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1.
Int J MS Care ; 24(5): 224-229, 2022.
Article in English | MEDLINE | ID: mdl-36090243

ABSTRACT

BACKGROUND: Being a parent can be demanding and stressful, especially for people with chronic diseases such as multiple sclerosis (MS). Parenting can be disrupted by flareups, disease worsening, and other MS symptoms, including mobility problems, pain, fatigue, and cognitive impairment. Mood disorders, such as depression and anxiety, have been found to occur at much higher rates in people with MS than in the general population. Surprisingly, less is known about which factors may predict mood disorders in parents with MS. This study aims to identify potential demographic, clinical, and self-reported predictors that contribute to mood disorders measured by the Hospital Anxiety and Depression Scale. METHODS: A total of 285 parents with MS completed an anonymous online questionnaire combining sociodemographic, clinical, and family characteristics and scales, validated in Italian, related to coping strategies and social support. Associations between each variable and mood disorders were assessed using univariate and multivariate logistic regression analyses. RESULTS: Disability level, emotional and dysfunctional coping strategies, and perceived social support were significant predictors of mood disorders in parents with MS. CONCLUSIONS: These findings confirm the importance of identifying risk factors for mood disorders in parents with MS so that early intervention can minimize mood disruptions caused by the disease.

2.
Mult Scler Relat Disord ; 63: 103909, 2022 Jul.
Article in English | MEDLINE | ID: mdl-35675744

ABSTRACT

BACKGROUND: Many risk factors for the development of severe forms of Covid-19 have been identified, some applying to the general population and others specific to Multiple Sclerosis (MS) patients. However, a score for quantifying the individual risk of severe Covid-19 in patients with MS is not available. The aim of this study was to construct such score and to evaluate its performance. METHODS: Data on patients with MS infected with Covid-19 in Italy, Turkey and South America were extracted from the Musc-19 platform. After imputation of missing values, data were separated into training data set (70%) and validation data set (30%). Univariable logistic regression models were performed in the training dataset to identify the main risk factors to be included in the multivariable logistic regression analyses. To select the most relevant variables we applied three different approaches: (1) multivariable stepwise, (2) Lasso regression, (3) Bayesian model averaging. Three scores were defined as the linear combination of the coefficients estimated in the models multiplied by the corresponding value of the variables and higher scores were associated to higher risk of severe Covid-19 course. The performances of the three scores were compared in the validation dataset based on the area under the ROC curve (AUC) and an optimal cut-off was calculated in the training dataset for the score with the best performance. The probability of showing a severe Covid-19 course was calculated based on the score with the best performance. RESULTS: 3852 patients were included in the study (2696 in the training dataset and 1156 in the validation data set). 17% of the patients required hospitalization and risk factors for severe Covid-19 course were older age, male sex, living in Turkey or South America instead of living in Italy, presence of comorbidities, progressive MS, longer disease duration, higher Expanded Disability Status Scale, Methylprednisolone use and anti-CD20 treatment. The score with the best performance was the one derived using the Lasso selection approach (AUC= 0.72) and it was built with the following variables: age, sex, country, BMI, presence of comorbidities, EDSS, methylprednisolone use, treatment. An excel spreadsheet to calculate the score and the probability of severe Covid-19 is available at the following link: https://osf.io/ac47u/?view_only=691814d57b564a34b3596e4fcdcf8580. CONCLUSIONS: The originality of this study consists in building a useful tool to quantify the individual risk for Covid-19 severity based on patient's characteristics. Due to the modest predictive ability and to the need of external validation, this tool is not ready for being fully used in clinical practice to make important decisions or interventions. However, it can be used as an additional instrument to identify high-risk patients and persuade them to take important measures to prevent Covid-19 infection (i.e. getting vaccinated against Covid-19, adhering to social distancing, and using of personal protection equipment).


Subject(s)
COVID-19 , Multiple Sclerosis , Bayes Theorem , COVID-19/epidemiology , Humans , Male , Methylprednisolone , Multiple Sclerosis/epidemiology , Personal Protective Equipment
3.
Neurol Sci ; 41(11): 3273-3281, 2020 Nov.
Article in English | MEDLINE | ID: mdl-32394274

ABSTRACT

INTRODUCTION: Arm and hand function deficits are commonly in people with multiple sclerosis (PwMS). The Arm Function in Multiple Sclerosis Questionnaire (AMSQ) is a novel self-administered instrument specifically developed to evaluate upper limb function in MS. The aim of this study was to translate and adapt the AMSQ into Italian and to assess its psychometric properties in PwMS. Validity (structural, construct, and known-groups) and reliability (internal consistency, test-retest, and measurement error) were assessed. MATERIALS AND METHODS: From June 2017 to February 2018, a prospective cohort of PwMS among those followed as outpatients at the Rehabilitation Services of the Italian Multiple Sclerosis Society (AISM) of Genoa, Padua, and Vicenza was involved in the study. Construct validity of AMSQ was determined by examining correlations with the Italian version of ABILHAND, Modified Fatigue Impact Scale (MFIS), and Functional Independence Measure (FIM). RESULTS: A total of 234 PwMS were enrolled. The mean AMSQ total score was 67.3 (SD = 38.4). Factor analysis results suggested one factor. As expected, moderate to high correlation coefficients were found between AMSQ and ABILHAND (- 0.79), MFIS (0.50) and its subsets, and FIM (- 0.60) and its subsets involving upper limb functioning. PwMS with higher EDSS reported worse total score of AMSQ than patients with low disability. The internal consistency of the 31 items was high (Cronbach's α, 0.98). Test-retest reliability, as measured with ICC, was 0.96 (95% IC, 0.93-0.98), and measurement error was about 8.3 points showing good reliability. DISCUSSION: AMSQ has been adapted and validated, it is a reliable questionnaire for Italian PwMS.


Subject(s)
Multiple Sclerosis , Arm , Disability Evaluation , Humans , Italy , Multiple Sclerosis/diagnosis , Prospective Studies , Psychometrics , Reproducibility of Results , Surveys and Questionnaires
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