Article Figures & Data
Figures
- Figure 1 Univariate and Multivariate Regressions of Clinical Characteristics for the Risk of Hospitalization
Univariate and multivariate logistic regression analyses were performed on patient characteristics before COVID-19 infection based on risk for hospitalization (n = 66 for nonhospitalized and n = 25 for hospitalized). (A) Univariate logistic regression was performed on patient characteristics. ORs with 95% CIs are listed in the table to the left. Significant correlations are indicated by bold font and *. Age, disability, employment, number of non-neuroimmunologic comorbidities, hypertension, cardiovascular disease, progressive MS, and higher disability scores (EDSS and 25FTW) were predictive of hospitalization, whereas part-time or full-time employment predicted nonhospitalization. (B) Stepwise multivariate logistic regression utilizing Akaike information criteria was performed using significant hospitalization risk factors in univariate analysis. Only significant independent risk factors for hospitalization are listed in the table (left) and figure (right). Older age, a higher number of non-neuroimmunologic comorbidities, and a longer 25FTW were found to be independent risk factors for hospitalization. 25FTW = Timed 25-Foot Walk; BMI = body mass index; COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy; EDSS = Expanded Disability Status Scale; PPMS = primary progressive MS; RRMS = relapsing-remitting MS; SPMS = secondary progressive MS.
- Figure 2 Univariate and Multivariate Regressions of Presenting Symptoms for the Risk of Hospitalization
Univariate and multivariate logistic regression analyses were performed on presenting symptoms based on risk for hospitalization (n = 66 for nonhospitalized and n = 25 for hospitalized). (A) Univariate logistic regression was performed on presenting symptoms. ORs with 95% CIs are listed in the table to the left. Significant correlations are indicated by bold font and *. Dyspnea, nausea/vomiting, and neurologic symptoms were found to be predictive of hospitalization, whereas headache was found to be predictive of nonhospitalization. (B) Stepwise multivariate logistic regression utilizing Akaike information criteria was performed using significant hospitalization risk factors in univariate analysis. Only significant independent risk factors for hospitalization are listed in the table (left) and figure (right). Only nausea/vomiting and neurologic symptoms (e.g., weakness, sensory symptoms, urinary retention, and gait instability) were found to be independent risk factors for hospitalization, whereas headache was the only independent predictor of nonhospitalization.
- Figure 3 Significant Laboratory Values Before/During/After COVID-19 Infection
Laboratory tests were obtained before, during, and after COVID-19 infection. (A) Laboratory values before, during, and after COVID-19 infection grouped by hospitalization status (nonhospitalized [left] and hospitalized [right]) were analyzed for significant effects of time and/or hospitalization. Values are listed as averages with SEM in parenthesis, and the rightward column indicating the number of values included in that average. Values represent unique contributions from 49 nonhospitalized patients and 19 hospitalized patients. Significance was determined by two-way analysis of variance, with significance between each group determined by Bonferroni post hoc analysis. Significant effect of time was found for aspartate transaminase. Significant effect of hospitalization status was found for absolute lymphocyte count, hemoglobin, and albumin. There was a significant interaction between time and hospitalization status for absolute lymphocyte count with post hoc analysis indicating significance during hospitalization. Post hoc analysis did not indicate a significant individual interaction for hemoglobin, aspartate transaminase, or albumin. Significant (p < 0.05) effect of subgroups in post hoc analysis is indicated by *. (B) Absolute lymphocyte count was lower at all time points in the hospitalized group. There were also unique trends in each group, with nonhospitalized patients having a peak during acute infection, whereas hospitalized patients demonstrated a nadir during acute infection. Error bars represent SEM. Significance through Bonferroni post hoc analysis is indicated by *. COVID-19 = coronavirus disease 2019.
- Figure 4 COVID-19 Symptoms and PCR Positivity Duration by DMT
Duration of COVID-19 symptoms and duration of COVID-19 PCR positivity were grouped by DMT efficacy (none/other, low, mid, and high). (A) Symptom duration in days is indicated on the x axis, and DMTs grouped by efficacy are on the y axis. There were no significant differences in symptom duration based on DMT efficacy with one-way analysis of variance. A number of patients contributing to each group for symptom duration were 2 none/other, 5 low efficacy, 2 mid efficacy, and 10 high efficacy. (B) Duration of PCR positivity in days is indicated on the x axis, and DMTs grouped by efficacy are on the y axis. There was a significant association of DMT efficacy with post hoc analysis (Bonferroni) demonstrating a significant difference between high-efficacy DMT vs none/other DMT with regard to duration of PCR positivity. A number of patients contributing to each group for PCR positivity duration were 4 none/other, 5 low efficacy, 1 mid efficacy, and 9 high efficacy. Error bars indicated SEM and are not shown in samples where n = 1. Significance (p < 0.05) is indicated by *. COVID-19 = coronavirus disease 2019; DMT = disease-modifying therapy.
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