| Literature DB >> 36119957 |
Mahsa Ghajarzadeh1,2, Omid Mirmosayyeb3, Negar Molazadeh1, Mohammad Ali Sahraian1, Simona Bonavita4, Vahid Shaygannejad5.
Abstract
Background: Patients with multiple sclerosis (MS) are considered at higher risk of COVID-19 infection due to treatment with immune modulators and immune-suppressive agents. The exact risk factors are not clear. So, we aimed to conduct a study to determine the predictors of catching COVID-19 infection during the pandemic stage in patients with multiple sclerosis (MS).Entities:
Keywords: COVID-19; Iran; multiple sclerosis; predictor
Year: 2022 PMID: 36119957 PMCID: PMC9470912 DOI: 10.4103/ijpvm.IJPVM_480_20
Source DB: PubMed Journal: Int J Prev Med ISSN: 2008-7802
Demographic, clinical, and COVID-19 related information
| Variables | Findings |
|---|---|
| Age (Mean±SD) (Year) | 34.7±8.7 |
| Disease duration (Mean±SD) (Year) | 10.4±5.9 |
| Sex | |
| Female | 1155 (79.8%) |
| Male | 293 (20.2%) |
| Type of MS | |
| Relapsing Remitting | 1195 (82.5%) |
| Progressive Forms [progressive relapsing (PR), primary progressive (PP), secondary progressive (SP)] | 253 (17.5%) |
| Current medication | |
| INFs | 501 (34.6%) |
| Glatiramer acetate (GA) | 95 (6.6%) |
| Dimethyl fumarate (DMF) | 113 (7.8%) |
| Triflunomide | 69 (4.8%) |
| Ocrelizumab | 10 (0.7%) |
| Rituximab | 359 (24.8%) |
| Natalizumab | 12 (0.8%) |
| Azathioprine | 7 (0.5%) |
| Fingolimod | 185 (12.8%) |
| No current medication | 97 (6.7%) |
| Blood group | |
| A | 422 (29.1%) |
| B | 268 (19.8%) |
| AB | 164 (11.3%) |
| O | 576 (39.8%) |
| Vitamin D consumption. | |
| Daily | 65 (4.5%) |
| Weekly | 310 (21.4%) |
| Every two weeks | 609 (42.1%) |
| Monthly | 291 (20.1%) |
| None | 173 (11.9%) |
| Co-morbidities | |
| Diabetes | 29 (2%) |
| Hypertension | 81 (5.6%) |
| Cardiovascular disease | 25 (1.7%) |
| Hypothyroidism | 160 (11%) |
| Asthma/allergy | 107 (7.4%) |
| Living alone (yes). | 74 (5.1%) |
| Wearing masks and gloves in public places | 1184 (81.8%) |
| Implementation of social distancing | 1326 (91.6%) |
| Implementation of home-quarantine | 1312 (90.6%) |
| Family support in the implementation of quarantine | 1269 (87.6%) |
| Consuming immune-boosting supplements before pandemic | 794 (48%) |
Characteristics of COVID-19 confirmed cases
| Variables | Findings |
|---|---|
| Age (Mean±SD)(Year) | 37.5±9.3 |
| Sex | |
| Female | 20 (80%) |
| Male | 5 (20%) |
| Type of MS. | |
| Relapsing-Remitting | 20 (80%) |
| Progressive Forms (PR, PP, SP) | 5 (20%) |
| Current medication | |
| INFs | 0 |
| GA | 2 (8%) |
| Triflunomide | 2 (8%) |
| Rituximab | 5 (20%) |
| No medication | 4 (16%) |
| Blood group | |
| A | 6 (24%) |
| B | 4 (16%) |
| AB | 2 (8%) |
| O | 13 (52%) |
| Vitamin D consumption | |
| Yes | 23 (92%) |
| No | 2 (8%) |
| Comorbidities | |
| Diabetes | 0 |
| Hypertension | 2 (8%) |
| Cardiovascular disease | 2 (8%) |
| Hypothyroidism | 5 (20%) |
| Asthma/allergy | 4 (16%) |
| Living alone | 2 (85%) |
| Wearing masks and gloves in public places | 18 (72%) |
| Implementation of social distancing | 22 (88%) |
| Implementation of home-quarantine | 24 (96%) |
| Symptoms | |
| Fever | 22 (88%) |
| Cough | 21 (84%) |
| Shortness of the breath | 14 (56%) |
| Diarrhea | 3 (12%) |
| Nausea/vomiting | 5 (20%) |
| Hyposmia | 5 (20%) |
| Hypogeusia | 3 (12%) |
| Headache/vertigo | 13 (52%) |
Predictors of COVID-19 diagnosis at univariate logistic regression analysis
| OR | 95%CI | |
|---|---|---|
| Sex | 0.98 | (0.36-2.6) |
| Type of MS | 0.84 | (0.31-2.2) |
| Blood group | 0.84 | (0.61-1.16) |
| Vitamin D consumption | 1.5 | (0.36-6.7) |
| Cardiovascular disease | 5.2 | (1.1-23.7) |
| Hypothyroidism | 2 | (0.75-5.5) |
| Hypertension | 1.4 | (0.34-6.3) |
| Asthma/allergy | 2.4 | (0.82-7.2) |
| Current medication | ||
| B-cell depleting agents | 1.2 | (0.46-3.4) |
| Others |