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10.1016/j.msard.2020.102359

http://scihub22266oqcxt.onion/10.1016/j.msard.2020.102359
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suck abstract from ncbi


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pmid32663793      Mult+Scler+Relat+Disord 2020 ; 45 (ä): 102359
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  • Adherence to social distancing and use of personal protective equipment and the risk of SARS-CoV-2 infection in a cohort of patients with multiple sclerosis #MMPMID32663793
  • Landi D; Ponzano M; Nicoletti CG; Cecchi G; Cola G; Mataluni G; Mercuri NB; Sormani MP; Marfia GA
  • Mult Scler Relat Disord 2020[Oct]; 45 (ä): 102359 PMID32663793show ga
  • Background Aiming to safeguard its population from COVID19 infection, Italian government provided specific advices, especially to fragile individuals such those affected by Multiple Sclerosis (MS), to respect social distancing, to arrange remote work and to use personal protective equipment (PPE). The aim of this study is to investigate real adherence to these measures among MS patients and to evaluate its impact on exposure to infection. Methods MS patients followed at the MS center of Tor Vergata University hospital, Rome, Italy were asked to complete an anonymous 35-items web-survey exploring demographics, residency, employment, social distancing habits, use of PPE, MS features and COVID19 infection data, including self-reported information about contacts with SARS-CoV-2 positive/presumed positive persons. In order to estimate adherence to social distancing and use of PPE, an overall 'Lockdown Score' (LS) on 0-10 scale was created analyzing four main domains (Working (0 - 4), Social distancing and PPE use (0 - 4), Assistance for shopping needs (0 - 2), Residency (-2 - 0)). Mean scores for several pre-defined subgroups of patients were compared using both univariable and multivariable analyses. Accuracy of the score in discriminating subjects at higher risk of coming in contact with SARS-CoV-2 positive/presumed positive individuals was calculated as the area under the receiver-operator characteristic curve (AUC). The optimal cut-off was identified and used to dichotomize LS (high/ low). Logistic regression model was applied to estimate individuals' characteristics associated with high/low LS and odds ratio of coming in contact with SARS-CoV-2 positive/presumed positive persons based on continous and dichotomised LS. Results Respondents (N = 551) had a mean(+/-SD) overall LS of 6.52+/-2.11 (Working 3.16+/-1.19, Social distancing and PPE use 2.69+/-1.33, Assistance 0.66+/- 0.62, Residency penalty applied in 4 cases). Female, disabled and unemployed individuals had significantly higher mean LS (p<0.05). The AUC of the LS was 0.68 (95% CI, 0.59-0.77) and the optimal LS cut-off for discrimination was 6.0. Consistently, female, disabled and unemployed individuals had higher odd of getting a high LS (>/= 6) compared to male, independent and employed (p<0.05). Odd of coming in contact with SARS-CoV-2 positive/presumed positive individuals was significantly reduced for one-unit increase in LS (0.74 (95% CI: 0.64-0.85)) and among individuals with high LS (0.37 (95% CI: 0.19-0.72)). Only one subject among respondents declared to have been diagnosed with COVID19. Conclusions MS patients, especially those with social unfavorable conditions, demonstrated good adherence to social distancing and use of protection equipment. Implementing domains, such as social assistance, may improve protection from infection. LS score is potentially able to identify subjects with behaviors at greater risk of infection, although it needs to be validated against MS population living in higher incidence areas.
  • |*Multiple Sclerosis[MESH]
  • |*Personal Protective Equipment[MESH]
  • |Adolescent[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |Betacoronavirus[MESH]
  • |COVID-19[MESH]
  • |Cohort Studies[MESH]
  • |Coronavirus Infections/epidemiology/*prevention & control[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Italy[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pandemics/*prevention & control[MESH]
  • |Patient Compliance/*statistics & numerical data[MESH]
  • |Pneumonia, Viral/epidemiology/*prevention & control[MESH]
  • |Risk Factors[MESH]
  • |SARS-CoV-2[MESH]
  • |Surveys and Questionnaires[MESH]


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