–3.08) | 1.59 (0.99–2.55) | 1.13 (0.57–2.23) | 1.25 (0.60–2.59) | 1.29 (0.70–2.36) | 1.41 (0.73–2.70) |
| Hand/arm weakness | 0.96 (0.67–1.37) | 0.83 (0.56–1.23) | 0.91 (0.54–1.54) | 0.95 (0.53–1.69) | 1.16 (0.73–1.86) | 1.18 (0.70–1.99) |
| Leg/foot weakness | 1.01 (0.72–1.42) | 0.93 (0.64–1.36) | 0.81 (0.49–1.32) | 0.89 (0.52–1.53) | 1.36 (0.85–2.16) | 1.56 (0.94–2.59) |
| Muscle tightness/stiffness | 0.98 (0.70–1.38) | 0.91 (0.62–1.31) | 0.44 (0.25–0.77) | 0.44 (0.24–0.79) | 1.10 (0.70–1.74) | 1.09 (0.67–1.78) |
| Difficulty walking | 1.05 (0.75–1.48) | 0.97 (0.67–1.42) | 0.69 (0.42–1.14) | 0.77 (0.44–1.35) | 0.79 (0.50–1.24) | 0.86 (0.52–1.43) |
| Sexual problems | 1.02 (0.53–1.98) | 0.93 (0.42–2.02) | 0.51 (0.15–1.75) | 0.54 (0.15–1.99) | 1.29 (0.57–2.94) | 1.46 (0.60–3.58) |
| Pain | 0.88 (0.62–1.25) | 0.8 (0.55–1.18) | 0.62 (0.36–1.05) | 0.71 (0.40–1.26) | 0.75 (0.47–1.2) | 0.87 (0.52–1.44) |
| Coordination (tripping, dropping things) | 1.09 (0.78–1.53) | 0.99 (0.69–1.42) | 0.67 (0.41–1.11) | 0.72 (0.42–1.23) | 0.93 (0.59–1.47) | 0.97 (0.60–1.58) |
| Other | 1.94 (1.02–3.71) | 2.58 (1.25–5.33) | 0.87 (0.28–2.67) | 1.23 (0.38–4.00) | 1.64 (0.70–3.83) | 1.91 (0.74–4.90) |
Abbreviations: OR = odds ratio; PDDS = patient-determined disease step.
Adjusted for sex (reference = female), race (reference = White/Caucasian), education level (reference = nonbachelor's), annual income (reference = <$50K), PDDS, and COVID vaccination status.
Timing of Relapses and Pseudo-Relapses
The proportions of participants in the timing cohort analysis (n = 413) and the full cohort who reported a relapse were comparable (relapse: 26.0% vs 29.5%, p = 0.13; pseudo-relapse: 84.0% vs 85.5%, p = 0.41, respectively). Of those with complete timing information, 29.1% (58/199) had a relapse in the previous 6 months and 11.6% (23/199) had a relapse within 1 month of the infection while 79.9% (159/199) had a pseudo-relapse in the previous 6 months and 46.2% (92/199) had a pseudo-relapse within 1 month of the infection.
Among infection groups having a relapse within 1 month of infection, 13 participants (56.5%) reported having a relapse at the time of infection, 3 (13.0%) within 1 month before, and 7 (30.5%) within 1 month after their infection (Figure 2). No significant differences were noted between recent COVID, non-COVID and recent COVID, and non-COVID infection groups in relation to the timing of their relapses (p = 0.10, Figure 3A).
Figure 2. Timing of Infections, Relapses, and Pseudo-Relapses by Infection Group.
The timing of infection, relapse, and pseudo-relapses for each participant in the (A) recent COVID, (B) 1 infection, and (C) COVID + non-COVID infection groups.
Figure 3. Frequency of Relapses and Pseudo-Relapses Around the Time of Infection by Group.
The frequency of (A) relapses and (B) pseudo-relapses around the time of infection by infection group.
Overall, 42 participants (45.7%) reported having a pseudo-relapse at the time of their infection, 19 (20.7%) before their infection, and 31 (33.7%) after their infection. No significant differences were noted between recent COVID, non-COVID, and recent COVID and non-COVID infection groups in relation to the timing of their relapses (p = 0.11, Figure 3B).
Discussion
Among people with MS, we found increased odds of pseudo-relapse in those with recent COVID infection, non-COVID infection, and recent COVID and non-COVID infection compared with those with no reported infection. Participants with COVID infection had a reduced risk of relapse while those with a non-COVID infection had an increased risk of relapse compared with those uninfected controls. For participants with information on timing of the relapse or pseudo-relapse, most of the pseudo-relapses were reported to occur in the month around the infection while relapses occurring around the time of infection were reported less frequently. These rates were similar for those with a non-COVID and COVID infection.
The association between non-COVID infections and relapses observed in our study is consistent with previous reports examining influenza and other infections. These infections have been shown to be associated with increased rates of relapses (rate ratios of 1.3–3.4) in multiple studies.1,17-20 Consistent with these reports, we observed 38% increased odds of relapse among those with a non-COVID infection. While our findings are at the low end of the other studies reported, this could be due to less precision around the time of the infection or the older age of this cohort. Of interest, after adjusting for multiple factors, COVID infections were associated with a decreased risk of relapse in our participants compared with those uninfected. Given the general association of infections with relapses, we expected an increased risk of relapses after SARS-CoV-2 infection. Although 2 studies have reported an increased risk of relapse after COVID infection,3,21 other studies observed no increased risk of relapse in those with COVID infection.4,5,22 Differences in the study population may partly explain the mixed findings, yet studies investigating potential differences in mechanisms between SARS-CoV-2 and other pathogens may be warranted.
Both infection groups had increased odds of pseudo-relapse, where symptoms improve after the illness resolves, compared with those uninfected. Yet, the proportion reporting pseudo-relapses was relatively high across all 3 groups, highlighting the importance of having a control group. One study observed that a large proportion of their post-COVID cohort had neurologic worsening due to pseudo-relapse (46.3%) and in 4.9% due to relapse.7 The proportion of pseudo-relapses around the time of infection in our study was similar; however, our proportion with relapses was higher. Differences may be due to their study population being younger or data collected earlier in the pandemic. Yet, the high frequency with which pseudo-relapses occur is clinically important because misdiagnosis of these events may result in inappropriate changes to DMT or corticosteroid treatment.6 Symptoms associated with pseudo-relapses in those with non-COVID infection included bladder problems, which may be due in part to 38% of the infections in this group being urinary tract infections. However, UTIs are common in MS,23 and bladder symptoms may be worsened in the presence of other infections. Reporting a recent COVID infection was associated with increased chewing and swallowing symptoms compared with those with no infection. The respiratory nature of the virus and an estimated 30% prevalence of dysphagia in persons with MS may partly explain this association.24 Yet, it is still an important clinical symptom to consider in persons with MS. That the lower odds of muscle tightness/stiffness in those with recent COVID compared with those uninfected is a new observation. COVID is more generally associated with muscle aches and fatigue rather than spasticity, which is more commonly observed in MS.25-27
Most of our study participants were vaccinated for COVID, and our previous reports have shown that uptake of other vaccines has been high, ranging between 59% and 79.9%.28,29 However, vaccination, both in general and specific to COVID, has not been shown to increase relapse rates in MS.30-32 In addition, vaccination may have reduced the severity of infection. We were unable to control for severity in our analysis because a small number of participants reported being hospitalized because of infection; this suggests that most COVID infections were not severe. Future studies would benefit from including measures of infection severity to understand its effect on outcomes.
In those participants with COVID infection, some may have postacute sequela of COVID (PASC, long COVID); however, the rates of PASC may be relatively low in people with MS.22,33 PASC is a concept defined by symptoms, many of which are common in persons with MS, and may be difficult to distinguish from symptoms of MS.27,34,35 When evaluating the RECOVER PASC score based on symptoms of PASC, we found that 15.9% of participants with MS with recent COVID infection would meet current criteria for PASC, but 17.2% of those never reporting COVID infection also met current criteria for PASC.36 When using new persistent symptoms in the PASC score, a low prevalence of PASC was found (1.5% of participants with a COVID infection and 0.23% of those with other infections).36 The association between infections and development of new persistent symptoms after infections is complex, and incorporating objective findings may improve defining PASC in MS.
This study has strengths and limitations. Using a large cohort of individuals with MS, we were able to compare individuals with a recent COVID infection, those with non-COVID infection, and those uninfected. We ascertained the proportion of pseudo-relapses experienced and symptoms associated with those pseudo-relapses from participants. While relapses and pseudo-relapses were self-reported, a recent study showed good overall agreement between patient-reported and physician-reported relapses, although some over-reporting of relapses by patients was observed.32,37 Our analyses controlled for disability level and age, which were associated with higher and lower odds, respectively, of participants over-reporting relapses compared with physicians.37 We observed a low number of relapses that were treated with corticosteroids, which could reflect misclassification of relapses and pseudo-relapses. However, a Canadian study suggests that most relapses are not steroid-treated, and another study observed that only 30.5% of patient relapses were treated.38,39 It is also possible that participants were reluctant to report these events to providers or seek treatment potentially because of lower severity or dissatisfaction with experiences with corticosteroids.40 Given the retrospective cross-sectional study design, we could not determine causality of the associations, nor determine the precise timing of relapses and pseudo-relapses. NARCOMS Registry participants voluntarily participate in the registry, potentially limiting the generalizability of study results. The registry lacks clinical and imaging data because linking to these data sources is not feasible, given the large number of health systems represented in the geographically diverse NARCOMS cohort. The analysis was limited to participants who reported a positive test for COVID infection; however, these tests can produce incorrect results, and participants could experience asymptomatic COVID. Our analyses controlled for COVID vaccination status but not for other vaccinations.
Because individuals with MS are at increased risk of infections, the association of infections with relapses and pseudo-relapses is important for clinical care. Our study highlights the high prevalence of acute worsening after infection, regardless of the type of infection, in persons with MS.
Acknowledgment
NARCOMS is a project of the Consortium of Multiple Sclerosis Centers (CMSC) and the Foundation of the CMSC.
Glossary
- CMSC
Consortium of Multiple Sclerosis Center
- DMT
disease-modifying therapy
- MS
multiple sclerosis
- NARCOMS
North American Research Committee on Multiple Sclerosis
- PASC
postacute sequela of COVID
- PDDS
patient-determined disease step
- UTI
urinary tract infection
Author Contributions
A. Salter: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. S. Lancia: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. M. Sharma: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. G.R. Cutter: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. R.J. Fox: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. R.A. Marrie: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data.
Study Funding
This investigation was supported by a Strategic Initiatives award (SI-2209-40362) from the National Multiple Sclerosis Society.
Disclosure
A. Salter receives research funding from the Multiple Sclerosis Society of Canada, the National Multiple Sclerosis Society, the Consortium of Multiple Sclerosis Centers (CMSC), and the Department of Defense Congressionally Directed Medical Research Program; is a member of the editorial board of Neurology®; serves as a consultant for Gryphon Bio LLC, Sora Neuroscience, and Abata Therapeutics; has equity in Owl Therapeutics; is a member of the data and safety monitoring board for Premature Infants Receiving Milking or Delayed Cord Clamping, Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis, and Methotrexate treatment of Arthritis caused by Chikungunya virus (March); and holds the Kenney Marie Dixon‐Pickens Distinguished Professorship in Multiple Sclerosis Research. S. Lancia and M. Sharma have nothing to disclose. G. Cutter serves on data and safety monitoring boards for Applied Therapeutics, AI Therapeutics, AMO Pharma, Astra-Zeneca, Avexis Pharmaceuticals, Biolinerx, Brainstorm Cell Therapeutics, Bristol Meyers Squibb/Celgene, CSL Behring, Galmed Pharmaceuticals, Green Valley Pharma, Horizon Pharmaceuticals, Immunic, Karuna Therapeutics, Mapi Pharmaceuticals LTD, Merck, Mitsubishi Tanabe Pharma Holdings, Opko Biologics, Prothena Biosciences, Novartis, Regeneron, Sanofi-Aventis, Reata Pharmaceuticals, Teva Pharmaceuticals, National Heart, Lung, and Blood Institute (Protocol Review Committee), University of Texas Southwestern, University of Pennsylvania, and Visioneering Technologies Inc.; has served on consulting or advisory boards for Alexion, Antisense Therapeutics, Biogen, Clinical Trial Solutions LLC, Entelexo Biotherapeutics Inc., Genzyme, Genentech, GW Pharmaceuticals, Immunic, Immunosis Pty Ltd, Klein-Buendel Incorporated, Merck/Serono, Novartis, Perception Neurosciences, Protalix Biotherapeutics, Regeneron, Roche, and SAB Biotherapeutics; is employed by the University of Alabama at Birmingham; and is president of Pythagoras Inc., a private consulting company located in Birmingham, AL. R.J. Fox has received personal consulting fees from Astoria Biologica, Biogen, Bristol Myers Squibb, Cognito, EMD Serono, Galvani, Immunic, INmune Bio, Kiniksa, Novartis, Sanofi, Siemens, TG Therapeutics, and Viracta; served on advisory committees for AB Science, Biogen, Immunic, Novartis, and Sanofi; received clinical trial contract and research grant funding from Biogen, Novartis, and Sanofi; and serves on the editorial boards of Neurology® and Multiple Sclerosis Journal. R.A. Marrie receives research funding from Canadian Institutes of Health Research, MS Canada, Crohn's and Colitis Canada, the National Multiple Sclerosis Society, CMSC, the Arthritis Society, the US Department of Defense, the Pfizer Foundation, and the Public Health Agency of Canada; is a coinvestigator on studies receiving funding from Biogen Idec and Roche Canada; holds the Multiple Sclerosis Chair in Clinical Research; and serves on the editorial board of Neurology®. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/cp.
TAKE-HOME POINTS
→ Infection(s) were associated with an increase in the odds of a pseudo-relapse.
→ Non-COVID infections were associated with increased odds of relapse.
→ Because individuals with MS are at increased risk of infections, the association of infections with relapses and pseudo-relapses is important for clinical care.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Individual participant data that underlie the results reported in this article, after deidentification, will be made available for replication on request. Proposals should be directed to msregistry@narcoms.org; to gain access, data requestors will need to sign a data access agreement.